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Center for AI Safety: Statement on AI Risk

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Center for AI Safety: Statement on AI Risk

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Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.
AI experts, journalists, policymakers, and the public are increasingly discussing a broad spectrum of important and urgent risks from AI. Even so, it can be difficult to voice concerns about some of advanced AI’s most severe risks. The succinct statement below aims to overcome this obstacle and open up discussion. It is also meant to create common knowledge of the growing number of experts and public figures who also take some of advanced AI’s most severe risks seriously.

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Florian Schütz wird Direktor des neuen Bundesamtes für Cybersicherheit

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Florian Schütz wird Direktor des neuen Bundesamtes für Cybersicherheit

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Der Bundesrat hat den heutigen Delegierten des Bundes für Cybersicherheit und Leiter des Nationalen Zentrums für Cybersicherheit (NCSC), Florian Schütz, per 1. Januar 2024 zum Direktor des neuen Bundesamtes für Cybersicherheit ernannt.

Am 2. Dezember 2022 hat der Bundesrat beschlossen, das heute dem Generalsekretariat des Eidgenössischen Finanzdepartement (EFD) angesiedelten Nationalen Zentrum für Cybersicherheit (NCSC) als neues Bundesamt ins Eidgenössischen Departement für Verteidigung, Bevölkerungsschutz und Sport (VBS) anzusiedeln. Das NCSC wird dank den Synergien mit den im VBS bereits vorhandenen Fähigkeiten im Bereich Cybersicherheit gestärkt. Nun hat der Bundesrat den bisherigen Delegierten des Bundes für Cybersicherheit, Florian Schütz, per 1. Januar 2024 zum Direktor des neuen Bundesamtes ernannt.

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E-Learning zur Informations- und Cybersicherheit

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E-Learning zur Informations- und Cybersicherheit

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Im Auftrag der Konferenz der Kantonalen Justiz- und Polizeidirektorinnen und -direktoren (KKJPD) hat der Sicherheitsverbund Schweiz (SVS) in Zusammenarbeit mit Expertinnen und Experten von Bund, Kantonen und Gemeinden sowie der Unterstützung des Institut de lutte contre la criminalité économique (ILCE) ein E-Learning für Verwaltungsangestellte erarbeitet. Dieses soll dazu beitragen, dass die Informations- und Cybersicherheit in den öffentlichen Behörden über alle Bereiche und Hierarchiestufen hinweg sichergestellt ist und gemeinsame Standards erfüllt.

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Angriff auf Schweizer IT-Dienstleister betrifft Pathé-Kinos und legt Gemeinde lahm

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Angriff auf Schweizer IT-Dienstleister betrifft Pathé-Kinos und legt Gemeinde lahm

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Eine Ransomware-Attacke gegen die Berner Unico Data AG hat weitreichende Konsequenzen. Betroffen sind zahlreiche Kundinnen und Kunden, darunter die Kinokette Pathé und eine Spitalbetreiberin.

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Angriff auf Schweizer IT-Dienstleister betrifft Pathé-Kinos und legt Gemeinde lahm

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Eine Ransomware-Attacke der Gruppe Play gegen die IT-Dienstleisterin Unico Data hat weitreichende Folgen.

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Dies ist der Hammer - Phishing E-Mail mit falscher Anrede

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Dies ist der Hammer - Phishing E-Mail mit falscher Anrede

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Phisher versuchen mit immer neuen Varianten, die Opfer zu verleiten, Ihre Zugangsdaten anzugeben. Dabei schrecken sie auch nicht davor zurück, das Opfer auf eine angebliche Veröffentlichung von intimen Bildern hinzuweisen. Allerdings funktioniert nicht immer alles nach Plan, wie ein zweites Beispiel zeigt, das dem NCSC letzte Woche gemeldet wurde.

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23.05.2023 - Phisher versuchen mit immer neuen Varianten, die Opfer zu verleiten, Ihre Zugangsdaten anzugeben. Dabei schrecken sie auch nicht davor zurück, das Opfer auf eine angebliche Veröffentlichung von intimen Bildern hinzuweisen. Allerdings funktioniert nicht immer alles nach Plan, wie ein zweites Beispiel zeigt, das dem NCSC letzte Woche gemeldet wurde.

Phishing mit Drohung

Geben Sie nie persönliche Daten wie Passwörter oder Kreditkartendaten auf einer Webseite ein, die Sie über einen Link in einer E-Mail oder Textnachricht angeklickt haben. Diese einfache Grundregel verhindert bereits viele Phishing-Versuche.

Dank der stetigen steigenden Awareness reagieren viele Internetnutzerinnen und -nutzer mittlerweile sensibel auf klassische Phishing-E-Mails, die beispielsweise mit Kontosperrung drohen oder eine Rückerstattung in Aussicht stellen. Die Angreifer versuchen deshalb die Empfänger mit immer neuen Geschichten zu überrumpeln und den kurzen Moment auszunutzen, in dem die Opfer verunsichert sind, sich keine Gedanken über die Plausibilität machen und deshalb keinen Verdacht schöpfen.

Einen besonders perfiden Fall wurde dem NCSC in der letzten Woche gemeldet. Im Namen von einer mit dem Opfer "befreundeten" Person wurde dem Opfer über eine Facebook-Nachricht mitgeteilt, dass jemand Nacktfotos von ihm ins Netz gestellt habe. Um sich vom Sachverhalt zu überzeugen soll es auf den angegebenen Link klicken. Die sich öffnende Seite imitierte Facebook und enthielt zahlreiche Kommentare, die tatsächlich darauf schliessen liessen, dass es sich bei dem Inhalt um kompromittierende Bilder handelte. Diese Kommentare sowie die Angabe, dass der Inhalt schon 947-mal geteilt wurde, dienten dazu das Opfer unter Druck zu setzen. Um die Bilder anschauen zu können, müsse aber zuerst eine Altersbestätigung erfolgen, da es sich um Erwachseneninhalt handle. Dazu müssten die Login-Daten von Facebook angegeben werden. Die Login-Daten gingen natürlich in diesem Fall nicht zu Facebook, sondern direkt an die Angreifer. Die ganze Seite war ein Bluff, um das Opfer zu verunsichern. Nach der Eingabe der Login-Daten erschien eine Seite, dass die Bilder bereits entfernt wurden.

Der Hinweis auf die Seite mit den angeblichen Nacktbildern kam wie oben erwähnt von einem Bekannten des Opfers auf Facebook und gab der Nachricht noch mehr Glaubwürdigkeit. Das NCSC geht davon aus, dass der angebliche Absender zuvor auch abgephisht wurde und die Kontaktdaten dazu benutzt werden, gezielt weitere Phishing-Nachrichten zu versenden.

Dies ist der Hammer - Phishing E-Mail mit falscher Anrede

Phishing-Versuche mit persönlicher Anrede sind immer noch selten. Vielfach verwenden die Betrüger ein unpersönliches "Guten Tag" oder "Hallo Kunde" oder benutzen die Angaben aus der E-Mail-Adresse, um daraus eine mehr oder weniger passende Anrede anzuzeigen.

Vergangene Woche ist eine neue Variante des bekannten SBB-Phishing-Versuches aufgetaucht, die mit angeblicher Ticketrückerstattung locken oder mit Swisspass-Kontosperrung drohen. In der aktuellen Variante wurde die persönliche Anrede verwendet. Im ersten Moment musste man davon ausgehen, dass die Betrüger Daten aus einem Datenabfluss verwenden, der einen sehr gezielten Angriff möglich macht. Nach den ersten Meldungen, die beim NCSC eingingen, wurde aber schnell klar, dass immer der gleiche Nachname als Anrede verwendet wurde, egal wie der Empfänger respektive die Empfängerin heisst.

Dieser Fehler seitens Angreifer zeigt exemplarisch deren Vorgehensweise. Die Angreifer hacken sich in E-Mail-Konten und durchsuchen den Posteingang nach brauchbarem Material. E-Mails von Firmen, wie in diesem Fall eine Ticketrückerstattung der SBB, sind für die Betrüger natürlich interessant und werden anschliessend angepasst und mit einem Phishing-Link versehen. Die Betrüger müssen sich so keine Gedanken über die Korrektheit der Sprache machen. Diese E-Mails sind in perfektem Deutsch, Französisch oder Italienisch, ausser natürlich die Bereiche, die von den Betrügern angepasst wurden. In diesem Falle verwendeten die Angreifer überall die Anrede "Herr Hammer" und vergassen auch diese zu personalisieren.

Dieser Fall zeigt auch wie wichtig Meldungen sind, die Sie ans NSCS machen. Nur durch die zahlreichen Meldungen konnte das NCSC den Fall schnell einschätzen und erkennen, dass es sich nicht um gezielte Angriffe handelt und entsprechend warnen.

Geben Sie nie persönliche Daten wie Passwörter oder Kreditkartendaten auf einer Webseite ein, die Sie über einen Link in einer E-Mail oder Textnachricht angeklickt haben;

Installieren Sie, wenn immer möglich eine Zwei-Faktor-Authentifizierung. Dies bietet eine zusätzliche Schutzebene, um zu verhindern, dass Ihr Konto gehackt wird;

Keine Bank und kein Kreditkarteninstitut wird Sie jemals per E-Mail auffordern, Passwörter zu ändern oder Kreditkartendaten zu verifizieren;

Bedenken Sie, dass E-Mail-Absender leicht gefälscht werden können;

Seien Sie skeptisch, wenn Sie E-Mails bekommen, die eine Aktion von Ihnen verlangen und ansonsten mit Konsequenzen drohen (Geldverlust, Strafanzeige oder Gerichtsverfahren, Konto- oder Kartensperrung, Verpasste Chance, Unglück).

Aktuelle Zahlen und Statistiken

Die Anzahl Meldungen der letzten Woche nach Kategorien sind publiziert unter:
Aktuelle Zahlen

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Woche 20: Dies ist der Hammer - Phishing E-Mail mit falscher Anrede

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23.05.2023 - Phisher versuchen mit immer neuen Varianten, die Opfer zu verleiten, Ihre Zugangsdaten anzugeben. Dabei schrecken sie auch nicht davor zurück, das Opfer auf eine angebliche Veröffentlichung von intimen Bildern hinzuweisen. Allerdings funktioniert nicht immer alles nach Plan, wie ein zweites Beispiel zeigt, das dem NCSC letzte Woche gemeldet wurde.

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Wie das NTC prüfen will, was andere nicht prüfen

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Wie das NTC prüfen will, was andere nicht prüfen

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Das Nationale Testinstitut für Cybersicherheit (NTC) hat es sich zum Ziel gesetzt, quasi ein Pendant zur Empa im Cyberbereich zu werden - umfassend, transparent und zum Wohle der Gesellschaft. Wie es auswählt, was es prüft, welche Meilensteine es nun anpeilt und weshalb die Schweiz überhaupt ein NTC braucht, sagt Raphael Reischuk, Mitgründer des NTC und Mitglied des Cybersecurity Advisory Board der SATW, im Interview.

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Was ist die Idee hinter dem NTC?

Raphael Reischuk: In der Schweiz werden viele digitale Geräte und cyberphysische Komponenten betrieben, die nicht oder zu wenig auf Schwachstellen geprüft werden. Gleichzeitig kommen jeden Tag viele neue Schwachstellen ans Licht in Produkten, die nicht gründlich genug getestet wurden, bevor sie auf den Markt kamen. Genau da setzen wir an: Wir testen, was sonst nicht getestet wird.

Und was ist Ihre Rolle beim NTC?

Meine Kollegen nennen mich gern den "geistigen Vater des NTC" (lacht). Zusammen mit Thomas Held, dem ehemaligen Direktor der Denkfabrik Avenir Suisse, und einer 12-köpfigen Expertengruppe aus Wirtschaft und Forschung konzipierte ich in den Jahren 2019 und 2020 das Institut. Darauf aufbauend erfolgte die Gründung des Instituts zusammen mit Andreas Kaelin als Geschäftsführer sowie dem Zuger Regierungsrat Heinz Tännler und Nationalrat Franz Grüter als Präsident respektive Vizepräsident des Vorstands. Abgesehen von meiner Rolle als Vorstandsmitglied bin ich weiterhin einer der Impulsgeber, der die generelle strategische Richtung angibt, in der wir uns entwickeln wollen. Denn das NTC bleibt weiterhin mein Baby (lacht).

Wir sind bereits seit der Gründung im Dezember 2020 operativ. Es war mir sehr wichtig, keine Organisation zu gründen, die zunächst eine Ewigkeit mit sich selbst beschäftigt ist. Unmittelbar nach dem Start des NTCs waren wir damit beschäftigt, das Covid-Zertifikat zu analysieren - zusammen mit dem Nationalen Zentrum für Cybersicherheit (NCSC) sowie dem Bundesamt für Informatik und Telekommunikation (BIT). Seitdem haben wir eine Reihe von Untersuchungen durchgeführt.

Wie gross ist das Team von Testexperten aktuell?

Derzeit beschäftigen wir drei festangestellte Testpersonen. Und wir werden weiter wachsen, auch wenn der Fachkräftemangel es nicht gerade leicht macht, die echten Top-Experten zu bekommen. Wir werden aber trotzdem keine Kompromisse bei der Qualität eingehen, um die bestmögliche Leistung zu erbringen.

Ist es für Sie - im Vergleich zur Privatwirtschaft - einfacher oder schwieriger, Fachkräfte zu rekrutieren?

Ich denke, für uns ist es tatsächlich ein bisschen einfacher. Als Non-Profit-Organisation agieren wir frei von den kommerziellen Interessen der Marktteilnehmer. Somit können wir uns vollständig unserem Ziel widmen: Wir testen, was sonst nicht getestet wird. Dieser klare Leitsatz beschreibt unsere Daseinsberechtigung - also neudeutsch unseren "Purpose" - recht gut und macht uns zusätzlich noch interessanter für die Fachkräfte. Wir wollen mit unseren Dienstleistungen zwar definitiv nicht mit der Privatwirtschaft konkurrieren. Aber wenn es um den Talentmarkt geht, schöpfen wir aus demselben Topf.

Was sind die nächsten Meilensteine, die Sie mit dem NTC anpeilen?

Grob gesagt, geht es nun darum zu beweisen, dass die 7,5 Millionen Franken, die der Kanton Zug investiert hat, eine gewinnbringende Investition für die gesamte Schweiz sind. Das können wir zeigen, indem wir unserem Versprechen gerecht werden, genau die Dinge zu prüfen, die eine kritische Relevanz für die Schweiz haben, aber derzeit noch nicht genügend untersucht werden. Das ist das Ziel, das wir bis Ende 2024 erreichen möchten.

Können Sie ein Beispiel für so ein Produkt nennen?

Natürlich. Vor kurzem prüften wir beispielsweise die Tiktok-App. In einigen Staaten ist diese App gesperrt - oder es wird aktuell darüber nachgedacht, sie zu sperren. Dennoch muss die Schweiz selbst eine unabhängige Meinung darüber bilden können, wie gefährlich diese App wirklich ist.

Diese 7,5 Millionen vom Kanton Zug werden nicht ewig halten. Wer finanziert darüber hinaus das NTC?

Wir setzen diese Mittel sehr bedacht ein, deshalb wird das Geld noch eine Zeit lang reichen. Wir sind sehr dankbar dafür, dass der Kanton Zug uns so grosszügig finanziell unterstützt. Nun hoffen wir, dass wir weitere Kantone und auch den Bund überzeugen können. So wollen wir eine Basisfinanzierung sicherstellen. Wenn wir einen Beitrag zur Sicherheit des Landes leisten, dann ist es auch Aufgabe der Öffentlichkeit, die Finanzierung sicherzustellen. Denkbar ist auch ein Finanzierungsmodell, wie es beispielsweise die Rega nutzt. Das heisst, Gönner zahlen einen kleinen Beitrag, ohne eine direkte Gegenleistung zu erwarten - also à fonds perdu.

Können Unternehmen das NTC beauftragen, ein Produkt zu testen?

Ja, aber ein Auftraggeber, der eine Prüfung finanziert, darf nicht sein eigenes Produkt testen lassen. Das ist in unseren FAQ auf der Website klar beschrieben. Wenn beispielsweise die Swisscom jedoch Netzwerkkomponenten eines anderen Herstellers testen will, bevor sie diese einsetzt, könnten wir den Auftrag annehmen.

Was für Verbindungen hat das NTC zur Privatwirtschaft, zur Forschung und zur Politik?

Wir wollen das Rad nicht neu erfinden, deswegen greifen wir auf die zahlreichen Kompetenzen zurück, die in der Schweiz schon vorhanden sind. Wir pflegen beispielsweise Kontakte zu ETH und EPFL, zum NCSC, zum CyberPeace Institute, zum Cyber-Defence Campus von Armasuisse und natürlich auch zur Privatwirtschaft. Der Cyberbereich entwickelt sich rasant - ohne mit anderen zusammenzuarbeiten, kommt niemand sehr weit.

Sie sagten, das nächste Ziel sei es, zu beweisen, dass die Schweiz das NTC braucht. Aber braucht die Schweiz das NTC? Es gibt doch schon genügend privatwirtschaftliche Unternehmen, die IT-Produkte und -Lösungen auf ihre IT-Mängel prüfen.

Die Privatwirtschaft wird nur dann aktiv, wenn ein Business Case dahintersteht. Der Markt ist jedoch voller Produkte, auf die dies nicht zutrifft. Heutzutage bringen viele Anbieter ihre Produkte einfach möglichst schnell auf den Markt, um sich einen Vorteil gegenüber dem Wettbewerb zu verschaffen. Und IT-Security wird dabei oft als eine ausbremsende Blockade verstanden. Zudem gibt es bei vielen dieser Produkte niemanden, der dafür zahlen würde, deren Cybersicherheit zu prüfen. Deswegen braucht es eine neutrale, unabhängige Stelle, die selbstständig aktiv wird, wenn sie Risiken erkennt und diese prüft - zum Wohle der Gesellschaft. Die Privatwirtschaft, die ihre eigenen kommerziellen Interessen verfolgt, deckt diesen Auftrag nicht ab - was völlig verständlich ist. Deshalb springen wir hier in die Bresche.

Was halten Sie eigentlich von der umgangssprachlichen Bezeichnung "Cyber-Empa" für das NTC?

Als wir den Ausdruck zum ersten Mal hörten, löste er im Team Freude aus. Die Empa ist eine etablierte Institution in der Schweiz und es ist sehr erfreulich, mit ihr verglichen zu werden. Aber eigentlich passt der Vergleich nicht so gut.

Weshalb nicht?

Die Empa prüft Baustoffe und Materialien. Sie kann davon ausgehen, dass die Eigenschaften, die sie in den Tests dieser Stoffe feststellt, sich auch fünf Jahre später nicht verändert haben werden. Das ist im Cyberspace völlig anders. Wir prüfen digitale Technologie. Und diese entwickelt sich rasant weiter. Das ist der entscheidende Unterschied: Im Gegensatz zur Empa können wir ein Produkt nicht einmal prüfen und erwarten, dass diese Einschätzung für mehrere Jahre gültig sein wird. Eigentlich müssten wir alles jeden Tag aufs Neue prüfen, um eine fundierte Aussage machen zu können über eine bestimmte Hard- oder Software.

Ich vermute, das heisst, dass das NTC keine Zertifizierungen für geprüfte Produkte aushändigen wird.

Richtig. Zertifizierungen sind nicht zielführend und sie setzen falsche Anreize. Einerseits werden Unternehmen aus wirtschaftlichen Interessen nur gerade so viel tun, wie sie müssen, um eine Zertifizierung knapp zu erreichen - aber nur selten mehr. Und andererseits ist bei einem zertifizierten Produkt nicht klar, ob dieses Gütesiegel nach dem nächsten Softwareupdate noch gültig ist. Ausserdem widerspricht es unserem Neutralitätsanspruch: Wir wollen keine Zertifizierungen ausstellen, die ein Hersteller zur Stärkung seiner Marktposition nutzen könnte. Diese Einschätzung bezieht sich allerdings nur auf die Zertifizierung von Produkten. Für Prozesse sind Zertifizierungen wie etwa ISO 27001 durchaus sinnvoll.

Was halten Sie von Angeboten wie Bug-Bounty-Programme und Pentesting-Dienstleistungen?

Beide sind sehr wichtige Instrumente - wir arbeiten auch mit Anbietern aus diesen Bereichen zusammen. Aber für Bug-Bounty-Programme und Pentesting-Services benötigt es immer einen Auftraggeber im Hintergrund, der die finanziellen Mittel bereitstellt. Und wie gesagt, bei vielen Produkten auf dem Markt ist dieser Auftraggeber nicht gegeben.

Kommen Sie mit Ihren Testdienstleistungen hier der Privatwirtschaft nicht in die Quere?

Nein, denn wir bedienen ein anderes Segment als die Privatwirtschaft. Wenn ein Unternehmen ein eigenes Produkt testen will, bevor es auf den Markt kommt, wird das über privatwirtschaftliche Security-Firmen abgewickelt - nicht über das NTC. Wir kommen nur dann ins Spiel, wenn wir das Gefühl haben, dass ein Produkt bislang nicht getestet wurde. Folglich schnappen wir keiner Firma einen Auftrag weg.

Wie entscheiden Sie, welche Produkte getestet werden sollten?

Wir haben einen grossen Backlog, der auf zahlreichen Informationsquellen und Sensoren im Feld beruht. Die Einträge in diesem Backlog werden regelmässig priorisiert - dabei achten wir auf Merkmale wie etwa das Schadenspotenzial und die Wahrscheinlichkeit, mit der dieser Schaden eintreten könnte. Anhand dieser Priorisierung arbeiten wir den Backlog ab mit den Ressourcen, die wir haben.

Wie läuft so ein NTC-Test ab?

Grundsätzlich überlegen sich unsere Prüfer bei jedem Produkt und bei jeder Dienstleistung, wofür sie konzipiert wurde und wie sie missbräuchlich genutzt werden könnte. Dabei fragen sie sich, was die Entwickler vielleicht übersehen haben, was für Schwachstellen sie möglicherweise - bewusst oder unbewusst - eingebaut haben. Dafür muss man sowohl die technische als auch die Business-Seite verstehen. Die gefundenen Schwachstellen werden sauber dokumentiert und dem Hersteller mitgeteilt, damit dieser die Sicherheitslücken schliessen kann.

Was passiert, wenn der Hersteller nicht reagiert? Was für Mittel stehen Ihnen zur Verfügung, um das Problem zu lösen?

Es gibt eine Reihe von Eskalationsstufen, mit denen wir versuchen, den Druck sukzessiv zu erhöhen. Meldet sich der betroffene Anbieter nach einer definierten Frist nicht, schalten wir die nächste Instanz ein. Das könnte beispielsweise das NCSC sein. Nach Ablauf einer weiteren Frist, könnten wir auch die Medien und die Öffentlichkeit informieren, um den Druck weiter zu erhöhen. Dabei halten wir uns an die branchenüblichen Responsible-Disclosure-Prozesse.

Wie reagieren Unternehmen, wenn Sie wegen Schwachstellen kontaktiert werden?

Die Mehrheit der Unternehmen schätzt unsere Informationen und setzt alles daran, die Schwachstelle zu beheben. Es gibt aber auch Unternehmen, die solche Hinweise ignorieren - oder noch schlimmer: Sie verklagen die Personen, die die Schwachstellen gefunden haben.

Was für Garantien gibt es, dass die Prüfungen des NTC tatsächlich ohne Beeinflussung stattfinden?

Die wichtigste Garantie ist unsere finanzielle Unabhängigkeit. Wir haben keine Geldgeber im Hintergrund, die ihre eigenen Interessen verfolgen. Zudem führen wir sorgfältige Background-Checks bei unseren Mitarbeitenden durch.

Schwachstellen in IT-Produkten sind heutzutage leider keine Seltenheit. Inwiefern müssen wir Hersteller stärker zwingen, die IT-Sicherheit ernst zu nehmen? Brauchen wir in diesem Bereich striktere Regulierungen?

Ja, es braucht deutlich mehr Regulation - bei der Lebensmittel- und Automobilindustrien ist das ja auch so. Ist es nicht möglich, diese Regulierungen global durchzusetzen, müssen wir Vorschriften bei der Einführung und Inverkehrssetzung von Produkten aufstellen. Solche Regeln müssen nicht zwingend sperrig sein. Aber sie müssen einen gewissen Basisschutz abdecken. Ich rede hier von ganz einfachen Sachen. So sollten Geräte - insbesondere IoT-Geräte - keine Standardpasswörter haben dürfen. Jedes Gerät muss ein individuelles Passwort haben - oder die Geräte müssen vor der erstmaligen Nutzung die User auffordern, das Passwort zu ändern. Solche Grundregeln sind essenziell für die Sicherheit der Gesellschaft und der Wirtschaft. Essenziell, aber nicht trivial. Deswegen werden wir wohl noch die nächsten 5 bis 10 Jahre darüber diskutieren.

Der Kanton Zug beteiligt sich auch am Aufbau der Plattform ITSec4KMU. Somit kommen derzeit zwei wichtige Projekte für die IT-Sicherheit aus dem Kanton. Was genau macht Zug zum Cybersecurity Hub der Schweiz?

Dafür gibt es mehrere Gründe. Ein Faktor ist sicherlich die glückliche finanzielle Ausgangslage, in der sich der Kanton befindet. Ferner hat der Kanton Zug auch einen gewissen Unternehmergeist; er ist neuen Themen gegenüber nicht abgeneigt, sondern begegnet diesen mit offenen Armen. Das sieht man auch am Zuger Crypto Valley. Wer solche technologischen Themen vorantreibt, muss auch die IT-Sicherheit im Auge behalten. Genau das erkannte der Kanton Zug und lancierte deshalb diese beiden Security-Projekte.

Was ist Ihrer Meinung nach zurzeit das grösste IT- oder Cyberproblem?

Das grösste Problem derzeit sind generative Sprachmodelle, wie sie etwa ChatGPT nutzt. Über den Chatbot wird gerade eine Technologie auf die grosse Mehrheit der Bevölkerung losgelassen, deren Konsequenzen wir bei weitem noch nicht verstanden haben. Nun integrieren auch Apps wie Snapchat eine Schnittstelle zu ChatGPT. Solche auf Machine Learning gestützten Chatbots können beispielsweise falsche Identitäten vorgaukeln und Fake News generieren und diese verbreiten - und das personalisiert und automatisiert! Das wird eine massive Zerreissprobe für unsere Demokratie.

Wie meinen Sie das?

Die grösste Gefahr für die Gesellschaft besteht darin, dass Ableger der Künstlichen Intelligenz es wirklich jedem einfach machen, diese Technologie zu nutzen. Das schliesst auch Cyberkriminelle mit ein: ChatGPT beispielsweise senkt die Einstiegshürde markant für Möchtegern-Hacker. Jeder, der sich zuhause langweilt und noch keinen moralischen Kompass entwickelt hat, wird nicht mehr auf die Idee kommen, Graffitis an Hauswände zu malen. Stattdessen wird er mit ChatGPT herumspielen und kommt damit wahrscheinlich schnell zu ersten Erfolgen, die ihn motivieren, weiterzumachen. ChatGPT kann nämlich auch Schwachstellen in Source Code finden, Exploits dafür generieren und diese automatisch ausrollen. Die Wahrscheinlichkeit, dass junge Menschen auf die falsche Bahn kommen, ist somit massiv höher als früher.

Wie kann man dem entgegenwirken?

Die technologische Entwicklung kann man nicht stoppen. Deswegen ist es auch nicht sinnvoll, dies via Moratorien zu versuchen. Was wir aber verhindern müssen, ist die massenhafte Verbreitung solcher Technologien. ChatGPT knackte die Marke von 100 Millionen Nutzerinnen und Nutzern bedeutend schneller als Facebook und Instagram. So eine Verhaltensänderung kann man nicht erzwingen. Aber es ist trotzdem etwas, das die Menschheit lernen muss. Unerprobte Technologien in einem so frühen Stadium öffentlich zugänglich zu machen, noch dazu via Snapchat massenhaft auch an Minderjährige, ist aus meiner Sicht unverantwortlich. Medikamente werden ja auch nicht verschrieben oder in Apotheken angeboten, während sie noch erforscht werden. Das gilt für viele Produktkategorien wie etwa auch Fahrzeuge. Neue Technologien, die die Gesellschaft nachhaltig verändern können, sollten zunächst in kleinen Testgruppen untersucht werden. Denn wir dürfen die Entscheidung, wie sich die Welt entwickelt, nicht einer Handvoll CEOs von grossen Unternehmen überlassen.

Die grenzenlos scheinenden Möglichkeiten von ChatGPT sind derzeit in aller Munde. Von diesen können aber auch Cyberkriminelle Gebrauch machen. Was also bedeutet der Chatbot für die Security? Dieser Frage gingen Netzmedien und Check Point in einem gemeinsamen Webinar nach. Lesen Sie hier mehr dazu.
Wenn Sie mehr zu Cybercrime und Cybersecurity lesen möchten, melden Sie sich hier für den Newsletter von Swisscybersecurity.net an. Auf dem Portal lesen Sie täglich News über aktuelle Bedrohungen und neue Abwehrstrategien.

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Wie das NTC prüfen will, was andere nicht prüfen

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Das Nationale Testinstitut für Cybersicherheit (NTC) hat es sich zum Ziel gesetzt, quasi ein Pendant zur Empa im Cyberbereich zu werden - umfassend, transparent und zum Wohle der Gesellschaft. Wie es auswählt, was es prüft, welche Meilensteine es nun anpeilt und weshalb die Schweiz überhaupt ein NTC braucht, sagt Raphael Reischuk, Mitgründer des NTC und Mitglied des Cybersecurity Advisory Board der SATW, im Interview.

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StatBot.swiss: mit offenen Daten diskutieren

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StatBot.swiss: mit offenen Daten diskutieren

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Mit dem Projekt StatBot.swiss soll ein Chatbot entwickelt werden, der nach dem Frage-Antwort-Prinzip mit den offenen Daten der öffentlichen Verwaltung (Open Government Data, OGD) in der Schweiz interagieren kann. Federführend sind derzeit das Kompetenzzentrum für Datenwissenschaft (DSCC) und die Konferenz der regionalen statistischen Ämter der Schweiz (KORSTAT). Sie werden dabei von der Digitalen Verwaltung Schweiz (DVS) und der Zürcher Hochschule für Angewandte Wissenschaften (ZHAW) unterstützt. Ein erster Prototyp des Chatbots soll Ende 2023 vorliegen.

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The Underground History of Russia’s Most Ingenious Hacker Group

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The Underground History of Russia’s Most Ingenious Hacker Group

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WESTERN CYBERSECURITY intelligence analysts who their "favorite" group of foreign state-sponsored hackers is—the adversary they can't help but grudgingly admire and obsessively study—and most won't name any of the multitudes of hacking groups working on behalf of China or North Korea. Not China's APT41, with its brazen sprees of supply chain attacks, nor the North Korean Lazarus hackers who pull off massive cryptocurrency heists. Most won't even point to Russia's notorious Sandworm hacker group, despite the military unit's unprecedented blackout cyberattacks against power grids or destructive self-replicating code.

Instead, connoisseurs of computer intrusion tend to name a far more subtle team of cyberspies that, in various forms, has silently penetrated networks across the West for far longer than any other: a group known as Turla.

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The Underground History of Russia’s Most Ingenious Hacker Group

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From USB worms to satellite-based hacking, Russia’s FSB hackers, known as Turla, have spent 25 years distinguishing themselves as “adversary number one.”

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Killnet, grandeur et décadence d'un groupe de cybercriminels

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Killnet, grandeur et décadence d'un groupe de cybercriminels

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Dans le cybercrime, il ne fait pas bon être patriote. En tout cas pas pour la mère patrie russe, comme en fait l'amère expérience le groupe Killnet.
C'est une annonce inattendue qu'a faite le groupe de cybercriminels russes Killnet en ce mois de mai : les hackers ouvrent une marketplace de cryptomonnaies, et tous les internautes sont invités à l'utiliser. Bien sûr, le groupe promet la plus grande discrétion à ses utilisateurs. Une décision originale mais pas si surpenante que ça pour qui a suivi les déboires récents de cette ex star du cybercrime. Car Killmilk, le chef de cette ex star du cybercrime, tente en réalité tout simplement de remettre dans le vert les finances du groupe, mises à mal par une série de décisions malencontreuses depuis le début du conflit entre la Russie et l'Ukraine.

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Dans le cybercrime, il ne fait pas bon être patriote. En tout cas pas pour la mère patrie russe, comme en fait l'amère expérience le groupe Killnet.

C'est une annonce inattendue qu'a faite le groupe de cybercriminels russes Killnet en ce mois de mai : les hackers ouvrent une marketplace de cryptomonnaies, et tous les internautes sont invités à l'utiliser. Bien sûr, le groupe promet la plus grande discrétion à ses utilisateurs. Une décision originale mais pas si surpenante que ça pour qui a suivi les déboires récents de cette ex star du cybercrime. Car Killmilk, le chef de cette ex star du cybercrime, tente en réalité tout simplement de remettre dans le vert les finances du groupe, mises à mal par une série de décisions malencontreuses depuis le début du conflit entre la Russie et l'Ukraine.

Précisément, cette chute du groupe a commencé le 24 février 2022. Au départ, Killnet était, comme tous les groupes de cybercriminels, composé de membres hétéroclites réunis dans le seul but de gagner de l'argent par des moyens illégaux. Mais tout change lorsque Killmilk déclare que leur nouvelle mission est d'appuyer leur mère patrie la Russie dans sa guerre contre l'Ukraine. Désormais, seuls les cybercriminels russes ethniques ont le droit de rester au sein du groupe. Ce changement de positionnement vers l'hacktivisme fait perdre à Killnet un nombre important de membres et surtout l'objectif n'est plus de gagner de l'argent mais de nuire à des pays pro-Ukraine. Si au début les opérations se passent bien, les fonds du groupe se retrouvent vite dans le rouge. Faute d'argent il doit notamment cesser ses cyberattaques ciblant le Japon.

C'est que l'hacktivisme consomme autant de ressources que le cybercrime : il faut développer des outils pour les attaques, scanner les failles utilisables et payer les cybercriminels. Mais voilà, il ne rapporte rien car on est plus dans le paradigme de criminels qui paralysent dans un but financier, on est dans le politique et donc aucune rançon ne peut être demandée... Le chef des hackers espérait obtenir un statut équivalent à celui de Wagner et des autres SMP (société militaire privée) russes, avec salaires versés par l'Etat, aide logistique et bien sûr reconnaissance dans la sphère publique comme défenseurs de la patrie, mais rien de tout cela n'est arrivé.

Pour pallier ce manque d'argent, Killnet organise une collecte de fonds et des pubs sont postées sur des Telegram pro-russes. La collecte n'atteint pas les objectifs fixés et le groupe est toujours sur la corde raide. Il doit très vite trouver de nouvelles entrées d'argent, une idée est alors avancée : affilier d'autres groupes de cybercriminels. L' affiliation n'est pas un phénomène nouveau dans le monde cybercriminel voire criminel. Les règles sont les suivantes : je t'autorise à utiliser certains de mes outils dans tes cyberattaques mais en échange tu dois me verser un impôt. La campagne d'affiliation est alors lancée. Malgré des recrues bien connues comme anonymous soudan, celle-ci ne permet toujours pas de faire rentrer le groupe dans ses frais.

Finalement début mai, le groupe décide de tout simplement revenir à sa première forme, et annonce redevenir un acteur cybercriminel. Il explique aussi devenir une compagnie de mercenaires et donne même le montant des contrats selon la mission. C'est un aveu d'échec, et cette nouvelle mue ne semble même pas avoir apporté le résultat escompté vu l'ouverture de cette marketplace de cryptomonnaie.

Cette chute de Killnet est la démonstration qu'être hacktiviste et cybercriminel sont deux choses très différentes. L'hacktiviste occupe souvent un "vrai" travail mais le cybercriminel vit uniquement des cyberattaques. Si du jour au lendemain on lui coupe l'accès aux revenus qu'il en tire, tout s'arrête pour lui. C'est exactement ce détail que Killnet a oublié et les conséquences s'en ressentent encore aujourd'hui.

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Killnet, grandeur et décadence d'un groupe de cybercriminels

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Dans le cybercrime, il ne fait pas bon être patriote. En tout cas pas pour la mère patrie russe, comme en fait l'amère expérience le groupe Killnet. C'est une annonce inattendue qu'a faite le groupe de cybercriminels russes Killnet en ce mois de mai : les hackers ouvrent une marketplace de cryptomonnaies, et tous les internautes sont invités à l'utiliser.

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Defensive Cyber Warfare Lessons from Inside Ukraine

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Defensive Cyber Warfare Lessons from Inside Ukraine

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In late 2021, U.S. Cyber Command’s Cyber National Mission Force (CNMF) deployed to Ukraine its largest hunt-forward operation (HFO) to date. Like a traditional reconnaissance element, these U.S. Marine Corps, Navy, and Coast Guard defensive cyber operators and intelligence analysts hunted and gained insight into Russian malicious cyber activity as tanks massed along Ukraine’s border. They worked in-country, side by side with senior Ukrainian officials, for nearly 70 days to assist in the cyber defense of multiple critical networks.

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Defensive Cyber Warfare Lessons from Inside Ukraine

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U.S. hunt-forward teams show the power of partnership and early engagement.

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Addressing Russian and Chinese Cyber Threats: A Transatlantic Perspective on Threats to Ukraine and Beyond

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Addressing Russian and Chinese Cyber Threats: A Transatlantic Perspective on Threats to Ukraine and Beyond

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In an interconnected world, cyberattacks are becoming more frequent and sophisticated. Building resilience against this asymmetric threat is critical for countries to protect their economies, critical infrastructure, and democratic institutions. However, cyberattacks do not respect borders, and no country can address this threat alone. The strength and longevity of the transatlantic partnership between the EU and the U.S. presents a unique opportunity to address this strategic threat through international cooperation. Through an analysis of cyberwarfare in the ongoing war in Ukraine, this paper proposes policy recommendations to enhance transatlantic coordination and cooperation against current and future adversaries in a new era of strategic competition. Ultimately, a stronger transatlantic partnership is critical for protecting international democratic norms, building resilience against cyber threats, and strengthening global security and stability.
This paper addresses and presents policy recommendations for two significant challenges:

Challenge 1: Curtailing Russia’s ability to support war ambitions in Ukraine

Challenge 2: Defending the transatlantic partners against the Chinese cyberwarfare threat

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Belfer Center for Science and International Affairs

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Addressing Russian and Chinese Cyber Threats: A Transatlantic Perspective on Threats to Ukraine and Beyond

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In an interconnected world, cyberattacks are becoming more frequent and sophisticated. Building resilience against this asymmetric threat is critical for countries to protect their economies, critical infrastructure, and democratic institutions. However, cyberattacks do not respect borders, and no country can address this threat alone.

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Influence Operations of China, Russia, and the Soviet Union: A Comparison

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Influence Operations of China, Russia, and the Soviet Union: A Comparison

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Influence Operations of China, Russia, and the Soviet Union: A Comparison

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Private Eyes: China's Embrace of Open-Source Military Intelligence | Recorded Future

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Private Eyes: China's Embrace of Open-Source Military Intelligence | Recorded Future

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The People’s Liberation Army (PLA) is using new collection, processing, and analysis technologies to exploit the massive amount of open-source information available from the internet and other sources for military intelligence purposes. A growing ecosystem of private companies, state-owned enterprises, state-run research organizations, and universities is supporting the PLA’s push to leverage open-source intelligence (OSINT) by providing research services, platforms, and data. The PLA almost certainly views OSINT as an increasingly valuable source of military intelligence that can support decision-making and necessitates the use of new collection, processing, and analysis technologies, which the PLA and China’s defense industry are actively developing.

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Chinese Espionage Operation ‘Volt Typhoon’ Targets US

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Chinese Espionage Operation ‘Volt Typhoon’ Targets US

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Volt Typhoon, a state-sponsored Chinese espionage actor, has managed to infiltrate US infrastructure networks., warned a joint Cybersecurity Advisory (CSA) issued by the United States and its allies. However, China has rejected the claim calling the advisory a “collective disinformation campaign”.
The Chinese espionage group, which has been active since mid-2021, has conducted several cyber attacks targeting critical infrastructure organizations in Guam and networks across the United States, noted Microsoft security report.
The Volt Typhoon campaign, which is mainly working towards gathering information and espionage, is refining itself to develop capabilities that could gravely impact the communications infrastructure between Asia and the United States.
The joint advisory aims to alert organizations of the activities and techniques used by the state-sponsored Chinese hackers and how the same can be applied worldwide.

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Chinese Espionage Operation ‘Volt Typhoon’ Targets US

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The Volt Typhoon has been carefully running its operations to blend in with legitimate network activity and stay undetected.

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President Biden warns artificial intelligence could ‘overtake human thinking’

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President Biden warns artificial intelligence could ‘overtake human thinking’

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President Joe Biden on Thursday amplified fears of scientists who say artificial intelligence could "overtake human thinking" in his most direct warning to date on growing concerns about the rise of AI.
Biden brought up AI during a commencement address to graduates of the Air Force Academy in Colorado Springs, Colo. while discussing the rapid transformation of technology that he said could "change the character" of future conflicts.
"It's not going to be easy decisions, guys," Biden said. "I met in the Oval Office with eight leading scientists in the area of AI. Some are very worried that AI can actually overtake human thinking and planning. So we've got a lot to deal with. An incredible opportunity, but a lot do deal with."

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President Biden warns artificial intelligence could ‘overtake human thinking’

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President Biden’s comments on artificial intelligence marked his most direct warning yet on growing concerns about the rise of AI.

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US senators introduce Digital Platform Commission Act

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US senators introduce Digital Platform Commission Act

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U.S. Sens. Michael Bennet, D-Colo., and Peter Welch, D-Vt., introduced the Digital Platform Commission Act. The proposed legislation would create a Federal Digital Platform Commission "with the mandate, jurisdiction, and tools to develop and enforce rules for a sector that has gone virtually unregulated" — artificial intelligence and social media. "We need an expert federal agency that can stand up for the American people and ensure AI tools and digital platforms operate in the public interest," Bennet said.

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U.S. Sens. Michael Bennet, D-Colo., and Peter Welch, D-Vt., introduced the Digital Platform Commission Act. The proposed legislation would create a Federal Digital Platform Commission "with the mandate, jurisdiction, and tools to develop and enforce rules for a sector that has gone virtually unregulated" - artificial intelligence and social media. "We need an expert federal agency that can stand up for the American people and ensure AI tools and digital platforms operate in the public interest," Bennet said.
Full Story

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US senators introduce Digital Platform Commission Act

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U.S. Sens. Michael Bennet, D-Colo., and Peter Welch, D-Vt., introduced the Digital Platform Commission Act. The proposed legislation would create a Federal Digital Platform Commission "with the mandate, jurisdiction, and tools to develop and enforce rules for a sector that has gone virtually unregulated" - artificial intelligence and social media.

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Twenty-Five Years of White House Cyber Policies

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Twenty-Five Years of White House Cyber Policies

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Twenty-five years ago, on May 22, 1998, the Clinton administration published the White House’s first-ever national cyber policy: Presidential Decision 63 (PDD 63). On March 2, 2023, the Biden administration published the latest White House cyber strategy, the National Cybersecurity Strategy (NCS).
In comparison with other lingering national issues, such as climate change or immigration, this article highlights a broad cyber-policy consensus across three Democratic and two Republican administrations. New administrations haven’t torn down the initiatives of their predecessors; rather, each White House has built on and refined them. There is a downside to this consensus and teamwork, however. Despite the various iterations of cyber strategies (and the effort of those who worked to create and implement them) over the years, many underlying cyber problems facing the United States today are worse than they were in 1998. Accordingly, something needs to change if the impact of this strategy is going to be any different.

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The Biden Administration’s Cyber Plans for Critical Infrastructure

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The Biden Administration’s Cyber Plans for Critical Infrastructure

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Securing critical infrastructure from cyber threats through mandatory minimum standards is a core pillar of the Biden Administration’s National Cybersecurity Strategy. The executive branch is utilizing existing authorities to implement minimums where they exist and developing new mandates where there are gaps. This event will highlight sectors where the administration has utilized authorities to enact baseline cybersecurity requirements, discuss implementation, and highlight next steps.

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The Biden Administration’s Cyber Plans for Critical Infrastructure: Focus on Pipelines, Rails, Aviation | CSIS Events

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Join CSIS for an event to highlight sectors where the Biden administration has utilized authorities to enact baseline cybersecurity requirements, discuss implementation, and highlight next steps.

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Meta's $1.3 Billion Fine Is a Strike Against Surveillance Capitalism

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Meta's $1.3 Billion Fine Is a Strike Against Surveillance Capitalism

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EUROPE’S GDPR has just dealt its biggest hammer blow yet. Almost exactly five years since the continent’s strict data rules came into force, Meta has been hit with a colossal €1.2 billion fine ($1.3 billion) for sending data about hundreds of millions of Europeans to the United States, where weaker privacy rules open it up to US snooping.

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Europe's GDPR has just dealt its biggest hammer blow yet. Almost exactly five years since the continent's strict data rules came into force, Meta has been hit with a colossal €1.2 billion fine ($1.3 billion) for sending data about hundreds of millions of Europeans to the United States, where weaker privacy rules open it up to US snooping.

Ireland's Data Protection Commission (DPC), the lead regulator for Meta in Europe, issued the fine after years of dispute about how data is transferred across the Atlantic. The decision says a complex legal mechanism, used by thousands of businesses for transferring data between the regions, was not lawful.

The fine is the biggest GDPR penalty ever issued, eclipsing Luxembourg's $833 million fine against Amazon. It brings the total amount of fines under the legislation to around €4 billion. However, it's small change for Meta, which made $28 billion in the first three months of this year.

In addition to the fine, the DPC's ruling gives Meta five months to stop sending data from Europe to the US and six months to stop handling data it previously collected, which could mean deleting photos, videos, and Facebook posts or moving them back to Europe. The decision is likely to bring into focus other GDPR powers, which can impact how companies handle data and arguably cut to the heart of Big Tech's surveillance capitalism.

Meta says it is "disappointed" by the decision and will appeal. The decision is also likely to heap extra pressure on US and European negotiators who are scrambling to finalize a long-awaited new data-sharing agreement between the two regions that will limit what information US intelligence agencies can get their hands on. A draft decision was agreed to at the end of 2022, with a potential deal being finalized later this year.

"The entire commercial and trade relationship between the EU and the US underpinned by data exchanges may be affected," says Gabriela Zanfir-Fortuna, vice president of global privacy at Future of Privacy Forum, a nonprofit think tank. "While this decision is addressed to Meta, it is about facts and situations that are identical for all American companies doing business in Europe offering online services, from payments, to cloud, to social media, to electronic communications, or software used in schools and public administrations."

'Bittersweet Decision'

The billion-euro fine against Meta has a long history. It stems back to 2013, long before GDPR was in place, when lawyer and privacy activist Max Schrems complained about US intelligence agencies' ability to access data following the Edward Snowden revelations about the National Security Agency (NSA). Twice since then, Europe's top courts have struck down US-EU data-sharing systems. The second of these rulings, in 2020, made the Privacy Shield agreement ineffective and also tightened rules around "standard contractual clauses (SSCs)."

The use of SCCs, a legal mechanism for transferring data, is at the center of the Meta case. In 2020, Schrems complained about Meta's use of them to send data to the US. Today's Irish decision, which is supported by other European regulators, found Meta's use of the legal tool "did not address the risks to the fundamental rights and freedoms of data subjects." In short, they were unlawful.

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Meta's $1.3 Billion Fine Is a Strike Against Surveillance Capitalism

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Europe's GDPR has just dealt its biggest hammer blow yet. Almost exactly five years since the continent's strict data rules came into force, Meta has been hit with a colossal €1.2 billion fine ($1.3 billion) for sending data about hundreds of millions of Europeans to the United States, where weaker privacy rules open it up to US snooping.

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Publication : La cybersécurité pour les TPE/PME en treize questions

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Publication : La cybersécurité pour les TPE/PME en treize questions

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L'ANSSI publie, en partenariat avec la direction générale des entreprises (DGE), la Confédération des petites et moyennes entreprises (CPME) et France Num, un nouveau guide destiné aux TPE et aux PME. Réalisée avec le soutien du dispositif Cybermalveillance.gouv.fr, cette publication propose des réponses accessibles à 13 questions essentielles pour la sécurité de ces entreprises.

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Leaked Government Document Shows Spain Wants to Ban End-to-End Encryption

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Leaked Government Document Shows Spain Wants to Ban End-to-End Encryption

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Spain has advocated banning encryption for hundreds of millions of people within the European Union, according to a leaked document obtained by WIRED that reveals strong support among EU member states for proposals to scan private messages for illegal content.

The document, a European Council survey of member countries’ views on encryption regulation, offered officials’ behind-the-scenes opinions on how to craft a highly controversial law to stop the spread of child sexual abuse material (CSAM) in Europe. The proposed law would require tech companies to scan their platforms, including users’ private messages, to find illegal material. However, the proposal from Ylva Johansson, the EU commissioner in charge of home affairs, has drawn ire from cryptographers, technologists, and privacy advocates for its potential impact on end-to-end encryption.

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Jakubowska, who reviewed the document, says that several countries appear to say they would give police access to people's encrypted messages and communications. Comments from Cyprus, for example, say it is "necessary" that law enforcement authorities have the ability to access encrypted communications to investigate online sexual abuse crimes and that the "impact of this regulation is significant because it will set a precedent for other sectors in the future." Similarly, officials in Hungary say "new methods of data interception and access are needed" to help law enforcement.

"Cyprus, Hungary, and Spain very clearly see this law as their opportunity to get inside encryption to undermine encrypted communications, and that to me is huge," Jakubowska says. "They are seeing this law as going far beyond what DG home is claiming that it's there for."

Officials in Belgium said in the document that they believe in the motto "security through encryption and despite encryption." When approached by WIRED, a spokesperson from Belgium's Ministry of Foreign Affairs initially shared a statement from the country's federal police saying its position has evolved since it submitted comments for the document and that Belgium is adopting a position, alongside other "like-minded states," that it wants encryption weakened. However, half an hour later, the spokesperson attempted to retract the statement, saying the country declined to comment.

Security experts have long said that any potential backdoors into encrypted communications or ways to decrypt services would undermine the overall security of the encryption. If law enforcement officials have a way to decipher messages, criminal hackers or those working on behalf of governments could exploit the same capabilities.

Despite the potential attack on encryption from some countries, many nations also appeared to strongly support end-to-end encryption and the protections it provides. Italy described the proposal for a new system as disproportionate. "It would represent a generalized control on all the encrypted correspondence sent through the web," the country's representatives said. Estonia cautioned that if the EU mandates the scanning of end-to-end encrypted messages, companies are likely to either redesign their systems so they can decrypt data or shut down in the EU. Triin Oppi, a spokesperson for Estonia's Ministry of Foreign Affairs, says the country's position had not changed.

Finland urged the EU Commission to provide more information about the technologies that can fight child sexual abuse without jeopardizing online security and warned that the proposal could conflict with the Finnish constitution.

Representatives from Germany-a country that has staunchly opposed the proposal-said the draft law needs to explicitly state that no technologies will be used that disrupt, circumvent, or modify encryption. "This means that the draft text must be revised before Germany can accept it," the country said. Member states need to agree on the text for the draft bill before the negotiations can move forward.

"The responses from countries such as Finland, Estonia, and Germany demonstrate a more comprehensive understanding of the stakes in the CSA regulation discussions," Stanford's Pfefferkorn says. "The regulation will not only affect criminal investigations for a specific set of offenses; it affects governments' own data security, national security, and the privacy and data protection rights of their citizens, as well as innovation and economic development."

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Lily Hay Newman Morgan Meaker Matt Burgess

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Leaked Government Document Shows Spain Wants to Ban End-to-End Encryption

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Jakubowska, who reviewed the document, says that several countries appear to say they would give police access to people's encrypted messages and communications. Comments from Cyprus, for example, say it is "necessary" that law enforcement authorities have the ability to access encrypted communications to investigate online sexual abuse crimes and that the "impact of this regulation is significant because it will set a precedent for other sectors in the future."

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Lors d’une discussion avec des observateurs avisés du secteur (directeur d’école d’ingénieur, patron de BU), deux chiffres ressortent : les besoins en experts cyber en France varient entre 4 000 et 16 000 postes à pourvoir selon les métriques. Et il sort bon an mal an 400 diplômés de l’ensemble des écoles sur le territoire. Ils ne vont pas tous dans la cybersécurité et ils ne restent pas tous en France. A ce rythme, il faudra entre 10 et 40 ans pour combler les besoins.

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Lors d'une discussion avec des observateurs avisés du secteur (directeur d'école d'ingénieur, patron de BU), deux chiffres ressortent : les besoins en experts cyber en France varient entre 4 000 et 16 000 postes à pourvoir selon les métriques. Et il sort bon an mal an 400 diplômés de l'ensemble des écoles sur le territoire. Ils ne vont pas tous dans la cybersécurité et ils ne restent pas tous en France. A ce rythme, il faudra entre 10 et 40 ans pour combler les besoins.

Bon nombre de facteurs expliquent, au moins en partie, ce déséquilibre entre la demande (de compétences humaines) et l'offre, mais peu résistent à une critique objective. Désaffection des étudiants pour les métiers techniques réputés difficiles. Mais alors comment expliquer la saturation des premières années de médecine, pas spécialement faciles ? Bas salaires, mais pas différents de pas mal de formations de niveau Master 2. Le fait que les hackers gagnent bien plus que les experts cyber en défense dans les entreprises ? Mais alors à ce compte les formations de comptabilité seraient désertées au profit d'une carrière de braqueur de banque ?

La cybersécurité va devoir travailler sur plusieurs axes et avant tout l'image des métiers. La question des colloques et salons étudiants est déjà adressée. Rendons à César, le visionnaire Michel Van Den Berghe (directeur du Campus Cyber) a émis l'idée d'une série TV, constatant que " Le Bureau des légendes " avait fait exploser les candidatures à la DGSE.

Autre idée, si l'école a pour mission de former les citoyens de demain, pourra-t-on longtemps affirmer que ces futurs citoyens auront passé autant d'heures sur les bancs de l'écoles, entre la maternelle et le baccalauréat, avec aussi peu de sensibilisation à la cybersécurité ? Sans même parler des formations post-bac dont très peu proposent dans leurs programmes une sensibilisation au sujet cyber, forcément variable en fonction du public : étudiants en médecine, BTS, etc.

Gros gisement potentiel de compétences également : les reconversions professionnelles. J'ai pu croiser, au cours de ma vie professionnelle, un agent hospitalier en charge du paramétrage de tous les routeurs et switch d'un CHU... Et dont le seul bagage était un CAP de chaudronnerie. Il y a beaucoup de très bons experts cyber qui s'ignorent et un diplôme du sérail n'est qu'une voie d'entrée possible.

Le culte du bac+5 va nécessairement devoir être remis en question. Quand des promotions entières d'étudiants d'école d'ingénieurs sont recrutées par des gros acteurs du privé qui les collent devant des écrans de SOC huit heures par jour à regarder des courbes et des alertes en couleur, faut-il s'étonner de la désaffection pour le métier ? On manque certes d'ingénieurs mais encore plus de techniciens supérieurs bien formés, bien encadrés et accompagnés dans leur évolution professionnelle. Comme disait un ancien PDG de General Electric, " le marché est plus grand que nos rêves ". Les possibilités d'évolutions professionnelles aussi.

Mais il est surtout dramatique de constater qu'environ la moitié de l'humanité est quasi absente de ce secteur pourtant passionnant : la moitié féminine s'entend. C'est d'abord un sujet car cela prive le secteur de recrutements potentiels. C'est surtout un sujet car, comme le dit le proverbe, si vous êtes un marteau alors vous voyez tous les problèmes comme des clous. Si vous ne mettez dans une pièce que des hommes, ils auront forcément un biais culturel d'analyse des problèmes, un biais de sélection des solutions et une quantité invraisemblable de zones non couvertes. D'où l'importance de mélanger tout le monde.

Certains métiers sont beaucoup plus féminisés, par exemple celui de qualiticien. Cela tombe bien, on a besoin de qualiticiens car les démarches de type ISO structurent la cyber. La cybersécurité est souvent dans l'urgence. Cela tombe bien, des catégories entières de professions médicales sont rompues à l'urgence (infirmières / iers, etc.).

La cybersécurité est souvent affaire de communication. Cela tombe bien, des promotions entières de communicants (es) ont des leçons à donner aux experts de la technique. La cyber est de plus en plus juridique. Cela tombe bien, les juristes font d'excellents candidats(es).

Force est de constater que, si en 2023, le marché flèche le sujet de la cybersécurité par la débauche de technologie, dans les faits c'est bien le sujet des hommes - et surtout des femmes - qui fera que l'on finira, ou pas, par sortir la tête de l'eau. Parce que les guerres se perdent d'abord par manque de combattant(e)s.

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Lors d'une discussion avec des observateurs avisés du secteur (directeur d'école d'ingénieur, patron de BU), deux chiffres ressortent : les besoins en experts cyber en France varient entre 4 000 et 16 000 postes à pourvoir selon les métriques. Et il sort bon an mal an 400 diplômés de l'ensemble des écoles sur le territoire.

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Digitaler Graben - Digitalisierung hängt viele Menschen ab

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Digitaler Graben - Digitalisierung hängt viele Menschen ab

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Die ältere Bevölkerung ist mittlerweile gut an die digitale Welt angeschlossen. Eine neue Studie stellt nun fest, dass sich vor allem zwischen Menschen mit tiefem Einkommen und wenig Bildung und Gebildeten und Bessergestellten ein digitaler Graben auftut.

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Die ältere Bevölkerung ist mittlerweile gut an die digitale Welt angeschlossen. Eine neue Studie stellt nun fest, dass sich vor allem zwischen Menschen mit tiefem Einkommen und wenig Bildung und Gebildeten und Bessergestellten ein digitaler Graben auftut.

Seniorinnen und Senioren werden digital immer fitter. Im Jahr 2009 surfte erst etwa ein Drittel der Altersgruppe über 65 durchs World Wide Web, wie damals das Zentrum für Gerontologie der Universität Zürich im Auftrag von Pro Senectute ermittelte. Zehn Jahre später waren es bereits drei Viertel. "Heute sind viele Seniorinnen und Senioren noch während ihres Erwerbslebens mit Computern in Kontakt gekommen. Zudem sind heute die Anwendungen viel einfacher und intuitiver geworden", sagt Peter Burri von Pro Senectute.

Nun rücken punkto Online-Anschluss andere Teile der Bevölkerung in den Fokus. Eine repräsentative Umfrage der Fachhochschule Nordwestschweiz zeigt, dass Ausbildung und Einkommen als Faktor für die digitale Fitness wichtiger werden. "Das heisst, die Technologie-Polarisierung wächst weiter. Als Gesellschaft laufen wir Gefahr, dass viele Gruppen von der Digitalisierung abgehängt werden", sagt Studienautor Marc Peter.

Überfordernde Geschwindigkeit

Diese Studie mit dem Titel "Digital-Radar Schweiz" wurde bereits einmal durchgeführt - und seither sei der gesellschaftliche Graben noch grösser geworden. "Es sind einerseits die vielen neuen Technologien, die fast monatlich auftauchen, neue Mobiltelefone, neue Webseiten, neue Applikationen. Es sind aber auch die Unternehmen, die mehr und mehr nur noch auf digitalen Kanälen operieren wollen. Und so müssen die Kunden für ihre Bank- und Versicherungsgeschäfte immer mehr digitale Apps nutzen", erläutert Peter diese Entwicklung.

In anderen Worten: Die Technologien verändern sich in einer Geschwindigkeit, dass selbst gut Ausgebildete und Gutsituierte Mühe bekunden, mit der Entwicklung Schritt zu halten.

"Wenn wir dieses Thema nicht aktiv angehen und unsere gesellschaftliche Verantwortung nicht wahrnehmen, droht unserem Land, dass wir auch wirtschaftlich an Wettbewerbsfähigkeit einbüssen, um in dieser digitalisierten Welt erfolgreich zu sein", befürchtet Marc Peter. Er verweist auf skandinavische und asiatische Länder, wo mehr unternommen werde, um die Gesellschaft im Umgang mit den digitalen Technologien à jour zu halten und sich der Chancen und Risiken bewusst zu werden.

Studienautor Marc Peter hofft, dass die Politik aktiv wird. "Wir müssen über diese Technologie-Polarisierung und dass verschiedene Gruppen in der Schweiz nicht über das notwendige Wissen verfügen, diskutieren. Es braucht nationale Initiativen, um dieses Technologiewissen zu vermitteln."

Tagesschau, 21.05.2023, 19:30 Uhr

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Digitaler Graben - Digitalisierung hängt viele Menschen ab

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Die ältere Bevölkerung ist mittlerweile gut an die digitale Welt angeschlossen. Eine neue Studie stellt nun fest, dass sich vor allem zwischen Menschen mit tiefem Einkommen und wenig Bildung und Gebildeten und Bessergestellten ein digitaler Graben auftut. Seniorinnen und Senioren werden digital immer fitter.

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Managing the New Era of Deterrence and Warfare: Visualizing the Information Domain

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Managing the New Era of Deterrence and Warfare: Visualizing the Information Domain

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This report is the capstone of a series that our two organizations led over the past year, which convened leaders from allied, partnered, and U.S. militaries, governments, academia, and industry to envision and shape future strategic advantages through visualizing information operations
This report is the capstone of a series that our two organizations led over the past year, which convened leaders from allied, partnered, and U.S. militaries, governments, academia, and industry to envision and shape future strategic advantages through visualizing information operations.

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We’ve been getting cyber wrong for years, new book claims

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We’ve been getting cyber wrong for years, new book claims

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China was last week accused of hacking into American critical infrastructure. The Five Eyes intelligence sharing alliance responded by urging companies to protect themselves. But increasingly simply raising defences no longer suffices in the domain of cyber competition.
If anything, the rules of engagement in cyberwars are proving fundamentally different to those of normal, physical wars.
Malware, one of the tools used for hacking, is simply computer code, which can be re-engineered and repurposed for positive or negative use. Network intrusions can be done for defensive reasons.
Now, a trio of researchers has proposed a new way to understand the real-world politics of hacking: they call it “cyber persistence theory”.
In “cyber persistence theory”, winners don’t dominate or coerce their enemies, as they would in the physical world of submarines, tanks and planes.

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We’ve been getting cyber wrong for years, new book claims

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In “cyber persistence theory”, winning hackers don’t dominate or coerce their enemies, as they would with military arms. They instead take the initiative and restructure the landscape.

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Will Artificial General Intelligence Change the Nature of War?

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Will Artificial General Intelligence Change the Nature of War?

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The idea of the immutability of the nature of war, as formulated by Clausewitz, is an article of faith that is constantly put to trial. The latest development in human history that can potentially change the nature of war is Artificial Intelligence (AI). In a recent article published in this magazine, Alloui-Cros argued that the nature of war will not change.[i] He based this conclusion on three points: AI is just a tool that compresses timeframes but is unable to make complex decisions, AI has human biases and is designed to solve human problems, and war is a human activity, and we will always have a choice to determine its course. Looking at the AIs that are currently available, he is probably correct and AI will not change what war is or break the trinity of passion, chance and policy that defines its nature. His conclusions are aligned with those of other scholars that discussed how military revolutions changed war. For example, Gray concluded that ‘some confused theorists would have us believe that war can change its nature’.[ii] Echevarria investigated the relation between RMA, globalisation, and the nature of war and concluded that, although it is changing, the Clausewitzian framework remains ‘more suitable for understanding the nature of war in today’s global environment than any of the alternatives’.

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Introduction

The idea of the immutability of the nature of war, as formulated by Clausewitz, is an article of faith that is constantly put to trial. The latest development in human history that can potentially change the nature of war is Artificial Intelligence (AI). In a recent article published in this magazine, Alloui-Cros argued that the nature of war will not change.[i] He based this conclusion on three points: AI is just a tool that compresses timeframes but is unable to make complex decisions, AI has human biases and is designed to solve human problems, and war is a human activity, and we will always have a choice to determine its course. Looking at the AIs that are currently available, he is probably correct and AI will not change what war is or break the trinity of passion, chance and policy that defines its nature. His conclusions are aligned with those of other scholars that discussed how military revolutions changed war. For example, Gray concluded that 'some confused theorists would have us believe that war can change its nature'.[ii] Echevarria investigated the relation between RMA, globalisation, and the nature of war and concluded that, although it is changing, the Clausewitzian framework remains 'more suitable for understanding the nature of war in today's global environment than any of the alternatives'.[iii]

On one hand, Alloui-Cros' article has merits because it recognized that Clausewitz's theory of war is still the point of reference for any discussion and updated to AI past conclusions on the effects of technological revolutions on the nature of war.

On the other hand, he did not consider if an AI with human-like capabilities, so-called Artificial General Intelligence (AGI), of whose capabilities far surpass human comprehension can falsify this theory. Vinge called this AI a 'singularity', a mathematical term used to label a point where a function degenerates and changes its nature becoming qualitatively different from what was before. Vinge concluded that 'it is a point where our models must be discarded and a new reality rules'.[iv] An AGI that far surpasses human capabilities is thus called a singularity because, once it appears, the past will not be a guide to forecast or understand the future. Some authors portrayed this possibility as the end of the world.[v] The implicit conclusion is that it is not worth studying what comes after because the AGI singularity will annihilate us. This position is disputable because if we have no way to know how this new reality will be, then it is impossible and equally useless to conclude that the singularity will destroy instead of saveing us. Furthermore, as Vinge argued in his seminal paper, as time passes, we should see the symptoms of the singularity advent.[vi] Hence it is worth studying how the nature of war will be altered by this new evolving reality. Alloui-Cros answered the question on AI and the nature of war for the reality we know. The purpose of this article is to add to this discussion by speculating what might happen to the nature of war when we approach the AGI singularity.

This essay is divided into three parts. Firstly, it will present the two conditions needed for an AGI to become a singularity: super-intelligence and consciousness. Secondly, it will try to answer if AI super-intelligence and consciousness could change Clausewitz's definition of war. Thirdly, once we establish that war is still organised violence for political aims, it will describe how AI super-intelligence and consciousness might influence Clausewitz's trinity of violence, chance, and politics. The conclusion is that the AI super-intelligence and consciousness have the potential to change the nature of war.

What is Artificial Intelligence?

AI researcher Micah Clark wrote that on 'a very personal and philosophical level, AI has been about building persons, is about "personhood"'.[vii] Current AIs are far from achieving personhood and can be better understood as highly optimised algorithms to solve narrow tasks but are poor at transferring these skills to new ones.[viii] Researchers are even in disagreement about whether a synthetic, conscious intelligence capable of performing humanly relevant complex cognitive tasks will ever emerge and eventually surpass human capabilities.[ix] Nonetheless, super-intelligence and consciousness are two steps that, if ever reached, could change war and its nature.

Super-intelligence

There is no consensus on the essence of human intelligence and even less so on super-intelligence.[x] It is still possible to adopt a working definition like the one proposed by Bostrom: 'any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest' is super-intelligent.[xi] This can materialise as comparable human intellect capability but multiple orders of magnitude faster, or vastly more intelligent, or a combination.[xii] Initially, it would be a 'seed' AI capable of building a slightly better version of itself through recursive self-improvement.[xiii] AI researchers think that with sufficient skill at intelligence amplification, the system could develop new cognitive modules as needed, including empathy, strategic thought and political acumen.[xiv]

Social psychologists, however, have recognized that the mind, as something associated with a single organism, is an approximation of intelligence. In reality, the mind is social, and it exists inside social and cultural systems.[xv] Artificial Life (ALife) research can give us insights into how machines can organise societies with rules for trade and fight and act as social intelligence. ALife envisions the possibility of a society of AI that leads to their superior intelligence.[xvi]

Consciousness

An AGI might develop consciousness as a tool to optimise its overall reward function and might have characteristics significantly different from that of humans.[xvii] Philosophers and researchers disagree on what consciousness is and whether self-consciousness is necessary or just a particular sort of phenomenal consciousness.[xviii] In particular, the lack of bodily experience and biological motivations would realise a clear cartesian dualism of body-mind that would question at its core the ability of AI to distinguish itself from the rest, care about itself and express intentionality.[xix]

The evolution of AI is not completely predictable, but we can expect increasing intelligence and some level of autonomy approaching consciousness to develop. We can explore its impact on war through these concepts.

Is it war?
Clausewitz's definition of war
The first question to answer is if war fought with and by AGIs is still war or a different type of interaction. In 'On war', Clausewitz introduces the concept (Begriff) of war as 'an act of violence (Gewalt) to force an opponent to fulfil our will'.[xx]

This definition comprises three elements: a) the violence, b) the purpose, and c) the social element.

1. For Clausewitz, the results of the application of violence are 'bloodsheds',[xxi] and the reciprocal element of war gives violence an escalatory quality without theoretical limits to its application.[xxii]

2. On the other hand, escalation is a potential outcome rather than a necessary one because the rational decisions of human beings should determine it.[xxiii] Military aims (Ziel) are thus constrained and judged in relation to the political purpose of the war (Zweck) and are only a component of the overall means (Mittel) available.[xxiv]

3. War is a relation between communities willing to resist and realise their political aims. It is a function of 'coalitionary aggression' and must happen between organised groups with a shared understanding of reality.[xxv]

a. Violence and AGIs
Handel highlights that for Clausewitz, victory without violence is an aberration in the history of warfare.[xxvi] In theory, it can be achieved by two methods, through manoeuvre,[xxvii] or as 'war by algebra', a clash resolved by comparing figures of each other's strengths.[xxviii] The Prussian general believed the first ineffective and the second impossible because of passion. By contrast, an AI commander might act as a perfectly rational entity and realise the 'war by algebra'. However, there are different combinations of this situation that are worth mentioning. If the AGI is under human control, the AGI evaluation might be overrun by a passionate human commander. Similarly, for the reciprocal nature of war, if the opponent is a human agent, the AGI might be forced to use violence to react to non-rational decisions. Conversely, if it faces another purely rational entity, or Huntington's Civil-Military relations concept remains valid, even when AGI is in charge of military operations, then an AGI commander might calculate that a battle or a war should not occur. Paradoxically, AGIs commanders might agree that the most efficient way to resolve a battle is to calculate the likely outcome and destroy their own resources based on this shared conclusion.[xxix] They would maintain valid the 'dominance of the destructive principle',[xxx] but would morph war and make explicit that it is an act of self-violence.
b. Purpose and AGIs
There must be a rational purpose for a conscious, and thus intentional, AGI to resort to war and violence or self-violence. If the AI does not have a freely chosen purpose and acts violently, if it goes 'rogue', then it is not war: it is an unnatural disaster. At the same time, it is unclear what a rational purpose would be for an AGI. Humans have biological motivations and emotions that connect these needs to our behaviours.[xxxi] It is unclear if an AI would have motivations or if some non-human motivations will emerge during their evolution. Minsky suggested that free will develops from a 'strong primitive defense mechanism' to resist or deny compulsion.[xxxii] If this is true, we can at least assume that a conscious AI will try to defend itself. Unfortunately, it does not clarify if an AGI will understand human motivations and how much value it will give to itself in relation to the rest of reality.
c. Social element and AGIs
An additional element to consider is that humans and AGIs might have different perceptions about what constitutes a violent act and its severity. Moreover, as humans, we might not be able to understand the thought processes of a super-intelligent being. This incomprehension of aims and means undermines the definition of war as a social institution: we do not wage wars on apes or cats, and similarly, AGIs will not have wars with us.[xxxiii] Interestingly, if AGIs develop their own society with norms and shared understandings, as ALife suggests, it means that they could potentially have AGI social wars waged for AGIs social motivations.

Overall, AGIs might not be interested in human wars unless they perceive them as threats. We will likely need a new word to identify these new social interactions. At the same time, war between humans with AGIs assistance is impossible to rule out, and it is thus essential to explore how its nature might change.

Does it change the nature of war?
What is the nature of war?
The nature of war is distilled into what Clausewitz called the 'wondrous trinity'.[xxxiv] Its elements are a) violence, hatred, and enmity, b) the play of chance and probability, and c) the element of subordination of war to policy and reason.

1. Clausewitz identified two types of hostility: hostile feelings or animosity and hostile intentions. Hostile intentions are essentially political in nature, necessary for war to occur and can exist without hostile feelings.[xxxv] The latter is variable in intensity, and war would be an algebraic exercise if absent.[xxxvi]

2. Clausewitz states that war is the realm of probabilities. The unfavourable cases are caused by friction: moral and physical depletion (danger and exertion), and lack of knowledge and bad luck (uncertainty and chance).[xxxvii] Estimating the impact of these factors is a matter of judgement and approximation because the extremely high number of cases makes it impossible to calculate mathematically.[xxxviii] Human, limited cognitive capabilities force the commander to make 'good enough' decisions.[xxxix]

3. Clausewitz is adamant that war has a rational component and it is not 'something autonomous but always [...] an instrument of policy'.[xl] It is the job of the statesman and the commander to establish 'the kind of war on which they are embarking; neither mistaking it for nor trying to turn it into something that is alien to its nature'.[xli] They should do this while not clouded by hostile feelings and after having correctly judged the probabilities.

a. Hostility and AGIs
Superficially, a perfectly rational entity would not be influenced by feelings like hostility. As discussed, it is not clear if even conscious AGIs would have a purpose other than self-defence. Nonetheless, we can imagine that an AGI might see itself as so precious that any human activity is perceived as hostile. AGIs might thus exist in a state of constant AI-fear, defined as a hyper-rational passion that is very different from our biologically driven fear, and develop both hostile feelings and intent. A 'dehumanised perception' may facilitate violence and brutality and even extermination with the awareness of what it is doing.[xlii]
b. Chance and AGIs
A super-intelligence explosion will eventually become asymptotic with perfect knowledge and calculus, effectively realising a so-called 'Laplace's Demon'.[xliii] In theory, this entity would suffer almost no friction: it would immediately adjust to events and be relentless in its effort. This is the perfect realisation of war by algebra, and it is a vision incompatible with the trinitarian war. In practice, perfect knowledge is impossible because of nonlinear dynamics: it is impossible to eliminate mismatches between the representation of phenomena and their actuality.[xliv] Nonetheless, an AGI would suffer no friction compared to humans.

As Allen argued, when under humans' control, our fiat would only be a constraint and a weakness, and the centre of gravity ( Schwerpunkt) will become the speed of action and the effect itself.[xlv] War with almost perfect knowledge would no longer be the realm of the military human genius and, as Van Creveld concluded, 'fighting does not make sense since it can neither serve as a test nor be experienced as fun'.[xlvi]
c. Policy and AGIs
The acceleration of almost frictionless military activities brings forward the issue of policy control over them. We assume that an aware and intentional AGI is always in control of its means and can mediate responses and escalations. The problem arises when humans can access the power of a super-intelligent but not-conscious AI. If you know that the enemy will relentlessly attack you, you must be ready to defend yourself relentlessly. This might just translate into a mindless acceleration of escalation and violence. The not-conscious AIs can be programmed to act within policy limits, but this still accounts for a diminished policy role after the conflict started.

Ultimately, investigating what could happen to the nature of war closer to AI super-intelligence and consciousness shows that there can be extreme cases where one or two elements of the trinity might collapse and become irrelevant. Unexpectedly, only passion might remain a constant element.

Conclusions

Alloui-Cros' article proved that even narrow AI will not change the validity of Clausewitz's theory. This article speculates that a super-intelligent and conscious AGI might. It appears that the interaction and conflict with and between super-intelligent conscious AGIs have the potential to be a novel social interaction with a Begriff different from that of purely 'human' wars. Following this logic, AGIs would not change the nature of war but an 'AGI-war' would have its own different nature. Nevertheless, 'human' war is unlikely to disappear, and the participation of an AGI nearing super-intelligence and consciousness has the potential to change its nature.

Brodie suggested that Khan's 'On Thermonuclear War' 'usefully supplements Clausewitz but [...] he does not in any way help to supplant him'.[xlvii] It is possible that, if an AGI emerges, and in anticipation of its super-intelligence and consciousness, we might need a further expansion of Clausewitz's theory, an 'On AGI-War'.

[i] Alloui-Cros, Baptiste. 'Does Artificial Intelligence Change the Nature of War?'. Military Strategy Magazine. 8 (3): 4-8.
[ii] Gray, Colin S. 2006. Another Bloody Century: Future Warfare. Paperback ed. A Phoenix Paperback. London: Phoenix. p. 23.
[iii] Echevarria, Antulio Joseph. 2003. 'Globalization and the Clausewitzian Nature of War'. The European Legacy 8 (3): 317-32. p. 322-26.
[iv] Vinge, Vernor. 1993. 'The coming technological singularity: How to survive in the post-human era'. Whole Earth Review. Winter 1993.
[v] Torres, Phil. 2016. The end: what science and religion tell us about the Apocalypse. Durham, North Carolina: Pitchstone Publishing. Chapter 5.
[vi] Vinge, 1993.
[vii] Micah Clark is a research scientist from the Florida Institute for Human & Machine Cognition cited in Scharre, Paul. 2018. Army of None: Autonomous Weapons and the Future of War. First edition. New York; London: W. W. Norton & Company. p. 234.
[viii] Payne, Kenneth. 2018. Strategy, Evolution, and War: From Apes to Artificial Intelligence. Washington, DC: Georgetown University Press. pp. 168-72.
[ix] Müller, Vincent C., and Nick Bostrom. 2016. 'Future Progress in Artificial Intelligence: A Survey of Expert Opinion'. In Fundamental Issues of Artificial Intelligence, edited by Vincent C. Müller, 376:555-72. Synthese Library. Cham: Springer International Publishing; McDermott, Drew. 2007. 'Artiﬁcial Intelligence and Consciousness'. In 7 The Cambridge Handbook of Consciousness, edited by Philip David Zelazo, Morris Moscovitch, and Evan Thompson, 117-50. Cambridge University Press.
[x] Wang, Pei. 2007. 'The Logic of Intelligence'. In Artificial General Intelligence. Edited by Goertzel, Ben, and Cassio Pennachin, 31-62. Cognitive Technologies. New York: Springer. p. 31.
[xi] Bostrom, Nick. 2014. Superintelligence: Paths, Dangers, Strategies. First edition. Oxford: Oxford University Press. p. 39.
[xii] Bostrom, 2014, chap. 3.
[xiii] Good, Irving John. 1966. 'Speculations Concerning the First Ultraintelligent Machine'. In Advances in Computers, 6:31-88. Elsevier.
[xiv] Bostrom, 2014, p. 114.
[xv] Woolgar, Steve. 1985. 'Why Not a Sociology of Machines? The Case of Sociology and Artificial Intelligence'. Sociology 19 (4): 557-72.
[xvi] Red'ko, Vladimir G. 2007. 'The Natural Way to Artificial Intelligence'. In Artificial General Intelligence. Edited by Goertzel, Ben, and Cassio Pennachin, 327-351. Cognitive Technologies. New York: Springer. pp. 327-51.
[xvii] Payne, Kenneth. 2018. Strategy, Evolution, and War: From Apes to Artificial Intelligence. Washington, DC: Georgetown University Press. pp. 204-5.
[xviii] McDermott, Drew. 2007. 'Artiﬁcial Intelligence and Consciousness'. In 7 The Cambridge Handbook of Consciousness., edited by Philip David Zelazo, Morris Moscovitch, and Evan Thompson, 117-50. Cambridge University Press.
[xix] Searle, John R. 1980. 'Minds, Brains, and Programs'. Behavioral and Brain Sciences 3 (3): 417-24; Perlis, Donald. 1997. 'Consciousness as Self-Function'. Journal of Consciousness Studies 4 (January): 509-25.
[xx] Clausewitz, Carl von, Michael Howard, and Peter Paret. 1976. On War. Princeton, N.J: Princeton University Press. p. 13.
[xxi] Clausewitz et al. 1976. pp. 13-14.
[xxii] Clausewitz, Howard, and Paret. 1976. pp. 13-15.
[xxiii] Echevarria. 2007. p. 66.
[xxiv] Howard, Michael. 2002. Clausewitz: A Very Short Introduction. Very Short Introductions 61. Oxford; New York: Oxford University Press. Chap. 3.
[xxv] Centeno, Miguel Angel, and Elaine Enriquez. 2016. War & Society. Political Sociology Series. Cambridge, UK; Malden, MA: Polity. p. 13.
[xxvi] Handel, Michael I. 2001. Masters of War: Classical Strategic Thought. 3rd rev. and Expanded ed. London; Portland, OR: F. Cass. p. 109.
[xxvii] Clausewitz, Howard, and Paret. 1976. p. 529.
[xxviii] Clausewitz, Howard, and Paret. 1976. p. 14.
[xxix] For a similar concept, watch Star Trek. 1967. Season 1, Episode 23, 'A Taste of Armageddon'. Aired February 23, 1967 on NBC.
[xxx] Clausewitz, Howard, and Paret. 1976. pp. 269-70.
[xxxi] Payne. 2021. p. 31.
[xxxii] Minsky, Marvin L. 1968. 'Matter, Minds, Models'. In Semantic Information Processing, edited by Marvin L. Minsky. MIT Press. pp. 425-32.
[xxxiii] Woolgar, Steve. 1985. 'Why Not a Sociology of Machines? The Case of Sociology and Artificial Intelligence'. Sociology 19 (4): 557-72. pp. 557-72.
[xxxiv] Clausewitz, Howard, and Paret. 1976. pp. 30-31.
[xxxv] Echevarria. 2007. p. 72.
[xxxvi] Clausewitz, Howard, and Paret. 1976. p. 14.
[xxxvii] Clausewitz, Howard, and Paret. 1976. pp. 48-69.
[xxxviii] Clausewitz, Howard, and Paret. 1976. p. 59.
[xxxix] Simon, H. A. 1956. 'Rational Choice and the Structure of the Environment.' Psychological Review 63 (2): 129-38.
[xl] Clausewitz, Howard, and Paret. 1976. p. 30.
[xli] Clausewitz, Howard, and Paret. 1976. p. 30.
[xlii] Centeno and Enriquez. 2016. pp. 18-19.
[xliii] Dale and Laplace. 1995. ch. 13, p. 4.
[xliv] Watts, Barry D. 2012. Clausewitzian Friction and Future War. Washington, D.C: Institute for National Strategic Studies, National Defense University. p. 73.
[xlv] Allen, John R., F. Ben Hodges, and Julian Lindley-French. 2021. Future War and the Defence of Europe. Oxford: Oxford University Press. p. 246.
[xlvi] Van Creveld, Martin. 1991. The Transformation of War. New York: Toronto: New York: Free Press; Collier Macmillan Canada; Maxwell Macmillan International. pp 172-73.
[xlvii] Brodie, Bernard. 1976. 'The Continuing Relevance of On War'. In On War, by Carl von Clausewitz, edited by Michael Eliot Howard and Peter Paret, 45-58. Princeton University Press.

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Will Artificial General Intelligence Change the Nature of War? - Military Strategy Magazine

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The idea of the immutability of the nature of war, as formulated by Clausewitz, is an article of faith that is constantly put to trial. The latest development in human history that can potentially change the nature of war is Artificial Intelligence (AI).

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The concept of Information Manoeuvre: Winning the Battle of Perceptions

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The concept of Information Manoeuvre: Winning the Battle of Perceptions

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Information has always been critical to the battlefield. Today, however, developments have greatly changed the information environment: such as globalization, digitalization, increased data volume and velocity, and decreased credibility of information. Combined with the disruptive effects of new information technology, this has resulted in an ever-growing importance of information during conflicts.
With the changing nature of the current (and future) operating environment, the Dutch army is now called upon to strengthen its information position and ways of handling information in order to cope with the major changes and challenges in the information environment. A new concept is therefore necessary, allowing them to make better use of information as enabler, means and weapon.
However, much debate is still going on about what exactly the concept of Information maneuver defines. What should be the effects and what does it mean when information is used as a weapon? The question arises how the concept of Information maneuver can be defined. What is the essence of the concept, and of which elements does it consist of? Subsequently, what does Information maneuver in a military context really mean when executing it?

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Information has always been critical to the battlefield. Today, however, developments have greatly changed the information environment: such as globalization, digitalization, increased data volume and velocity, and decreased credibility of information. Combined with the disruptive effects of new information technology, this has resulted in an ever-growing importance of information during conflicts.

With the changing nature of the current (and future) operating environment, the Dutch army is now called upon to strengthen its information position and ways of handling information in order to cope with the major changes and challenges in the information environment. A new concept is therefore necessary, allowing them to make better use of information as enabler, means and weapon.

However, much debate is still going on about what exactly the concept of Information maneuver defines. What should be the effects and what does it mean when information is used as a weapon? The question arises how the concept of Information maneuver can be defined. What is the essence of the concept, and of which elements does it consist of? Subsequently, what does Information maneuver in a military context really mean when executing it?

In this brief by Judith T. van de Kuijt, , Jacoline C. Slaager (TNO), many questions are addressed about Information Manoeuvre in the operating environment, leaving room for applied research to start investigating its characteristics and its span. In this paper, the authors explore four fundamental elements of Information Manoeuvre and identify three dilemmas concerning its scope and conceptual considerations.

The military application of information has a long history in influencing the outcome of war and conflict on the battlefield. Be it by deceiving the opponent, maintaining troop confidence, or shaping public opinion. These tactics are placed under the banner of influencing human behaviour. Behavioural influencing is the act of meaningfully trying to affect the behaviour of an individual by targeting people's knowledge, beliefs and emotions. Within the Dutch armed forces these tactics fall under title of Information Manoeuvre. With the ever-larger and more evasive employment of information-based capabilities to target human cognition, the boundaries of the physical and cognitive battlefield have begun to fade.

For this paper series scholars, experts and policymakers submitted their papers on the employment of information-related capabilities to influence human behaviour in the military context. From the perspective of an individual European or NATO country's perspective.

The Information-based behavioural influencing and Western practice paper series is edited by Arthur Laudrain, Laura Jasper and Michel Rademaker.

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The concept of Information Manoeuvre: Winning the Battle of Perceptions - HCSS

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Judith T. van de Kuijt, Naomi Keja, Jacoline C. Slaager (TNO) explore four fundamental elements of Information Manoeuvre and identify three dilemmas concerning its scope and conceptual considerations. What should be the effects and what does it mean when information is used as a weapon?

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Lessons from 'Star Trek: Picard' - a cybersecurity expert explains how a sci-fi series illuminates today's threats

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Lessons from 'Star Trek: Picard' - a cybersecurity expert explains how a sci-fi series illuminates today's threats

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Society’s understanding of technology and cybersecurity often is based on simple stereotypes and sensational portrayals in the entertainment media. I’ve written about how certain scenarios are entertaining but misleading. Think of black-clad teenage hackers prowling megacities challenging corporate villains. Or think of counterintelligence specialists repositioning a satellite from the back of a surveillance van via a phone call.
But sometimes Hollywood gets it right by depicting reality in ways that both entertain and educate. And that’s important, because whether it’s a large company, government or your personal information, we all share many of the same cybersecurity threats and vulnerabilities. As a former cybersecurity industry practitioner and current cybersecurity researcher, I believe the final season of “Star Trek: Picard” is the latest example of entertainment media providing useful lessons about cybersecurity and the nature of the modern world.

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Society's understanding of technology and cybersecurity often is based on simple stereotypes and sensational portrayals in the entertainment media. I've written about how certain scenarios are entertaining but misleading. Think of black-clad teenage hackers prowling megacities challenging corporate villains. Or think of counterintelligence specialists repositioning a satellite from the back of a surveillance van via a phone call.

But sometimes Hollywood gets it right by depicting reality in ways that both entertain and educate. And that's important, because whether it's a large company, government or your personal information, we all share many of the same cybersecurity threats and vulnerabilities. As a former cybersecurity industry practitioner and current cybersecurity researcher, I believe the final season of " Star Trek: Picard " is the latest example of entertainment media providing useful lessons about cybersecurity and the nature of the modern world.

So how does "Star Trek: Picard" relate to cybersecurity?

The nature of the threat

The show's protagonist is Jean-Luc Picard, a retired Starfleet admiral who commanded the starship Enterprise-D in a previous series. Starfleet is the military wing of the United Federation of Planets, of which Earth is a member. In Season 3, the final season, Picard's ultimate enemy, the Borg, returns to try conquering humanity again. The Borg is a cybernetic collective of half-human, half-machine "drones" led by a cyborg queen.

The Borg has partnered with other villains and worked for over a decade to deploy hidden agents able to compromise the DNA data contained in the software underpinning the transporter - a teleportation device used regularly by Starfleet personnel. Over many years, a certain subgroup of Starfleet personnel had their DNA altered by using the transporter.

Thus, in launching their final attack, the Borg is able to instantly activate thousands of "drones" to do its bidding in the form of altered, compromised Starfleet personnel. As Geordi La Forge, the Enterprise-D's engineer, notes, "They've been assimilating the entire fleet this whole time, without anyone ever knowing it."

The Borg's prolonged, stealthy infiltration of the federation is indicative of how today's most effective cyberattackers work. While it's relatively easy to detect when hackers attempt to breach a system from the outside, experts worry about the effects of an enemy infiltrating critical systems from within. Attackers can put malicious code in software during manufacturing or in software updates, both of which are avenues of attack that do not arouse suspicion until the compromised systems are activated or targeted.

This underscores the importance of ensuring the security and integrity of digital supply chains from product development at the vendor through product deployment at client sites to ensure no silent "drones," such as malware, are waiting to be activated by an adversary.

Equally important, "Star Trek: Picard" presents the very real and insidious nature of the insider threat faced by today's organizations. While not infected with a cybernetic virus, recently arrested Massachusetts Air National Guard airman Jack Teixeira shows the damage that can occur when a trusted employee has malicious intent or becomes co-opted and inflicts significant damage on an employer.

In some cases, these compromised or malicious individuals can remain undiscovered for years. And some global adversaries of the U.S., such as China and Russia, are known for taking a long-term perspective when it comes to planning and conducting espionage activities - or cyberattacks.

Humans remain the weakest link

"Synchronistic technology that allows every ship in Starfleet to operate as one. An impenetrable armada. Unity and defense. The ultimate safeguard."

With these words, humanity's military defenders activated a feature that linked every Starfleet vessel together under one unified automated command system. While intended to serve as an emergency capability, this system - called Fleet Formation - was quickly hijacked by the Borg as part of its attack on Earth. In essence, Starfleet created a Borg-like defense system that the Borg itself used to attack the federation.

Here, the most well-intentioned plans for security were thwarted by enemies who used humanity's own technologies against them. In the real world, capabilities such as on-demand real-time software updates, ChatGPT and centrally administered systems sound enticing and offer conveniences, cost savings or new capabilities. However, the lesson here is that organizations should not put them into widespread use without carefully considering as many of the potential risks or vulnerabilities as practical.

But even then, technology alone can't protect humans from ourselves - after all, it's people who develop, design, select, administer and use technology, which means human flaws are present in these systems, too. Such failings frequently lead to a stream of high-profile cybersecurity incidents.

Resiliency is not futile

To counter the Borg's final assault on Earth, Picard's crew borrows its old starship, Enterprise-D, from a fleet museum. The rationale is that its ship is the only major combat vessel not connected to the Borg collective via Starfleet's compromised Fleet Formation protocol and therefore is able to operate independently during the crisis. As La Forge notes, "Something older, analog. Offline from the others."

From a cybersecurity perspective, ensuring the availability of information resources is one of the industry's guiding principles. Here, the Enterprise-D represents defenders in response to a cyber incident using assets that are outside of an adversary's reach. Perhaps more important, the vessel symbolizes the need to think carefully before embracing a completely networked computing environment or relying on any single company or provider of services and connectivity for daily operations.

From natural disasters to cyberattack, what's your plan if your IT environment becomes corrupted or inaccessible? Can your organization stay operational and still provide necessary services? For critical public messaging, do governments and corporations have their own uncorruptible Enterprise-D capabilities to fall back on, such as the fediverse, the decentralized microblogging platform that is immune to the impulsive manipulations of Twitter's ownership?

Prepare for the unknown

The "Star Trek" universe explores the unknown in both the universe and contemporary society. How the crews deal with these experiences relies on their training, the appreciation of broad perspectives and ability to devise innovative solutions to the crisis of the week. Often, such solutions are derived from characters' interests in music, painting, archaeology, history, sports and other nontechnical areas of study, recreation or expertise.

Similarly, as modern digital defenders, to successfully confront our own cyber unknowns we need a broad appreciation of things beyond just cybersecurity and technology. It's one thing to understand at a technical level how a cyberattack occurs and how to respond. But it's another thing to understand the broader, perhaps more systemic, nuanced, organizational or international factors that may be causes or solutions, too.

Lessons from literature, history, psychology, philosophy, law, management and other nontechnical disciplines can inform how organizations plan for and respond to cybersecurity challenges of all types. Balancing solid technical knowledge with foundations in the liberal arts and humanities allows people to adapt comfortably to constantly evolving technologies and shifting threats.

Dystopic metaphors in fiction often reflect current social concerns, and the "Star Trek" universe is no different. Although rooted in a science fiction fantasy, "Star Trek: Picard" provides some accurate, practical and understandable cybersecurity reminders for today.

Season 3, in particular, offers viewers both entertainment and education - indeed, the best of both worlds.

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Lessons from 'Star Trek: Picard' - a cybersecurity expert explains how a sci-fi series illuminates today's threats

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Society's understanding of technology and cybersecurity often is based on simple stereotypes and sensational portrayals in the entertainment media. I've written about how certain scenarios are entertaining but misleading. Think of black-clad teenage hackers prowling megacities challenging corporate villains. Or think of counterintelligence specialists repositioning a satellite from the back of a surveillance van via a phone call.

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Cyber-Resilienz-Programme greifen laut Studie zu kurz

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Cyber-Resilienz-Programme greifen laut Studie zu kurz

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Immersive Labs, Unternehmen im Bereich der mitarbeiterzentrierten Cyber-Resilienz, stellt seine von Osterman Research durchgeführte Studie „2023 Cyber Workforce Resilience Trend Report“ vor. Die Studie zeigt, dass die stetige Zunahme von Cyberangriffen und die sich verändernde Bedrohungslandschaft dazu führen, dass immer mehr Unternehmen ihren Fokus auf den Aufbau nachhaltiger Cyber-Resilienz richten.

Viele dieser Programme greifen jedoch zu kurz und können die praktischen Cyber-Fähigkeiten der Teams nicht belegen. Im Rahmen der Studie wurden 570 Cybersicherheits- und Risikoverantwortliche in britischen, US-amerikanischen und deutschen Unternehmen mit mindestens 1.000 Mitarbeitenden befragt. Obwohl 86 Prozent der Unternehmen über ein Cyber-Resilienz-Programm verfügen, mangelt es mehr als der Hälfte der Befragten zufolge an einem ganzheitlichen Ansatz zur Beurteilung der Cyber-Resilienz.

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Immersive Labs, Unternehmen im Bereich der mitarbeiterzentrierten Cyber-Resilienz, stellt seine von Osterman Research durchgeführte Studie „2023 Cyber Workforce Resilience Trend Report" vor. Die Studie zeigt, dass die stetige Zunahme von Cyberangriffen und die sich verändernde Bedrohungslandschaft dazu führen, dass immer mehr Unternehmen ihren Fokus auf den Aufbau nachhaltiger Cyber-Resilienz richten.

Viele dieser Programme greifen jedoch zu kurz und können die praktischen Cyber-Fähigkeiten der Teams nicht belegen. Im Rahmen der Studie wurden 570 Cybersicherheits- und Risikoverantwortliche in britischen, US-amerikanischen und deutschen Unternehmen mit mindestens 1.000 Mitarbeitenden befragt. Obwohl 86 Prozent der Unternehmen über ein Cyber-Resilienz-Programm verfügen, mangelt es mehr als der Hälfte der Befragten zufolge an einem ganzheitlichen Ansatz zur Beurteilung der Cyber-Resilienz.

Die Stärkung der Cyber-Fähigkeiten steht im Jahr 2023 für viele Unternehmen ganz oben auf der Liste der strategischen Prioritäten. Widerstandsfähigkeit aufseiten von Cybersicherheitsteams (83 Prozent) und der allgemeinen Workforce (75 Prozent) aufzubauen, werden dabei als die beiden wichtigsten Schwerpunktbereiche genannt. Zwar haben Unternehmen Maßnahmen zur Implementierung von Cyber-Resilienz-Programmen ergriffen. Dennoch räumen 53 Prozent der Befragten ein, dass die Mitarbeitenden des Unternehmens nicht ausreichend gegen zukünftige Cyberangriffe - ganz gleich, welcher Art - gewappnet sind. Etwas mehr als die Hälfte der Befragten gibt an, dass es an einem ganzheitlichen Ansatz zur Bewertung der Cyber-Resilienz mangelt. Diese Zahlen deuten darauf hin, dass Cyber-Resilienz zwar eine Priorität ist und Programme vorhanden sind, die bestehenden Strukturen und Trainingsmethoden jedoch ineffektiv sind.

„In Anbetracht einer sich ständig verändernden Bedrohungslandschaft, in der Ransomware, Supply-Chain-Risiken und Schwachstellen Cybersicherheitsverantwortliche umtreiben, ist das Thema Cyber-Resilienz heute in aller Munde. Obwohl es vielversprechend ist, dass Unternehmen und Führungskräfte Cyber-Resilienz-Strategien und -Programme implementieren, verfehlen viele leider immer noch ihr Ziel", erklärt James Hadley, CEO und Gründer von Immersive Labs. „Trotz all der Präsenzschulungen und Zertifizierungen gibt die Hälfte der Befragten an, dass Mitarbeitende, Cybersicherheitsteams und das Unternehmen als Ganzes nicht ausreichend vorbereitet sind. Da wird schnell klar, dass aktuelle Programme umstrukturiert werden müssen, um eine erfolgreiche Cyber-Resilienz-Agenda voranzutreiben."

Die Studie kam zu weiteren aufschlussreichen Erkenntnissen, die den Bedarf an effektiveren - und modernisierten - Cyber-Resilienz-Programmen, die unternehmensweit angelegt und nicht auf Cybersicherheitsteams beschränkt sind, unterstreichen. Darunter:

Unternehmen bezweifeln, dass ihre Mitarbeitenden wissen, wie sie auf einen Cybersicherheitsvorfall reagieren sollen: Zwei von drei Unternehmen sind der Meinung, dass 95 Prozent ihrer Mitarbeitenden nicht wissen, wie sie sich bei der Aufarbeitung eines Cybersicherheitsvorfalls verhalten sollen. Den Geschäftsbetrieb ohne wichtige IT-Systeme aufrechtzuerhalten, zeitkritische Prozesse manuell abzuwickeln und es zu vermeiden, den Recovery-Prozess durch das Anschließen kompromittierter Geräte an das Netzwerk zu beeinträchtigen, zählt dabei zu den Schwerpunktaufgaben.

Unternehmen stellen die Verlässlichkeit von Branchenzertifizierungen, Präsenzschulungen und Ad-hoc-Lernpfaden beim Aufbau von Cyber-Resilienz infrage: Während fast alle Unternehmen Branchenzertifizierungen fördern, bezeichnen sie nur 32 Prozent als effektiv bei der Eindämmung von Cyberbedrohungen. Präsenzschulungen werden zu selten angeboten, um effektiv zu sein: Nur etwa ein Viertel (27 Prozent) der Befragten gibt an, dass sie monatlich an Schulungen teilnehmen. Fast die Hälfte der Befragten (46 Prozent) ist der Meinung, dass ihre Mitarbeitenden trotz jahrelangen Sicherheitsschulungen und Phishing-Tests nicht wüssten, wie sie mit einer Phishing-E-Mail umgehen sollen.

Den meisten Unternehmen fehlt ein dediziertes Framework mit Kennzahlen zur Messung und zum Nachweis der Cyber-Resilienz: Um die Cyber-Resilienz von Teams gegenüber Vorstand und C-Level Executives belastbar nachzuweisen, sind Kennzahlen entscheidend. Dennoch gibt fast die Hälfte (46 Prozent) der befragten Cybersicherheits- und Risikoverantwortlichen an, nicht über die erforderlichen Kennzahlen zu verfügen, um die Widerstandsfähigkeit ihrer Mitarbeitenden im Falle eines Cyberangriffs nachzuweisen. Nur etwa 6 Prozent der Unternehmen verfügen über aussagekräftige Kennzahlen, wie Response-Zeiten bei der Behebung von Schwachstellen, tracken Intrusion Rates, internen Datenverlust und die Häufigkeit verschiedener Bedrohungsarten.

Das Thema Cyber-Resilienz der Vorstands- und obersten Führungsebene gegenüber zu kommunizieren, ist unerlässlich, um Veränderungen anzustoßen: Über das letzte halbe Jahr gesehen, hat der Vorstand in weniger als der Hälfte (46 Prozent) der Unternehmen einen Nachweis der Cyber-Resilienz vom Cybersicherheitsteam verlangt; in 51 Prozent der Unternehmen wurde ein solcher von der obersten Führungsebene verlangt. Die Vorstands- und die oberste Führungsebene für die Bedeutung der Cyber-Resilienz zu sensibilisieren, ist ein wichtiger Schritt, wenn es darum geht, mehr Unterstützung zu erhalten. Cybersicherheits- und Risikoverantwortliche sollten das Thema Cyber-Resilienz in den Mittelpunkt der Kommunikation stellen, anstatt sich auf Einzelmaßnahmen, wie die Einführung neuer Cybersicherheitslösungen, zu konzentrieren.

„Traditionelle Ansätze, ohne kontinuierliches Training, sind angesichts immer raffinierterer Bedrohungen schlichtweg nicht mehr zweckmäßig", so Hadley weiter. „Unternehmen, die ihre Cyber-Resilienz-Agenda vorantreiben wollen, sollten sich darauf konzentrieren, Cyber-Fähigkeiten kontinuierlich zu beurteilen und zu verbessern und dies anhand belastbarer Daten zu belegen. Es braucht zeitgemäße Lösungen im Bereich Cybersicherheitstrainings und eine Workforce, die über das notwendige Know-how verfügt, um aktuellen und neu aufkommenden Bedrohungen in der Praxis souverän zu begegnen."

www.immersivelabs.com

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Cyber-Resilienz-Programme greifen laut Studie zu kurz - Onlineportal von IT Management

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Immersive Labs, Unternehmen im Bereich der mitarbeiterzentrierten Cyber-Resilienz, stellt seine von Osterman Research durchgeführte Studie „2023 Cyber Workforce Resilience Trend Report" vor. Die Studie zeigt, dass die stetige Zunahme von Cyberangriffen und die sich verändernde Bedrohungslandschaft dazu führen, dass immer mehr Unternehmen ihren Fokus auf den Aufbau nachhaltiger Cyber-Resilienz richten.

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UK and Norway team up to protect undersea cables, gas pipes in wake of Nord Stream attacks

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UK and Norway team up to protect undersea cables, gas pipes in wake of Nord Stream attacks

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The U.K. and Norway signed a security partnership to prevent attacks against undersea infrastructure including gas pipeline and cables.

Under the agreement, announced Thursday by the defense ministers of both countries, Britain and Norway are promising to exchange intelligence, counter mine threats and improve their ability to detect submarines from hostile nations.

U.K. Defense Secretary Ben Wallace said Thursday that Russia has “the intent and capability” to sabotage critical Western infrastructure, but he refused to blame Moscow for last year’s attacks on the Nord Stream gas pipelines in the Baltic Sea. Swedish investigators said last month that a state actor was most likely responsible for the blasts, but that the incident remained “difficult to investigate.”

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LONDON-The U.K. and Norway signed a security partnership to prevent attacks against undersea infrastructure including gas pipeline and cables.

Under the agreement, announced Thursday by the defense ministers of both countries, Britain and Norway are promising to exchange intelligence, counter mine threats and improve their ability to detect submarines from hostile nations.

U.K. Defense Secretary Ben Wallace said Thursday that Russia has "the intent and capability" to sabotage critical Western infrastructure, but he refused to blame Moscow for last year's attacks on the Nord Stream gas pipelines in the Baltic Sea. Swedish investigators said last month that a state actor was most likely responsible for the blasts, but that the incident remained "difficult to investigate."

"What we know is the Russians have a work program, they have a specific naval program designed to both look at and potentially sabotage or attack critical national infrastructure belonging to its adversaries," Wallace said at a joint press conference with his Norwegian counterpart Bjørn Arild Gram.

Russia "has a number of submarines and other pieces of equipment and spy ships and everything else specifically designed for that purpose," Wallace added.

Britain will send its first patrolling ship, the RFA Proteus, to the North Sea in July, with the goal of protecting wind farms, cables and gas pipelines in Norwegian and British waters, Wallace said.

Gram said the "sabotage of the Nord Stream pipelines last year is a concrete reminder of what is at stake."

Wallace also declined to say whether the U.K. has seen any evidence to support media reports South Africa has supplied weapons to Russia for use in its war in Ukraine. But he confirmed that the Ukrainian army has already used some of the long-range Storm Shadow missiles recently donated by Britain to Ukraine.

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UK and Norway team up to protect undersea cables, gas pipes in wake of Nord Stream attacks

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LONDON-The U.K. and Norway signed a security partnership to prevent attacks against undersea infrastructure including gas pipeline and cables. Under the agreement, announced Thursday by the defense ministers of both countries, Britain and Norway are promising to exchange intelligence, counter mine threats and improve their ability to detect submarines from hostile nations.

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Risiken durch "Hacktivisten" und Geheimdienste steigen

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Risiken durch "Hacktivisten" und Geheimdienste steigen

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Cyberattacken können mit einer einzigen E-Mail beginnen und die darin verborgene Malware ganze Abteilungen oder sogar komplette Konzerne lahmlegen. Eine aktuelle Studie zeigt auf, dass noch nie Führungskräfte in Deutschland das Risikodigitaler Angriffe auf ihr eigenes Unternehmen so hoch bewertet haben wie aktuell. Mehr als zwei von drei Befragte (68 Prozent) bewerten die Gefahr, Opfer einer Cyberattacke zu werden als "eher hoch" bis "sehr hoch" – letztere Kategorie macht fast ein Fünftel aller von EY befragten Führungskräfte (18 Prozent) aus.
Im Vergleich zur vorangegangenen Befragung im Jahr 2021 ist der Anteil derer, die die Gefährdung als "eher hoch" oder "sehr hoch" bezeichnen, um fünf Prozentpunkte gestiegen. Aktuell besonders alarmiert sind Unternehmen der Technologie-, Medien- und Telekommunikationsbranche (77 Prozent), der Pharma- und Gesundheitsindustrie sowie Automobilhersteller (beide 75 Prozent).

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Cyberattacken können mit einer einzigen E-Mail beginnen und die darin verborgene Malware ganze Abteilungen oder sogar komplette Konzerne lahmlegen. Eine aktuelle Studie zeigt auf, dass noch nie Führungskräfte in Deutschland das digitaler Angriffe auf ihr eigenes Unternehmen so hoch bewertet haben wie aktuell. Mehr als zwei von drei Befragte (68 Prozent) bewerten die Gefahr, Opfer einer Cyberattacke zu werden als "eher hoch" bis "sehr hoch" - letztere Kategorie macht fast ein Fünftel aller von EY befragten Führungskräfte (18 Prozent) aus.

Im Vergleich zur vorangegangenen Befragung im Jahr 2021 ist der Anteil derer, die die Gefährdung als "eher hoch" oder "sehr hoch" bezeichnen, um fünf Prozentpunkte gestiegen. Aktuell besonders alarmiert sind Unternehmen der Technologie-, Medien- und Telekommunikationsbranche (77 Prozent), der Pharma- und Gesundheitsindustrie sowie Automobilhersteller (beide 75 Prozent).

Die Frage, ob das , Opfer einer Cyberattacke zu werden, in den vergangenen zwei Jahren zugenommen hat, beantworten fast drei Viertel der Befragten (72 Prozent) mit "Ja". Kleiner wird das Problem nach Einschätzung der Befragten nicht werden, im Gegenteil: Alle befragten Führungskräfte gehen davon aus, dass die Zahl der Cyberattacken und die Bedeutung des Themas Datenklau - beziehungsweise dessen Vermeidung - steigen wird.

Die Prüfungs- und Beratungsgesellschaft EY hat Führungskräfte aus IT-Sicherheit und Datenschutz von mehr als 500 deutschen Unternehmen befragt.
Gefahr erkannt - Gefahr gebannt?
Trotz des offensichtlich vorhandenen Risikobewusstseins sagt jeder dritte Befragte (33 Prozent), dass das eigene Unternehmen nicht ausreichend vor digitalen Attacken geschützt ist. Im Vergleich zu den Vorjahren ist der Anteil stetig gestiegen, von 19 Prozent im Jahr 2019 auf 27 Prozent im Jahr 2021.

Fast jedes dritte Unternehmen (30 Prozent) hat zudem entweder keinen Krisenplan als Reaktion auf Hackattacken in der Schublade oder den mit dem Thema Cybersicherheit beauftragten Führungskräften ist ein solcher Plan nicht bekannt. Eine Versicherung gegen digitale Risiken wie Angriffe von Hackern hat weniger als die Hälfte der Unternehmen (46 Prozent).
Unternehmen fürchten am meisten das organisierte Verbrechen
Insbesondere das organisierte Verbrechen stellt aus Sicht der befragten Führungskräfte eine große Gefahr dar: Fast drei Viertel der Befragten (73 Prozent) geht von einem hohen durch mafiöse oder zumindest mafiaähnliche Strukturen und Organisationen oder auch Clankriminalität aus. Gegenüber den früheren Analysen ist der Anteil dieser Gruppen damit noch einmal gestiegen: Im Jahr 2019 gaben 50 Prozent diese Tätergruppe als Risikofaktor an, vor zwei Jahren waren es 68 Prozent.

Weitere Bedrohungsfaktoren sind aus Expertensicht darüber hinaus sogenannte "Hacktivisten" - wie beispielsweise das Hackerkollektiv "Anonymous". Fast jeder zweite Befragte (47 Prozent) sagt dies inzwischen. Auch ausländische Geheimdienste (36 Prozent) stellen aus Sicht der Führungskräfte ein deutlich größeres als noch vor zwei Jahren (30 Prozent) dar.
Abb. 01: Besonders gefürchtet: organisierte Kriminalität, Hackergruppen und ausländische Geheimdienste [Angaben in Prozent; Mehrfachnennungen möglich, Quelle: EY] Die primären Ziele: Über IT-Systeme an Finanz- und Rechnungswesen
Der Großteil der Befragten nennt vor allem zwei Weltregionen, wenn es um mögliche Angriffe auf die eigene IT-Infrastruktur geht: Russland und China. Das Gefährdungspotential Russlands ist dabei aus Sicht der IT-Verantwortlichen im Vergleich zur Erhebung vor zwei Jahren stark gestiegen - von 56 auf 74 Prozent. Die mögliche Bedrohungslage durch Angriffe aus China bewerten die IT-Verantwortlichen in den Unternehmen mit 59 Prozent genauso groß wie 2021. Sicherlich sind diese Antworten auch geprägt durch die aktuelle geopolitische Lage und die so auch manchmal subjektive Wahrnehmung der Bedrohung; ein Trend lässt sich aber dennoch anhand konkreter Zwischenfälle ablesen.
84% stellen keine gesteigerte Zahl an Cyberangriffen in Folge "Homeoffice" fest
Fragt man die mit IT-Sicherheit betrauten Führungskräfte, gibt nur ein kleiner Teil konkrete Cyberangriffe auf das eigene Unternehmen zu: 37 Prozent der Befragten gaben an, bereits mindestens einmal digital attackiert worden zu sein. Ziel der Angreifer ist am häufigsten das Finanz- und Rechnungswesen: 42 Prozent der mit dem Thema vertrauten Führungskräfte gaben an, dass hier konkrete kriminelle Handlungen stattfanden. Dahinter folgen Angriffe auf Vertrieb (37 Prozent) und das Management (32 Prozent). Am häufigsten nutzten die Kriminellen hierbei die IT-Systeme direkt (53 Prozent) oder störten diese (25 Prozent).

84 Prozent der befragten Unternehmen stellen durch die erhöhte Zahl von Homeoffice-Aktivitäten keine gesteigerte Zahl von Cyberangriffen fest. Dieses Ergebnisse steht diametral entgegengesetzt zu anderen Studien, beispielsweise einer Umfrage von SoSafe, einem Cyber-Security-Awareness-Unternehmen. Hier haben Anfang 2023 9 von 10 Befragten an, dass sich die Cyber-Bedrohungslage nach der Verlagerung Richtung Remote-Arbeit und Homeoffice verschlechtert hat. So haben Angestellte, die im Homeoffice arbeiten, fast dreimal so häufig (30 Prozent) auf -E-Mails geklickt, als Mitarbeiter, die im Büro tätig sind (12 Prozent). Die Analyse des SoSafe's Human Risk Review 2022 basiert auf Antworten der SoSafe Awareness-Platform. Dafür wurden über 4,3 Millionen simulierte -Angriffe von 1.500 Organisationen anonym ausgewertet und die Erfolgswahrscheinlichkeit verschiedener Angriffstaktiken analysiert. Die Gründe hierfür sind offensichtlich: Nämlich die Nutzung eigener Technik sowie ungesicherte Arbeitsumgebungen.
Studie zeigt hohe Relevanz eines wirksamen IKS Abb. 02: Hat sich die Anzahl an Angriffen gegen Ihr Unternehmen auf IT-Systeme und Daten seit der großflächigen Einführung von Homeoffice verändert? [Angaben in Prozent, Quelle: EY]
In der EY-Studie sagt hingegen nur jeder sechste Befragte, dass Attacken zugenommen haben. Besonders betroffen sind hierbei Unternehmen der Gesundheitsbranche und der chemischen Industrie. Auch bei Technologie und Medienunternehmen sowie im Sektor Handel und Konsumgüter ist der Anteil überdurchschnittlich hoch.
Abb. 03: Wie wurden die kriminellen Handlungen aufgedeckt? [Angaben in Prozent; Basis: Unternehmen, die bereits geschädigt wurden; Mehrfachnennungen möglich, Quelle: EY] Fast jedes zweite Unternehmen ist gegen digitale Risiken versichert
Die Studie belegt die hohe Relevanz eines wirksamen internen Kontrollsystems (IKS). In mehr als jedem zweiten registrierten Fall (56 Prozent) half ein IKS bei der Aufdeckung der Cyberattacke. Und auch durch interne Routineprüfungen (37 Prozent) wurden kriminelle Handlungen entdeckt. Beide Werte sind nahezu identisch mit den Werten aus dem Jahr 2021. Hinweise unternehmensinterner Personen nahmen dagegen deutlich ab und liegen noch bei 36 Prozent.

Trotz aller Kontrollmechanismen und staatlichen Aktivitäten wird allerdings rund jeder siebte Angriff rein zufällig aufgedeckt. So stellt sich in diesem Kontext die Frage nach der "großen Unbekannten" der unerkannten Cyberattacken.
Abb. 04: Hat Ihr Unternehmen eine Versicherung gegen digitale Risiken (= Hackerangriffe etc.) abgeschlossen? [Angaben in Prozent; Werte 2021 in Klammern, Quelle: EY]
Mehr als jede zweite durch das interne Kontrollsystem aufgedeckte kriminelle Handlung (58 Prozent) wurde durch einen Alarm im Security Operations Center (SOC) oder Security Information and Event Management (SIEM) erkannt. Gut jeder dritte Fall wurde durch sonstige Auffälligkeiten im Information Security Management System (35 Prozent) beziehungsweise durch eine Regelprüfung wie zum Beispiel im Rahmen einer Überprüfung der Clean Desk (34 Prozent) erkannt.

46 Prozent der Unternehmen haben nach eigenen Angaben inzwischen eine Versicherung gegen digitale Risiken abgeschlossen. 35 Prozent der befragten Unternehmen verfügen noch über keinen derartigen Versicherungsschutz. 19 Prozent der Führungskräfte machen zu diesem Sachverhalt keine Angaben.

Besonders hoch ist der Anteil der Unternehmen mit Versicherungsschutz im Gesundheitssektor, im Bereich Bau-/Immobilien-/Gastgewerbe sowie dem Finanzsektor. Der Anteil Unternehmen mit einer Cyber-Versicherung liegt hier jeweils über 50 Prozent.

31 Prozent der Unternehmen, die noch keine Cyber-Versicherung abgeschlossen haben, planen den Abschluss einer solchen. Vor zwei Jahren waren es noch 20 Prozent der Unternehmen. Etwas weniger als die Hälfte der Befragten plant keine Absicherung. Besonders hoch ist der Anteil der Unternehmen, die den Abschluss einer Cyber-Versicherung planen, mit rund 50 Prozent im Bereich Transport und Logistik.

​​​​​​​ Abb. 05: Unternehmen, die (noch) keine Versicherung gegen digitale Risiken abgeschlossen haben: Planen Sie den Abschluss einer Cyberversicherung? [Angaben in Prozent; Grundgesamtheit: Unternehmen, die (noch) keine Versicherung gegen digitale Risiken abgeschlossen haben, Quelle: EY]

[ Bildquelle Titelbild: RiskNET [generiert mit Midjourney ] ]

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Risiken durch "Hacktivisten" und Geheimdienste steigt

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Cyberattacken können mit einer einzigen E-Mail beginnen und die darin verborgene Malware ganze Abteilungen oder sogar komplette Konzerne lahmlegen. Eine aktuelle Studie zeigt auf, dass noch nie Führungskräfte in Deutschland das digitaler Angriffe auf ihr eigenes Unternehmen so hoch bewertet haben wie aktuell.

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What every CEO should know about generative AI

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What every CEO should know about generative AI

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Generative AI is evolving at record speed while CEOs are still learning the technology’s business value and risks. Here, we offer some of the generative AI essentials.

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Amid the excitement surrounding generative AI since the release of ChatGPT, Bard, Claude, Midjourney, and other content-creating tools, CEOs are understandably wondering: Is this tech hype, or a game-changing opportunity? And if it is the latter, what is the value to my business?

The public-facing version of ChatGPT reached 100 million users in just two months. It democratized AI in a manner not previously seen while becoming by far the fastest-growing app ever. Its out-of-the-box accessibility makes generative AI different from all AI that came before it. Users don't need a degree in machine learning to interact with or derive value from it; nearly anyone who can ask questions can use it. And, as with other breakthrough technologies such as the personal computer or iPhone, one generative AI platform can give rise to many applications for audiences of any age or education level and in any location with internet access.

All of this is possible because generative AI chatbots are powered by foundation models, which contain expansive neural networks trained on vast quantities of unstructured, unlabeled data in a variety of formats, such as text and audio. Foundation models can be used for a wide range of tasks. In contrast, previous generations of AI models were often "narrow," meaning they could perform just one task, such as predicting customer churn. One foundation model, for example, can create an executive summary for a 20,000-word technical report on quantum computing, draft a go-to-market strategy for a tree-trimming business, and provide five different recipes for the ten ingredients in someone's refrigerator. The downside to such versatility is that, for now, generative AI can sometimes provide less accurate results, placing renewed attention on AI risk management.

With proper guardrails in place, generative AI can not only unlock novel use cases for businesses but also speed up, scale, or otherwise improve existing ones. Imagine a customer sales call, for example. A specially trained AI model could suggest upselling opportunities to a salesperson, but until now those were usually based only on static customer data obtained before the start of the call, such as demographics and purchasing patterns. A generative AI tool might suggest upselling opportunities to the salesperson in real time based on the actual content of the conversation, drawing from internal customer data, external market trends, and social media influencer data. At the same time, generative AI could offer a first draft of a sales pitch for the salesperson to adapt and personalize.

The preceding example demonstrates the implications of the technology on one job role. But nearly every knowledge worker can likely benefit from teaming up with generative AI. In fact, while generative AI may eventually be used to automate some tasks, much of its value could derive from how software vendors embed the technology into everyday tools (for example, email or word-processing software) used by knowledge workers. Such upgraded tools could substantially increase productivity.

CEOs want to know if they should act now-and, if so, how to start. Some may see an opportunity to leapfrog the competition by reimagining how humans get work done with generative AI applications at their side. Others may want to exercise caution, experimenting with a few use cases and learning more before making any large investments. Companies will also have to assess whether they have the necessary technical expertise, technology and data architecture, operating model, and risk management processes that some of the more transformative implementations of generative AI will require.

The goal of this article is to help CEOs and their teams reflect on the value creation case for generative AI and how to start their journey. First, we offer a generative AI primer to help executives better understand the fast-evolving state of AI and the technical options available. The next section looks at how companies can participate in generative AI through four example cases targeted toward improving organizational effectiveness. These cases reflect what we are seeing among early adopters and shed light on the array of options across the technology, cost, and operating model requirements. Finally, we address the CEO's vital role in positioning an organization for success with generative AI.

Excitement around generative AI is palpable, and C-suite executives rightfully want to move ahead with thoughtful and intentional speed. We hope this article offers business leaders a balanced introduction into the promising world of generative AI.

Generative AI technology is advancing quickly (Exhibit 1). The release cycle, number of start-ups, and rapid integration into existing software applications are remarkable. In this section, we will discuss the breadth of generative AI applications and provide a brief explanation of the technology, including how it differs from traditional AI.

More than a chatbot

Generative AI can be used to automate, augment, and accelerate work. For the purposes of this article, we focus on ways generative AI can enhance work rather than on how it can replace the role of humans.

While text-generating chatbots such as ChatGPT have been receiving outsize attention, generative AI can enable capabilities across a broad range of content, including images, video, audio, and computer code. And it can perform several functions in organizations, including classifying, editing, summarizing, answering questions, and drafting new content. Each of these actions has the potential to create value by changing how work gets done at the activity level across business functions and workflows. Following are some examples.

Classify

A fraud-detection analyst can input transaction descriptions and customer documents into a generative AI tool and ask it to identify fraudulent transactions.

A customer-care manager can use generative AI to categorize audio files of customer calls based on caller satisfaction levels.

Edit

A copywriter can use generative AI to correct grammar and convert an article to match a client's brand voice.

A graphic designer can remove an outdated logo from an image.

Summarize

A production assistant can create a highlight video based on hours of event footage.

A business analyst can create a Venn diagram that summarizes key points from an executive's presentation.

Answer questions

Employees of a manufacturing company can ask a generative AI-based "virtual expert" technical questions about operating procedures.

A consumer can ask a chatbot questions about how to assemble a new piece of furniture.

Draft

A software developer can prompt generative AI to create entire lines of code or suggest ways to complete partial lines of existing code.

A marketing manager can use generative AI to draft various versions of campaign messaging.

As the technology evolves and matures, these kinds of generative AI can be increasingly integrated into enterprise workflows to automate tasks and directly perform specific actions (for example, automatically sending summary notes at the end of meetings). We already see tools emerging in this area.

How generative AI differs from other kinds of AI

As the name suggests, the primary way in which generative AI differs from previous forms of AI or analytics is that it can generate new content efficiently, often in "unstructured" forms (for example, written text or images) that aren't naturally represented in tables with rows and columns (see sidebar "Glossary" for a list of terms associated with generative AI).

The underlying model that enables generative AI to work is called a foundation model. Transformers are key components of foundation models-GPT actually stands for generative pre-trained transformer. A transformer is a type of artificial neural network that is trained using deep learning, a term that alludes to the many (deep) layers within neural networks. Deep learning has powered many of the recent advances in AI.

However, some characteristics set foundation models apart from previous generations of deep learning models. To start, they can be trained on extremely large and varied sets of unstructured data. For example, a type of foundation model called a large language model can be trained on vast amounts of text that is publicly available on the internet and covers many different topics. While other deep learning models can operate on sizable amounts of unstructured data, they are usually trained on a more specific data set. For example, a model might be trained on a specific set of images to enable it to recognize certain objects in photographs.

In fact, other deep learning models often can perform only one such task. They can, for example, either classify objects in a photo or perform another function such as making a prediction. In contrast, one foundation model can perform both of these functions and generate content as well. Foundation models amass these capabilities by learning patterns and relationships from the broad training data they ingest, which, for example, enables them to predict the next word in a sentence. That's how ChatGPT can answer questions about varied topics and how DALL·E 2 and Stable Diffusion can produce images based on a description.

Given the versatility of a foundation model, companies can use the same one to implement multiple business use cases, something rarely achieved using earlier deep learning models. A foundation model that has incorporated information about a company's products could potentially be used both for answering customers' questions and for supporting engineers in developing updated versions of the products. As a result, companies can stand up applications and realize their benefits much faster.

However, because of the way current foundation models work, they aren't naturally suited to all applications. For example, large language models can be prone to "hallucination," or answering questions with plausible but untrue assertions (see sidebar "Using generative AI responsibly"). Additionally, the underlying reasoning or sources for a response are not always provided. This means companies should be careful of integrating generative AI without human oversight in applications where errors can cause harm or where explainability is needed. Generative AI is also currently unsuited for directly analyzing large amounts of tabular data or solving advanced numerical-optimization problems. Researchers are working hard to address these limitations.

The emerging generative AI ecosystem

While foundation models serve as the "brain" of generative AI, an entire value chain is emerging to support the training and use of this technology (Exhibit 2). Specialized hardware provides the extensive compute power needed to train the models. Cloud platforms offer the ability to tap this hardware. MLOps and model hub providers offer the tools, technologies, and practices an organization needs to adapt a foundation model and deploy it within its end-user applications. Many companies are entering the market to offer applications built on top of foundation models that enable them to perform a specific task, such as helping a company's customers with service issues.

The first foundation models required high levels of investment to develop, given the substantial computational resources required to train them and the human effort required to refine them. As a result, they were developed primarily by a few tech giants, start-ups backed by significant investment, and some open-source research collectives (for example, BigScience). However, work is under way on both smaller models that can deliver effective results for some tasks and training that's more efficient. This could eventually open the market to more entrants. Some start-ups have already succeeded in developing their own models-for example, Cohere, Anthropic, and AI21 Labs build and train their own large language models.

CEOs should consider exploration of generative AI a must, not a maybe. Generative AI can create value in a wide range of use cases. The economics and technical requirements to start are not prohibitive, while the downside of inaction could be quickly falling behind competitors. Each CEO should work with the executive team to reflect on where and how to play. Some CEOs may decide that generative AI presents a transformative opportunity for their companies, offering a chance to reimagine everything from research and development to marketing and sales to customer operations. Others may choose to start small and scale later. Once the decision is made, there are technical pathways that AI experts can follow to execute the strategy, depending on the use case.

Much of the use (although not necessarily all of the value) from generative AI in an organization will come from workers employing features embedded in the software they already have. Email systems will provide an option to write the first drafts of messages. Productivity applications will create the first draft of a presentation based on a description. Financial software will generate a prose description of the notable features in a financial report. Customer-relationship-management systems will suggest ways to interact with customers. These features could accelerate the productivity of every knowledge worker.

But generative AI can also be more transformative in certain use cases. Following, we look at four examples of how companies in different industries are using generative AI today to reshape how work is done within their organization. The examples range from those requiring minimal resources to resource-intensive undertakings. (For a quick comparison of these examples and more technical detail, see Exhibit 3.)

Lessons CEOs can take away from these examples

The use cases outlined here offer powerful takeaways for CEOs as they embark on the generative AI journey:

Transformative use cases that offer practical benefits for jobs and the workplace already exist. Companies across sectors, from pharmaceuticals to banking to retail, are standing up a range of use cases to capture value creation potential. Organizations can start small or large, depending on their aspiration.

Costs of pursuing generative AI vary widely, depending on the use case and the data required for software, cloud infrastructure, technical expertise, and risk mitigation. Companies must take into account risk issues, regardless of use case, and some will require more resources than others.

While there is merit to getting started fast, building a basic business case first will help companies better navigate their generative AI journeys.

The CEO has a crucial role to play in catalyzing a company's focus on generative AI. In this closing section, we discuss strategies that CEOs will want to keep in mind as they begin their journey. Many of them echo the responses of senior executives to previous waves of new technology. However, generative AI presents its own challenges, including managing a technology moving at a speed not seen in previous technology transitions.

Organizing for generative AI

Many organizations began exploring the possibilities for traditional AI through siloed experiments. Generative AI requires a more deliberate and coordinated approach given its unique risk considerations and the ability of foundation models to underpin multiple use cases across an organization. For example, a model fine-tuned using proprietary material to reflect the enterprise's brand identity could be deployed across several use cases (for example, generating personalized marketing campaigns and product descriptions) and business functions, such as product development and marketing.

To that end, we recommend convening a cross-functional group of the company's leaders (for example, representing data science, engineering, legal, cybersecurity, marketing, design, and other business functions). Such a group can not only help identify and prioritize the highest-value use cases but also enable coordinated and safe implementation across the organization.

Reimagining end-to-end domains versus focusing on use cases

Generative AI is a powerful tool that can transform how organizations operate, with particular impact in certain business domains within the value chain (for example, marketing for a retailer or operations for a manufacturer). The ease of deploying generative AI can tempt organizations to apply it to sporadic use cases across the business. It is important to have a perspective on the family of use cases by domain that will have the most transformative potential across business functions. Organizations are reimagining the target state enabled by generative AI working in sync with other traditional AI applications, along with new ways of working that may not have been possible before.

Enabling a fully loaded technology stack

A modern data and tech stack is key to nearly any successful approach to generative AI. CEOs should look to their chief technology officers to determine whether the company has the required technical capabilities in terms of computing resources, data systems, tools, and access to models (open source via model hubs or commercial via APIs).

For example, the lifeblood of generative AI is fluid access to data honed for a specific business context or problem. Companies that have not yet found ways to effectively harmonize and provide ready access to their data will be unable to fine-tune generative AI to unlock more of its potentially transformative uses. Equally important is to design a scalable data architecture that includes data governance and security procedures. Depending on the use case, the existing computing and tooling infrastructure (which can be sourced via a cloud provider or set up in-house) might also need upgrading. A clear data and infrastructure strategy anchored on the business value and competitive advantage derived from generative AI will be critical.

Building a 'lighthouse'

CEOs will want to avoid getting stuck in the planning stages. New models and applications are being developed and released rapidly. GPT-4, for example, was released in March 2023, following the release of ChatGPT (GPT-3.5) in November 2022 and GPT-3 in 2020. In the world of business, time is of the essence, and the fast-paced nature of generative AI technology demands that companies move quickly to take advantage of it. There are a few ways executives can keep moving at a steady clip.

Although generative AI is still in the early days, it's important to showcase internally how it can affect a company's operating model, perhaps through a "lighthouse approach." For example, one way forward is building a "virtual expert" that enables frontline workers to tap proprietary sources of knowledge and offer the most relevant content to customers. This has the potential to increase productivity, create enthusiasm, and enable an organization to test generative AI internally before scaling to customer-facing applications.

As with other waves of technical innovation, there will be proof-of-concept fatigue and many examples of companies stuck in "pilot purgatory." But encouraging a proof of concept is still the best way to quickly test and refine a valuable business case before scaling to adjacent use cases. By focusing on early wins that deliver meaningful results, companies can build momentum and then scale out and up, leveraging the multipurpose nature of generative AI. This approach could enable companies to promote broader AI adoption and create the culture of innovation that is essential to maintaining a competitive edge. As outlined above, the cross-functional leadership team will want to make sure such proofs of concept are deliberate and coordinated.

Balancing risk and value creation

As our four detailed use cases demonstrate, business leaders must balance value creation opportunities with the risks involved in generative AI. According to our recent Global AI Survey, most organizations don't mitigate most of the risks associated with traditional AI, even though more than half of organizations have already adopted the technology. Generative AI brings renewed attention to many of these same risks, such as the potential to perpetuate bias hidden in training data, while presenting new ones, such as its propensity to hallucinate.

As a result, the cross-functional leadership team will want to not only establish overarching ethical principles and guidelines for generative AI use but also develop a thorough understanding of the risks presented by each potential use case. It will be important to look for initial use cases that both align with the organization's overall risk tolerance and have structures in place to mitigate consequential risk. For example, a retail organization might prioritize a use case that has slightly lower value but also lower risk-such as creating initial drafts of marketing content and other tasks that keep a human in the loop. At the same time, the company might set aside a higher-value, high-risk use case such as a tool that automatically drafts and sends hyperpersonalized marketing emails. Such risk-forward practices can enable organizations to establish the controls necessary to properly manage generative AI and maintain compliance.

CEOs and their teams will also want to stay current with the latest developments in generative AI regulation, including rules related to consumer data protection and intellectual property rights, to protect the company from liability issues. Countries may take varying approaches to regulation, as they often already do with AI and data. Organizations may need to adapt their working approach to calibrate process management, culture, and talent management in a way that ensures they can handle the rapidly evolving regulatory environment and risks of generative AI at scale.

Applying an ecosystem approach to partnerships

Business leaders should focus on building and maintaining a balanced set of alliances. A company's acquisitions and alliances strategy should continue to concentrate on building an ecosystem of partners tuned to different contexts and addressing what generative AI requires at all levels of the tech stack, while being careful to prevent vendor lock-in.

Partnering with the right companies can help accelerate execution. Organizations do not have to build out all applications or foundation models themselves. Instead, they can partner with generative AI vendors and experts to move more quickly. For instance, they can team up with model providers to customize models for a specific sector, or partner with infrastructure providers that offer support capabilities such as scalable cloud computing.

Companies can use the expertise of others and move quickly to take advantage of the latest generative AI technology. But generative AI models are just the tip of the spear: multiple additional elements are required for value creation.

Focusing on required talent and skills

To effectively apply generative AI for business value, companies need to build their technical capabilities and upskill their current workforce. This requires a concerted effort by leadership to identify the required capabilities based on the company's prioritized use cases, which will likely extend beyond technical roles to include a talent mix across engineering, data, design, risk, product, and other business functions.

As demonstrated in the use cases highlighted above, technical and talent needs vary widely depending on the nature of a given implementation-from using off-the-shelf solutions to building a foundation model from scratch. For example, to build a generative model, a company may need PhD-level machine learning experts; on the other hand, to develop generative AI tools using existing models and SaaS offerings, a data engineer and a software engineer may be sufficient to lead the effort.

In addition to hiring the right talent, companies will want to train and educate their existing workforces. Prompt-based conversational user interfaces can make generative AI applications easy to use. But users still need to optimize their prompts, understand the technology's limitations, and know where and when they can acceptably integrate the application into their workflows. Leadership should provide clear guidelines on the use of generative AI tools and offer ongoing education and training to keep employees apprised of their risks. Fostering a culture of self-driven research and experimentation can also encourage employees to innovate processes and products that effectively incorporate these tools.

Businesses have been pursuing AI ambitions for years, and many have realized new revenue streams, product improvements, and operational efficiencies. Much of the successes in these areas have stemmed from AI technologies that remain the best tool for a particular job, and businesses should continue scaling such efforts. However, generative AI represents another promising leap forward and a world of new possibilities. While the technology's operational and risk scaffolding is still being built, business leaders know they should embark on the generative AI journey. But where and how should they start? The answer will vary from company to company as well as within an organization. Some will start big; others may undertake smaller experiments. The best approach will depend on a company's aspiration and risk appetite. Whatever the ambition, the key is to get under way and learn by doing.

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What every CEO should know about generative AI

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Gen AI is evolving at record speed while CEOs are still learning the technology's business value and risks. Here, we offer some of the generative AI essentials.

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Studie: Auch Rechenzentren leiden am Fachkräftemangel

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Studie: Auch Rechenzentren leiden am Fachkräftemangel

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Im letzten Jahr erlebten drei Viertel der befragten Firmen einen RZ-Ausfall. Aber auch der Mangel an IT-Spezialisten beschäftigte die Führungskräfte in den RZs.

Drei Viertel der Firmen im deutschsprachigen Raum (Schweiz, Deutschland und Österreich) hatte in den letzten 12 Monaten mindestens einen Ausfall oder eine Störung in ihrem Rechenzentrum. Das zeigt eine Studie zu den "Herausforderungen und Strategien im Rechenzentrum" des Schweizer IT-Dienstleisters Technogroup.

Als häufigste Ursachen für Ausfälle nannte fast die Hälfte der betroffenen Firmen defekte Hardware (42%). Aber auch Cyberattacken waren Gründe für RZ-Aussetzer (21%). "Für Unternehmen, ihre Produktion und ihre Services sind stabile Rechenzentren essenziell. Blickt man aber auf neuere und wachsende Herausforderungen wie die Verfügbarkeit von Hardware und Fachkräften, wird deutlich, dass Unternehmen ihre Technologie und ihr Know-how auf unterschiedliche Szenarien vorbereiten sollten", meint Arnd Krämer, Geschäftsführer von Technogroup.

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Is ChatGPT Already Obsolete? Exploring the Future of AI in the Workplace

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Is ChatGPT Already Obsolete? Exploring the Future of AI in the Workplace

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In the ever-evolving field of Artificial Intelligence (AI), there are ongoing debates about the relevance and effectiveness of ChatGPT. While some sources claim that ChatGPT is already outdated and being replaced by more advanced AI technologies, others argue that it remains a valuable tool that is transforming certain job roles. This article aims to provide insights into the current state of ChatGPT and its potential obsolescence in the face of AI advancements. We will also explore the broader impact of AI on the future of work.

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In the ever-evolving field of Artificial Intelligence (AI), there are ongoing debates about the relevance and effectiveness of ChatGPT. While some sources claim that ChatGPT is already outdated and being replaced by more advanced AI technologies, others argue that it remains a valuable tool that is transforming certain job roles. This article aims to provide insights into the current state of ChatGPT and its potential obsolescence in the face of AI advancements. We will also explore the broader impact of AI on the future of work.

Is ChatGPT Already Outdated?

ChatGPT: A Brief Overview

ChatGPT is an AI-powered chatbot that utilizes natural language processing to generate human-like responses to text-based prompts. It was introduced only six months ago but has quickly gained attention for its ability to engage in conversational interactions.

See More: ChatGPT 4 Login Page: Your Gateway to Conversational AI

Advancements in AI Technology

Some experts claim that ChatGPT is becoming obsolete due to the rapid advancements in AI technology. For instance, Google's Bard chatbot and OpenAI's GPT-4 are examples of more advanced AI products that can describe images and understand different media beyond written language. These advancements push the boundaries of AI capabilities, potentially surpassing ChatGPT in terms of functionality and performance.

Concerns about ChatGPT's Limitations

One of the concerns surrounding ChatGPT is its applicability in certain domains. It has been banned in some schools due to concerns about its potential to complete coursework and replace teachers. While it may excel in generating responses, ChatGPT's limitations in terms of subject matter expertise and accuracy raise questions about its utility in educational settings.

Transforming Jobs through Automation

Despite concerns about obsolescence, ChatGPT is seen as a transformative tool for certain job roles. It has the potential to automate tasks in fields like writing and teaching, making them more efficient. By handling routine tasks, ChatGPT allows professionals to focus on complex, creative, and rewarding aspects of their work.

Room for Improvement

While ChatGPT has shown promising results, some experts argue that it still has bugs and inaccuracies in terms of knowledge. However, they believe that with more extensive training data and improvements in the underlying technology, these limitations can be addressed, enhancing ChatGPT's performance and value.

GPT-4: A Glimpse into the Future

Looking ahead, GPT-4, a more advanced version of the technology behind ChatGPT, is on the horizon. GPT-4 can power chatbots and be applied to various purposes beyond text-based prompts. This indicates that AI technology will continue to evolve, potentially rendering ChatGPT obsolete in the future.

Check Also: Chat GPT Login Free: Sign Up, Login, Features, Security & FAQs

The Impact of AI on the Future of Work

While the discussion around ChatGPT's obsolescence continues, it is important to consider the broader impact of AI on the future of work. AI is undeniably transforming the job market, with predictions that it will replace millions of jobs globally while also creating new roles. Here are some key insights into this paradigm shift:

Job Market Disruption

The World Economic Forum's "The Future of Jobs Report 2020" projects that AI will replace 85 million jobs worldwide by 2025. However, it is important to note that AI may also create around 97 million new roles. This disruption in the job market reflects the profound changes brought about by AI technology.

Redefining Job Roles

As AI automates routine and repetitive tasks, workers can shift their focus to more complex, creative, and rewarding work. AI's ability to handle mundane responsibilities opens up opportunities for individuals to engage in critical thinking, problem-solving, and innovation. It can augment human capabilities and support professionals in their decision-making processes.

Upskilling and Adaptability

To thrive in the AI-driven workplace, individuals will need to embrace continuous learning and upskilling. The demand for skills such as data analysis, programming, and AI expertise will rise significantly. Organizations and educational institutions play a crucial role in providing training and development programs that equip individuals with the necessary skills to succeed in the evolving job market.

Ethical Considerations

The integration of AI in the workplace also raises ethical considerations. It is essential to ensure transparency, fairness, and accountability in AI systems. As AI becomes more prevalent, it is crucial to establish guidelines and regulations that mitigate potential biases, protect privacy, and maintain human oversight in decision-making processes.

Conclusion

While ChatGPT faces challenges in terms of advancements in AI technology and concerns about its limitations, it is not entirely obsolete. ChatGPT still holds value in transforming certain job roles and automating routine tasks. However, the rapid evolution of AI, with models like GPT-4 on the horizon, indicates that ChatGPT may eventually be surpassed by more advanced AI technologies. As AI continues to shape the future of work, it is important for individuals and organizations to adapt, upskill, and navigate the ethical considerations associated with this transformative technology.

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Is ChatGPT Already Obsolete? Exploring the Future of AI in the Workplace

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In the ever-evolving field of Artificial Intelligence (AI), there are ongoing debates about the relevance and effectiveness of ChatGPT. While some sources claim that ChatGPT is already outdated and being replaced by more advanced AI technologies, others argue that it remains a valuable tool that is transforming certain job roles.

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Machines of mind: The case for an AI-powered productivity boom

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Machines of mind: The case for an AI-powered productivity boom

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Large language models such as ChatGPT are emerging as powerful tools that not only make workers more productive but also increase the rate of innovation, laying the foundation for a significant acceleration in economic growth. As a general purpose technology, AI will impact a wide array of industries, prompting investments in new skills, transforming business processes, and altering the nature of work. However, official statistics will only partially capture the boost in productivity because the output of knowledge workers is difficult to measure. The rapid advances can have great benefits but may also lead to significant risks, so it is crucial to ensure that we steer progress in a direction that benefits all of society.

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Large language models such as ChatGPT are emerging as powerful tools that not only make workers more productive but also increase the rate of innovation, laying the foundation for a significant acceleration in economic growth. As a general purpose technology, AI will impact a wide array of industries, prompting investments in new skills, transforming business processes, and altering the nature of work. However, official statistics will only partially capture the boost in productivity because the output of knowledge workers is difficult to measure. The rapid advances can have great benefits but may also lead to significant risks, so it is crucial to ensure that we steer progress in a direction that benefits all of society.
On a recent Friday morning, one of us sat down in his favorite coffee shop to work on a new research paper regarding how AI will affect the labor market. To begin, he pulled up ChatGPT, a generative AI tool. After entering a few plain-English prompts, the system was able to provide a suitable economic model, draft code to run the model, and produce potential titles for the work. By the end of the morning, he had achieved a week's worth of progress on his research.

We expect millions of knowledge workers, ranging from doctors and lawyers to managers and salespeople to experience similar ground-breaking shifts in their productivity within a few years, if not sooner.

The potential of the most recent generation of AI systems is illustrated vividly by the viral uptake of ChatGPT, a large language model (LLM) that captured public attention by its ability to generate coherent and contextually appropriate text. This is not an innovation that is languishing in the basement. Its capabilities have already captivated hundreds of millions of users.

Other LLMs that were recently rolled out publicly include Google's Bard and Anthropic's Claude. But generative AI is not limited to text: in recent years, we have also seen generative AI systems that can create images, such as Midjourney, Stable Diffusion or DALL-E, and more recently multi-modal systems that combine text, images, video, audio and even robotic functions. These technologies are foundation models, which are vast systems based on deep neural networks that have been trained on massive amounts of data and can then be adapted to perform a wide range of different tasks. Because information and knowledge work dominates the US economy, these machines of the mind will dramatically boost overall productivity.

The power of productivity growth

The primary determinant of our long-term prosperity and welfare is the rate of productivity growth: the amount of output created per hour worked. This holds even though changes in productivity are not immediately felt by everyone and, in the short run, workers' perceptions of the economy are dominated by the business cycle. From World War II until the early 1970s, labor productivity grew at over 3% a year, more than doubling over the period, ushering in an era of prosperity for most Americans. In the early 1970s productivity growth slowed dramatically, rebounding in the 1990s, only to slow again since the early 2000s.

Figure 1: The Components of labor productivity growth 1948 to 2022. Contribution of total factor productivity. Contributions of capital intensity and labor force composition.

Figure 1 illustrates the story. It decomposes the overall growth in labor productivity into two components: total factor productivity (which is a measure of the impact of technology) and the contribution of the labor composition and capital intensity. The figure illustrates that the key driver of changes in labor productivity is changes total factor productivity (TFP). There are many reasons for America's recent economic struggles, but slow TFP growth is a key cause, slowly eating away at the country's prosperity, making it harder to fight inflation, eroding workers' wages and worsening budget deficits.

The generally slow pace of economic growth, together with the outsized profits of tech companies, has resulted in skepticism about the benefits of digital technologies for the broad economy. However, for about 10 years starting in the 1990s there was a surge in productivity growth, as shown in Figure 1, driven primarily by a huge wave of investment in computers and communications, which in turn drove business transformations. Even though there was a stock market bubble as well as significant reallocation of labor and resources, workers were generally better off. Furthermore, the federal budget was balanced from 1998 to 2001 -a double win. Digital technology can drive broad economic growth, and it happened less than thirty years ago.

Early estimates of AI's productivity effects

The recent advances in generative AI have been driven by progress in software, hardware, data collection, and growing amounts of investment in cutting-edge models. Sevilla et al. (2022) observe that the amount of compute (computing power) used to train cutting-edge AI systems has been doubling every six months over the past decade. The capabilities of generative AI systems have grown in tandem, allowing them to perform many tasks that used to be reserved for cognitive workers, such as writing well-crafted sentences, creating computer code, summarizing articles, brainstorming ideas, organizing plans, translating other languages, writing complex emails, and much more.

Generative AI has broad applications that will impact a wide range of workers, occupations, and activities. Unlike most advances in automation in the past, it is a machine of the mind affecting cognitive work. As noted in a recent research paper (Eloundou et al., 2023), LLMs could affect 80% of the US workforce in some form.

There is an emerging literature that estimates the productivity effects of AI on specific occupations or tasks. Kalliamvakou (2022) finds that software engineers can code up to twice as fast using a tool called Codex, based on the previous version of the large language model GPT-3. That's a transformative effect. Noy and Zhang (2023) find that many writing tasks can also be completed twice as fast and Korinek (2023) estimates, based on 25 use cases for language models, that economists can be 10-20% more productive using large language models.

But can these gains in specific tasks translate into significant gains in a real-world setting? The answer appears to be yes. Brynjolfsson, Li, and Raymond (2023) show that call center operators became 14% more productive when they used the technology, with the gains of over 30% for the least experienced workers. What's more, customer sentiment was higher when interacting with operators using generative AI as an aid, and perhaps as a result, employee attrition was lower. The system appears to create value by capturing and conveying some of the tacit organizational knowledge about how to solve problems and please customers that previously was learned only via on-the-job experience.

Criticism of large language models as merely "stochastic parrots" is misplaced. Most cognitive work involves drawing on past knowledge and experience and applying it to the problem at hand. It is true that generative AI programs are prone to certain types of mistakes, but the form of these mistakes is predictable. For example, language models tend to engage in "hallucinations," i.e., to make up facts and references. As a result, they clearly require human oversight. However, their economic value depends not on whether they are flawless, but on whether they can be used productively. By that criterion, they are already poised to have a massive impact. Moreover, the accuracy of generative AI models continues to improve rapidly.

Quantifying the productivity effects

A recent report by Goldman Sachs suggests that generative AI could raise global GDP by 7%, a truly significant effect for any single technology. Based on our analysis of a variety of use cases and the share of the workforce doing mainly cognitive work, this estimate strikes us as being reasonable, though there remains great uncertainty about the ultimate productivity and growth effects of AI.

It is useful to rigorously break down the channels through which we expect generative AI to produce growth in productivity, output, and ultimately in social welfare in a model.

The first channel is the increased efficiency of output production. By making cognitive workers engaged in production more efficient, the level of output increases. Economic theory tells us that, in competitive markets, the effect of a productivity boost in a given sector on aggregate productivity and output is equal to the size of the productivity boost multiplied by the size of the sector ( Hulten's theorem). For instance, if generative AI makes cognitive workers on average 30% more productive over a decade or two and cognitive work makes up about 60% of all value added in the economy (as measured by the wage bill attributable to cognitive tasks), this amounts to a 18% increase in aggregate productivity and output, spread out over those years.

The second, and ultimately more important, channel is the acceleration of innovation and thus future productivity growth. Cognitive workers not only produce current output but also invent new things, engage in discoveries, and generate the technological progress that boosts future productivity. This includes R&D-what scientists do-and perhaps more importantly, the process of rolling out new innovations into production activities throughout the economy-what managers do. If cognitive workers are more efficient, they will accelerate technological progress and thereby boost the rate of productivity growth-in perpetuity. For example, if productivity growth was 2% and the cognitive labor that underpins productivity growth is 20% more productive, this would raise the growth rate of productivity by 20% to 2.4%. In a given year, such a change is barely noticeable and is usually swamped by cyclical fluctuations.

But productivity growth compounds. After a decade, the described tiny increase in productivity growth would leave the economy 5% larger, and the growth would compound further every year thereafter. What's more, if the acceleration applied to the growth rate of the growth rate (for instance if one of the applications of AI was to improving AI itself), then of course, growth would accelerate even more over time.
Figure 2: Possible growth trajectories. Source: Authors' simulations.
Figure 2 schematically illustrates the effects of the two channels of productivity growth over a twenty year horizon. The baseline follows the current projection of the Congressional Budget Office (CBO) of 1.5% productivity growth, giving rise to a total of 33% productivity growth over 20 years. The projection labeled "Level" assumes that generative AI raises the level of productivity and output by an additional 18% over ten years, as suggested by the illustrative numbers we discussed for the first channel. After ten years, growth reverts to the baseline rate. The third projection labeled "Level+Growth" additionally includes a one percentage point boost in the rate of growth over the baseline rate, resulting from the additional innovation triggered by generative AI. At first, the resulting growth trajectory is barely distinguishable from the "Level" projection, but through the power of compounding, the effects grow bigger over time, leading to a near doubling of output after 20 years, far greater than the baseline projection.

Barriers and drivers of adoption

For the productivity gains to materialize, advances in AI have to disseminate throughout the economy. Traditionally, this has always taken time, so we would not expect potential productivity gains to show up immediately. The advances need to be taken up and rolled out by businesses and organizations that employ cognitive labor throughout the economy, including small and medium-sized businesses, some of which may be slow to realize the potential of adapting advanced new technologies or may lack the required skills to use them well. For example, the Goldman report assumes it takes 10 years for the gains to fully materialize.

The "productivity J-curve" (Brynjolfsson et al., 2021) describes how new technologies, especially general purpose technologies, deliver productivity gains only after a period of investment in complementary intangible goods, such as business processes and new skills. In fact, this can temporarily even drag down measured productivity. As a result, earlier general purpose technologies like electricity and the first wave of computers took decades to have a significant effect on productivity. Additional barriers to adoption and rollout include concerns about job losses and institutional inertia and regulation, in areas from the medicine to finance and law.

However, in the case of generative AI there are also factors that can mitigate these barriers, or even accelerate adoption. First, in contrast to physical automation, one benefit of cognitive automation is that it can often be rolled out quickly via software. This is particularly true now that a ubiquitous digital infrastructure is available: the Internet. ChatGPT famously was the most rapid product launch in history-it gained 100 million users in just two months -because it was accessible to anyone with an internet connection and did not require any hardware investment on the users' side.

Both Microsoft and Google are in the process of rolling out Generative AI tools as part of their search engines and office suites, offering access to generative AI to a large fraction of the cognitive workforce in advanced countries who regularly use these tools. Furthermore, application programming interfaces (APIs) are increasingly available to enable seamless modularization and connectivity between systems, and a marketplace for plug-ins and extensions is rapidly growing, making it much easier to add functionality. Finally, in contrast to other technologies, users of generative AI can interact with the technology in natural language rather than special codes or commands, making it easier to learn and adopt these tools.

These reasons for optimism suggest that the rollout of these new technologies may be faster than in the past. Still, the importance of training to make optimal use of these tools cannot be overstated.

Problems of measurement - silent productivity growth

The most common measure of productivity, non-farm business productivity, is quite adept at capturing increases in productivity in the industrial sector where inputs and outputs are tangible and easy to account for. However, productivity of cognitive labor is harder to measure. Statisticians who compile GDP and productivity statistics sometimes resort to valuing the output of cognitive activity simply by assuming it is proportional to the quantity of labor input being used to produce it, which of course eliminates any scope for productivity growth.

For example, generative AI enables economists to write more thought pieces and provide deeper analyses of the economy than before, yet this output would not directly show up in GDP statistics. Readers may feel that they have access to better and deeper economic analyses (contributing to channel 1 above). Moreover, the analyses may also play a part in enabling business leaders and policymakers to better harness the positive productivity effects of generative AI (contributing to channel 2 above). Neither of these positive productivity effects of such work would be directly captured in official GDP or productivity statistics, yet the benefits of economists' productivity gains would still lead to greater social welfare.

The same holds true for many other cognitive workers throughout the economy. This may give rise to significant under-measurement or "silent productivity growth."

Productivity growth, labor markets, and income distribution

A bigger pie does not automatically mean everyone benefits evenly, or at all. The productivity effects of generative AI are likely to go hand in hand with significant disruption in the job market as many workers may see downward wage pressures. For example, the Eloundou et al. paper cited earlier predicts that up to 49% of the workforce could eventually have half or more of their job tasks performed by AI. Will the demand for these tasks increase enough to compensate for such efficiency gains? Will the workers find other tasks to do? The answers are far from certain. In past technological transformations, workers who lost their jobs could transition to new jobs, and on average pay increased. However, given the scale of the impending disruption and the labor-saving nature of it, it remains to be seen whether this will be the case in the age of generative AI.

Moreover, the current wave of cognitive automation marks a change from most earlier waves of automation, which focused on physical jobs or routine cognitive tasks. Now, creative and unstructured cognitive jobs are also being impacted. Instead of the lowest paid workers bearing the brunt of the disruption, now many of the highest-paying occupations will be affected. These workers may find the disruption to be quite unexpected. If their skills are general, they may find it easier to adjust to displacement than blue-collar workers. However, if they have acquired a significant amount of human capital that becomes obsolete, they may experience much larger income losses than blue-collar workers who were displaced by previous rounds of automation.

The idea of jobs created versus jobs displaced is the most tangible manifestation of job market disruption for lay people. Job losses are indeed a significant social concern, and we need policies to facilitate adjustment. However, as economists, we note that the key factor in determining the influence of new technologies on the labor market is ultimately their effect on labor demand. Counting how many jobs are created versus how many are destroyed misses that employment is determined as the equilibrium of labor demand and labor supply. Labor supply is quite inelastic, reflecting that most working-age people want to or have to work independently of whether their incomes go up or down. Workers who lose their jobs as a result of changing technology will seek alternative employment. And, to the extent that changing technology raises productivity, this will increase national income and spur the demand for labor. Over the long run, the labor market can be expected to equilibrate, meaning that the supply of jobs, the demand for jobs and the level of wages will adjust to maintain full employment. This is evidenced by the fact that the unemployment rate in the United States has remained consistently low in the postwar period (with help from monetary and fiscal policy to recover from recessions). Job destruction has always been offset by job creation. Instead, the effects of automation and augmentation tend to be reflected in wages and income.

The effect of generative AI on labor demand depends on whether the systems complement or substitute for labor. Substitution occurs when AI models automate most or all tasks of certain jobs, while complementing occurs if they automate small parts of certain jobs, leaving humans indispensable. Additionally, AI systems can be complementary to human labor if they enable new tasks or increase quality.

As companies invest more in generative AI, they often have choices about whether to emphasize substitution or complementarity . For example, if call centers can use AI to complement human operators, or, as AI improves, they may restructure their processes to have the systems address more and more queries without human operators being involved. At the same time, higher productivity growth across the economy may make the overall effects more complementary by increasing overall labor demand and may mitigate the disruption.

In recent decades, there have been three main forces impacting income distribution. First, there has been an overall shift of income away from wages and towards corporate capital. Second, there has been an increase in the return to the skills that are valued by companies (reflected in part by higher returns to education). Third, there has been a shift caused by increased foreign competition.

It is hard to predict how generative AI will impact this mix. A positive interpretation is that workers who currently struggle with aspects of math and writing will become more productive with the help of these new tools and will be able to take better-paid jobs with the help of the new technology. A negative interpretation is that companies will use the technology to eliminate or de-skill more and more positions pushing a larger fraction of the workforce into unfulfilling jobs, raising the share of profits in income and, perhaps, increasing the demand for the most elite members of the workforce.

No doubt technological progress will not stop with the current wave of generative AI. Instead, we can expect even more dramatic advances in AI, bringing the technology closer to what is called artificial general intelligence (AGI). This will lead to even more radical transformations of life and work. The scarcity of human labor has been a double-edged sword throughout our history: on the one hand, it has held back economic growth because greater production would require more labor; on the other hand, it has been highly beneficial for income distribution since wages represent the market value of scarce labor. If labor can be replaced by machines across a wide range of tasks in the future, both points may no longer hold, and we may experience an AI-powered growth take-off at the same time as that the value of labor declines. This would present a significant challenge for our society. Moreover, AGI may also impose large risks on humanity if not aligned with human objectives.

Conclusion

Large language models and other forms of generative AI are still at an early stage, making it difficult to predict with great confidence the exact productivity effects they will have. Yet as we have argued, we expect that generative AI will have tremendous positive productivity effects, both by increasing the level of productivity and accelerating future productivity growth.

For policymakers, the goal should be to allow for the positive productivity gains while mitigating the risks and downsides of ever-more powerful AI. Faster productivity growth is an elixir that can solve or mitigate many of our society's challenges, from raising living standards and addressing poverty to providing healthcare for all and strengthening our defenses. Indeed, it will be nearly impossible to fix some of our budgetary challenges, including the growing deficits, without sufficiently stronger growth.

AI-powered productivity growth will also create challenges. There may be a need for updating social programs and tax policy to soften the welfare costs of labor market disruptions and ensure that the benefits of AI give rise to shared prosperity rather than concentration of wealth. Other harms will also need to be addressed, including the amplification of misinformation and polarization, potentially destabilizing our democracy, and the creation of new biological and other weapons that could injure or kill untold numbers of people.

Therefore, we cannot let the capabilities of AI outstrip our understanding of their potential impacts. Economists and other social scientists will need to accelerate their work on AI's impacts to keep up with our colleagues in AI research who are rapidly advancing the technologies. If we do that, we are optimistic our society can harness the productivity benefits and growth acceleration delivered by artificial intelligence to substantially advance human welfare in the coming years.
The authors used GPT4 for writing assistance in producing this text but assume full responsibility for its content and accuracy. The Brookings Institution is financed through the support of a diverse array of foundations, corporations, governments, individuals, as well as an endowment. A list of donors can be found in our annual reports published online . The findings, interpretations, and conclusions in this report are solely those of its author(s) and are not influenced by any donation.

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Martin Neil Baily, Erik Brynjolfsson, and Anton Korinek

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Machines of mind: The case for an AI-powered productivity boom

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Large language models such as ChatGPT are emerging as powerful tools that not only make workers more productive but also increase the rate of innovation, laying the foundation for a significant acceleration in economic growth. As a general purpose technology, AI will impact a wide array of industries, prompting investments in new skills, transforming business processes, and altering the nature of work.

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ChatGPT Can't Think-Consciousness Is Something Entirely Different to Today's AI

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ChatGPT Can't Think-Consciousness Is Something Entirely Different to Today's AI

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There has been shock around the world at the rapid rate of progress with ChatGPT and other artificial intelligence created with what’s known as large language models (LLMs). These systems can produce text that seems to display thought, understanding, and even creativity.
But can these systems really think and understand? This is not a question that can be answered through technological advance, but careful philosophical analysis and argument tell us the answer is no. And without working through these philosophical issues, we will never fully comprehend the dangers and benefits of the AI revolution.
In 1950, the father of modern computing, Alan Turing, published a paper that laid out a way of determining whether a computer thinks. This is now called “the Turing test.” Turing imagined a human being engaged in conversation with two interlocutors hidden from view: one another human being, the other a computer. The game is to work out which is which.
If a computer can fool 70 percent of judges in a 5-minute conversation into thinking it’s a person, the computer passes the test. Would passing the Turing test—something that now seems imminent—show that an AI has achieved thought and understanding?

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There has been shock around the world at the rapid rate of progress with ChatGPT and other artificial intelligence created with what's known as large language models (LLMs). These systems can produce text that seems to display thought, understanding, and even creativity.

But can these systems really think and understand? This is not a question that can be answered through technological advance, but careful philosophical analysis and argument tell us the answer is no. And without working through these philosophical issues, we will never fully comprehend the dangers and benefits of the AI revolution.

In 1950, the father of modern computing, Alan Turing, published a paper that laid out a way of determining whether a computer thinks. This is now called "the Turing test." Turing imagined a human being engaged in conversation with two interlocutors hidden from view: one another human being, the other a computer. The game is to work out which is which.

If a computer can fool 70 percent of judges in a 5-minute conversation into thinking it's a person, the computer passes the test. Would passing the Turing test-something that now seems imminent-show that an AI has achieved thought and understanding?

Chess Challenge

Turing dismissed this question as hopelessly vague, and replaced it with a pragmatic definition of "thought," whereby to think just means passing the test.

Turing was wrong, however, when he said the only clear notion of "understanding" is the purely behavioral one of passing his test. Although this way of thinking now dominates cognitive science, there is also a clear, everyday notion of "understanding" that's tied to consciousness. To understand in this sense is to consciously grasp some truth about reality.

In 1997, the Deep Blue AI beat chess grandmaster Garry Kasparov. On a purely behavioral conception of understanding, Deep Blue had knowledge of chess strategy that surpasses any human being. But it was not conscious: it didn't have any feelings or experiences.

Humans consciously understand the rules of chess and the rationale of a strategy. Deep Blue, in contrast, was an unfeeling mechanism that had been trained to perform well at the game. Likewise, ChatGPT is an unfeeling mechanism that has been trained on huge amounts of human-made data to generate content that seems like it was written by a person.

It doesn't consciously understand the meaning of the words it's spitting out. If "thought" means the act of conscious reflection, then ChatGPT has no thoughts about anything.

Time to Pay Up

How can I be so sure that ChatGPT isn't conscious? In the 1990s, neuroscientist Christof Koch bet philosopher David Chalmers a case of fine wine that scientists would have entirely pinned down the "neural correlates of consciousness" in 25 years.

By this, he meant they would have identified the forms of brain activity necessary and sufficient for conscious experience. It's about time Koch paid up, as there is zero consensus that this has happened.

This is because consciousness can't be observed by looking inside your head. In their attempts to find a connection between brain activity and experience, neuroscientists must rely on their subjects' testimony, or on external markers of consciousness. But there are multiple ways of interpreting the data.

Some scientists believe there is a close connection between consciousness and reflective cognition-the brain's ability to access and use information to make decisions. This leads them to think that the brain's prefrontal cortex-where the high-level processes of acquiring knowledge take place-is essentially involved in all conscious experience. Others deny this, arguing instead that it happens in whichever local brain region that the relevant sensory processing takes place.

Scientists have good understanding of the brain's basic chemistry. We have also made progress in understanding the high-level functions of various bits of the brain. But we are almost clueless about the bit in between: how the high-level functioning of the brain is realized at the cellular level.

People get very excited about the potential of scans to reveal the workings of the brain. But fMRI (functional magnetic resonance imaging) has a very low resolution: every pixel on a brain scan corresponds to 5.5 million neurons, which means there's a limit to how much detail these scans are able to show.

I believe progress on consciousness will come when we understand better how the brain works.

Pause in Development

As I argue in my forthcoming book Why? The Purpose of the Universe, consciousness must have evolved because it made a behavioral difference. Systems with consciousness must behave differently, and hence survive better, than systems without consciousness.

If all behavior was determined by underlying chemistry and physics, natural selection would have no motivation for making organisms conscious; we would have evolved as unfeeling survival mechanisms.

My bet, then, is that as we learn more about the brain's detailed workings, we will precisely identify which areas of the brain embody consciousness. This is because those regions will exhibit behavior that can't be explained by currently known chemistry and physics. Already, some neuroscientists are seeking potential new explanations for consciousness to supplement the basic equations of physics.

While the processing of LLMs is now too complex for us to fully understand, we know that it could in principle be predicted from known physics. On this basis, we can confidently assert that ChatGPT is not conscious.

There are many dangers posed by AI, and I fully support the recent call by tens of thousands of people, including tech leaders Steve Wozniak and Elon Musk, to pause development to address safety concerns. The potential for fraud, for example, is immense. However, the argument that near-term descendants of current AI systems will be super-intelligent, and hence a major threat to humanity, is premature.

This doesn't mean current AI systems aren't dangerous. But we can't correctly assess a threat unless we accurately categorize it. LLMs aren't intelligent. They are systems trained to give the outward appearance of human intelligence. Scary, but not that scary.
This article is republished from Image Credit: Gerd Altmann from Pixabay The Conversation under a Creative Commons license. Read the original article.

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ChatGPT Can't Think-Consciousness Is Something Entirely Different to Today's AI

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There has been shock around the world at the rapid rate of progress with ChatGPT and other artificial intelligence created with what's known as large language models (LLMs). These systems can produce text that seems to display thought, understanding, and even creativity. But can these systems really think and understand?

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Artificial Intelligence for Security Practitioners: A Conversation with ChatGPT

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Artificial Intelligence for Security Practitioners: A Conversation with ChatGPT

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ChatGPT and similar programs have put artificial intelligence (AI) into the hands of everyone with an internet connection. AI will transform how many professional fields conducts day-to-day business. Can AI help the Daniel K. Inouye Asia-Pacific Center for Security Studies (DKI APCSS) carry out its mission? The conversion with ChatGPT provides an overview of its basic capabilities and explores how it can assist DKI APCSS.
ChatGPT provides a glimpse into how powerful a tool artificial intelligence (AI) is and can become in the future. People in many different career fields are finding out how it can improve or even transform their industries. Can ChatGPT and other forms of AI being developed change how security practitioners revamp how they conduct business? At The Daniel K. Inouye Asia-Pacific Center for Security Studies (DKI APCSS), everyone is focused on its mission: “DKI APCSS builds resilient capacity, shared understanding, and networked relationships among civilian and military practitioners and institutions to advance a free and open Indo-Pacific.” DKI APCSS brings officials and other policymakers from around the world together to discuss the latest security concerns for the Indo-Pacific region and the world. How can ChatGPT help DKI APCSS carry out its mission? Let’s bring ChatGPT into the discussion to find out.

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Daniel K. Inouye Asia-Pacific Center for Security Studies

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By Brent Feller [1]

Summary: ChatGPT and similar programs have put artificial intelligence (AI) into the hands of everyone with an internet connection. AI will transform how many professional fields conducts day-to-day business. Can AI help the Daniel K. Inouye Asia-Pacific Center for Security Studies (DKI APCSS) carry out its mission? The conversion with ChatGPT provides an overview of its basic capabilities and explores how it can assist DKI APCSS.

ChatGPT provides a glimpse into how powerful a tool artificial intelligence (AI) is and can become in the future. People in many different career fields are finding out how it can improve or even transform their industries. Can ChatGPT and other forms of AI being developed change how security practitioners revamp how they conduct business? At The Daniel K. Inouye Asia-Pacific Center for Security Studies (DKI APCSS), everyone is focused on its mission: "DKI APCSS builds resilient capacity, shared understanding, and networked relationships among civilian and military practitioners and institutions to advance a free and open Indo-Pacific." DKI APCSS brings officials and other policymakers from around the world together to discuss the latest security concerns for the Indo-Pacific region and the world. How can ChatGPT help DKI APCSS carry out its mission? Let's bring ChatGPT into the discussion to find out.

It is important to point out the advice ChatGPT gave above regarding verifying information and critical thinking. ChatGPT focuses on providing an answer and does not always give a correct response. The term used for this is called hallucination. Everyone using ChatGPT needs to understand this and only use this tool as a starting point.

Three times each year, DKI APCSS conducts a course titled Comprehensive Security Cooperation. This course brings together individuals from around the world to discuss security concerns. ChatGPT provided many of the topics addressed over the 5-week course.

Now, to an individual with experience in Indo-Pacific maritime security issues, all of this information provided by ChatGPT is common knowledge. However, for an individual coming to this topic for the first time, like many of the individuals who attend courses at APCSS, this is a concise summation of the issues.

The initial questions to ChatGPT show that it can provide individuals with information that enables them to obtain a basic level of understanding of a topic. This can help in understanding the security challenges, but DKI APCSS is more than imparting knowledge to fellows; it is about building relationships to help get to solutions. How can ChatGPT help in this aspect?

ChatGPT drives directly to the heart of the issue and explains why DKI APCSS is important to the region. Fellows can learn about security concerns through ChatGPT, but it cannot provide what DKI APCSS does through its courses: foster "dialogue, cooperation, and coordination." This is what will solve current and future security concerns, and AI cannot replace this.

How can ChatGPT help DKI APCSS build relationships? ChatGPT can assist DKI APCSS in building relationships by facilitating communication and dialogue among stakeholders, providing a platform for engagement and information sharing, fostering understanding of diverse perspectives, and offering insights and recommendations on fostering cooperation and collaboration among nations in the Asia-Pacific region. However, building relationships requires personal interactions and context-specific approaches beyond the capabilities of a language model.

The power of AI is at its nascent stage, but it is already having a transformative impact in many areas. For security practitioners, ChatGPT can be utilized to increase knowledge about security concerns and provide further insights. DKI APCSS can be at the forefront of harnessing this new tool to carry out part of its mission, informing and understanding. With assistance from AI, DKI APCSS can double down on what will actually solve security concerns, as noted by ChatGPT, and that is in building relationships.

[1] Military Professor, DKI APCSS, Honolulu, Hawaii, U.S.A

The views expressed in this article are the author's alone, and do not necessarily reflect the official position of the DKI APCSS or the United States Government.
May 2023

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Artificial Intelligence for Security Practitioners: A Conversation with ChatGPT

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By Brent Feller Summary: ChatGPT and similar programs have put artificial intelligence (AI) into the hands of everyone with an internet connection. AI will transform how many professional fields conducts day-to-day business. Can AI help the Daniel K. Inouye Asia-Pacific Center for Security Studies (DKI APCSS) carry out its mission?

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Oversight of A.I.: Rules for Artificial Intelligence | United States Senate Committee on the Judiciary

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Oversight of A.I.: Rules for Artificial Intelligence | United States Senate Committee on the Judiciary

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