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Casey Flores AIGP, CIPP/US on LinkedIn: AIGP March 2024 | 50 comments

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Hi everyone! I have coalesced my list of #AIGP resources and notes into a single accessible document (Why did I not think of this in the first place?). I… | 50 comments on LinkedIn

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Here are two more #AIGP exam tips. 1. Understand Bloom's taxonomy. There's a reason the hierarchical teaching model is included in the Body of Knowledge (available at https://lnkd.in/epgCnB7d). It shows the types of skills that will be tested. More specifically, the BoK confirms that the exam is based on the Remember, Understand, Apply, and Analyze levels. Those, in turn, translate to actions like define and memorize (Remember), identify and describe (Understand), interpret and demonstrate (Apply), and compare and contrast (Analyze). Zooming out for context, I recall reviewing the very first round of questions that were submitted. Many were definitional, in part because the process started so long ago (~1 year ago) and they were the low-hanging fruit. But most were simply too easy because the exam isn't limited to memorization. It's more about understanding the types of issues that an AI governance professional will face in the real world, from knowing how to spot an issue to recognizing how it could or should be handled. So while you should study the terms in the Glossary (available at https://lnkd.in/emMWdiRQ), you also need to carefully read other resources that show how to understand and apply concepts in context. 2. Understand distractors. As mentioned last week, writing effective distractors is both art and science. The goal is to create an answer that might look correct to someone who doesn't know the topic, but is clearly incorrect to someone who does. I've been doing this long enough to realize that the most common distractors fall into three main categories: too broad; too narrow; or tangential. For example, if a question tests an understanding of bias, and one of the choices is specific to privacy, it's not likely to be the answer. Of course, questions can be pushed and pulled in lots of different directions, but the exam development process is comprehensive so that the exam is fair. That's why understanding these design elements is so important. They'll demystify the exam, and help you better prioritize your time.

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Kevin Fumai on LinkedIn: #aigp | 43 comments

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The #AIGP posts I've shared the past couple months have been well-received. 350K impressions, 3.2K interactions, and lots of private messages. Two things... | 43 comments on LinkedIn

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Przemysław (Shemy) Gruchała on LinkedIn: #aigovernance #iapp #professionalcertification #careerdevelopment #ai… | 27 comments

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My post on passing the AIGP exam got some attention, and people are already asking how I prepared for it. So, here’s my take on it!
(disclaimer⚡: this is the… | 27 comments on LinkedIn

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The AI Act Explorer | EU Artificial Intelligence Act

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AI Act has entered into application. Article 113 of the AI Act codifies its entry into force and application: "𝘛𝘩𝘪𝘴 𝘙𝘦𝘨𝘶𝘭𝘢𝘵𝘪𝘰𝘯 𝘴𝘩𝘢𝘭𝘭 𝘦𝘯𝘵𝘦𝘳 𝘪𝘯𝘵𝘰 𝘧𝘰𝘳𝘤𝘦 𝘰𝘯 𝘵𝘩𝘦 𝘵𝘸𝘦𝘯𝘵𝘪𝘦𝘵𝘩 𝘥𝘢𝘺 𝘧𝘰𝘭𝘭𝘰𝘸𝘪𝘯𝘨 𝘵𝘩𝘢𝘵 𝘰𝘧 𝘪𝘵𝘴 𝘱𝘶𝘣𝘭𝘪𝘤𝘢𝘵𝘪𝘰𝘯 𝘪𝘯 𝘵𝘩𝘦 𝘖𝘧𝘧𝘪𝘤𝘪𝘢𝘭 𝘑𝘰𝘶𝘳𝘯𝘢𝘭 𝘰𝘧 𝘵𝘩𝘦 𝘌𝘶𝘳𝘰𝘱𝘦𝘢𝘯 𝘜𝘯𝘪𝘰𝘯." Today, 𝐀𝐮𝐠𝐮𝐬𝐭 1𝐬𝐭, 2024, marks the twentieth day since the publication of the AI Act in the Official Journal of the E.U. on the 7th of July 2024. 𝐊𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬 𝐟𝐫𝐨𝐦 𝐨𝐮𝐫 𝐩𝐫𝐚𝐜𝐭𝐢𝐭𝐢𝐨𝐧𝐞𝐫𝐬: 📌 𝐃𝐚𝐭𝐚 𝐫𝐞𝐩𝐮𝐫𝐩𝐨𝐬𝐢𝐧𝐠: organisation must bear in mind the GDPR foundational principle of purpose limitation, meaning that personal data collected for a processing activity (i.e., recruitment) should not be used for an incompatible purpose (i.e., train AI technology) 📌 𝐋𝐚𝐰𝐟𝐮𝐥 𝐛𝐚𝐬𝐢𝐬: almost all the AI projects we have been involved with our clients are processing personal data. In the context of deploying AI, organisation must make sure that they have a lawful basis to process personal data. In most of the case, vital interest is not an avenue to pursue and some of the Data Protection Authorities released guidance in that sense. 📌 𝐈𝐧𝐝𝐢𝐯𝐢𝐝𝐮𝐚𝐥'𝐬 𝐫𝐢𝐠𝐡𝐭𝐬 𝐮𝐧𝐝𝐞𝐫 𝐆𝐃𝐏𝐑 might be affected. Organisations deploying AI must analyse and compensate the impact on, for example, the right to object or the right to data erasure (right to be forgotten). 📌 𝐇𝐢𝐠𝐡𝐭 𝐫𝐢𝐬𝐤 𝐀𝐈 𝐒𝐲𝐬𝐭𝐞𝐦𝐬. Organisations must be able to identify if the AI technology they plan to deploy qualifies as a High-Risk AI system under the AI Act. If that is the case additional compliance obligations must be follow through including ROPAs and DPIAs reviews and carrying out additional assessments, such as Fundamental Rights Impact Assessment or Bias Assessments. 📌 𝐎𝐭𝐡𝐞𝐫 𝐥𝐚𝐰𝐬. Beside the data protection law there are other laws that will play an important role in how an organisation designs, tests, trains and deploys AI, such as intellectual property laws, cybersecurity, product liability laws, contractual law. At Symmetry Compliance we can guide organisations through complying with the AI Act. Our fantastic team is made of brilliant consultants and data protection practitioners with relevant experience in the market, in diversified business contexts. CC - Petruta Pirvan Emiliya Dinkova Anton Ivanov Mateo Muñoz Landívar Melis Aktaş Jug Puljizevic#AIAct #Compliance #RiskManagement #DataProtection #DigitalRegulations

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Petruta Pirvan on LinkedIn: #ai #aisystems #aimodels #aiact

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𝐖𝐡𝐲 𝐢𝐭 𝐢𝐬 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐭𝐨 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭𝐢𝐚𝐭𝐞 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐀𝐈 𝐌𝐨𝐝𝐞𝐥𝐬 𝐚𝐧𝐝 𝐀𝐈 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 It is a common error to...

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CHAPTER II

Article 5

1. The following AI practices shall be prohibited:

the placing on the market, the putting into service or the use of AI systems for the evaluation or classification of natural persons or groups of persons over a certain period of time based on their social behaviour or known, inferred or predicted personal or personality characteristics, with the social score leading to either or both of the following:

the use of 'real-time' remote biometric identification systems in publicly accessible spaces for the purposes of law enforcement, unless and in so far as such use is strictly necessary for one of the following objectives:

Point (h) of the first subparagraph is without prejudice to Article 9 of Regulation (EU) 2016/679 for the processing of biometric data for purposes other than law enforcement.

2. The use of 'real-time' remote biometric identification systems in publicly accessible spaces for the purposes of law enforcement for any of the objectives referred to in paragraph 1, first subparagraph, point (h), shall be deployed for the purposes set out in that point only to confirm the identity of the specifically targeted individual, and it shall take into account the following elements:

In addition, the use of 'real-time' remote biometric identification systems in publicly accessible spaces for the purposes of law enforcement for any of the objectives referred to in paragraph 1, first subparagraph, point (h), of this Article shall comply with necessary and proportionate safeguards and conditions in relation to the use in accordance with the national law authorising the use thereof, in particular as regards the temporal, geographic and personal limitations. The use of the 'real-time' remote biometric identification system in publicly accessible spaces shall be authorised only if the law enforcement authority has completed a fundamental rights impact assessment as provided for in Article 27 and has registered the system in the EU database according to Article 49. However, in duly justified cases of urgency, the use of such systems may be commenced without the registration in the EU database, provided that such registration is completed without undue delay.

3. For the purposes of paragraph 1, first subparagraph, point (h) and paragraph 2, each use for the purposes of law enforcement of a 'real-time' remote biometric identification system in publicly accessible spaces shall be subject to a prior authorisation granted by a judicial authority or an independent administrative authority whose decision is binding of the Member State in which the use is to take place, issued upon a reasoned request and in accordance with the detailed rules of national law referred to in paragraph 5. However, in a duly justified situation of urgency, the use of such system may be commenced without an authorisation provided that such authorisation is requested without undue delay, at the latest within 24 hours. If such authorisation is rejected, the use shall be stopped with immediate effect and all the data, as well as the results and outputs of that use shall be immediately discarded and deleted.

The competent judicial authority or an independent administrative authority whose decision is binding shall grant the authorisation only where it is satisfied, on the basis of objective evidence or clear indications presented to it, that the use of the 'real-time' remote biometric identification system concerned is necessary for, and proportionate to, achieving one of the objectives specified in paragraph 1, first subparagraph, point (h), as identified in the request and, in particular, remains limited to what is strictly necessary concerning the period of time as well as the geographic and personal scope. In deciding on the request, that authority shall take into account the elements referred to in paragraph 2. No decision that produces an adverse legal effect on a person may be taken based solely on the output of the 'real-time' remote biometric identification system.

4. Without prejudice to paragraph 3, each use of a 'real-time' remote biometric identification system in publicly accessible spaces for law enforcement purposes shall be notified to the relevant market surveillance authority and the national data protection authority in accordance with the national rules referred to in paragraph 5. The notification shall, as a minimum, contain the information specified under paragraph 6 and shall not include sensitive operational data.

5. A Member State may decide to provide for the possibility to fully or partially authorise the use of 'real-time' remote biometric identification systems in publicly accessible spaces for the purposes of law enforcement within the limits and under the conditions listed in paragraph 1, first subparagraph, point (h), and paragraphs 2 and 3. Member States concerned shall lay down in their national law the necessary detailed rules for the request, issuance and exercise of, as well as supervision and reporting relating to, the authorisations referred to in paragraph 3. Those rules shall also specify in respect of which of the objectives listed in paragraph 1, first subparagraph, point (h), including which of the criminal offences referred to in point (h)(iii) thereof, the competent authorities may be authorised to use those systems for the purposes of law enforcement. Member States shall notify those rules to the Commission at the latest 30 days following the adoption thereof. Member States may introduce, in accordance with Union law, more restrictive laws on the use of remote biometric identification systems.

6. National market surveillance authorities and the national data protection authorities of Member States that have been notified of the use of 'real-time' remote biometric identification systems in publicly accessible spaces for law enforcement purposes pursuant to paragraph 4 shall submit to the Commission annual reports on such use. For that purpose, the Commission shall provide Member States and national market surveillance and data protection authorities with a template, including information on the number of the decisions taken by competent judicial authorities or an independent administrative authority whose decision is binding upon requests for authorisations in accordance with paragraph 3 and their result.

7. The Commission shall publish annual reports on the use of real-time remote biometric identification systems in publicly accessible spaces for law enforcement purposes, based on aggregated data in Member States on the basis of the annual reports referred to in paragraph 6. Those annual reports shall not include sensitive operational data of the related law enforcement activities.

8. This Article shall not affect the prohibitions that apply where an AI practice infringes other Union law.

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Contents of the book

The upcoming AI Act marks a turning point in the regulation of artificial intelligence, putting the legality and ethics of AI at the top of mind. This new European Regulation sets strict rules for the application of AI and uses a risk-based approach. This English-language book is your indispensable reference. Each section of the Act is thoroughly analyzed and discussed, with a focus on the practical implications for legal professionals.

What does the book offer you?

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This book is a practical guide to the upcoming European AI Act for legal professionals, covering its articles, practical examples, and 'trustworthy AI' principles.

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In 2021, the Commission presented its proposal for the AI Act which is currently in the final stages of the legislative process.

While some provisions of the AI Act will already apply shortly after the adoption of the Regulation, others (for example, some requirements on the high-risk AI systems) will only be applicable at the end of a transitional period (i.e. the time between entry into force and date of applicability).

In this context, the Commission is initiating the AI Pact, seeking the voluntary commitment of industry to anticipate the AI Act and to start implementing its requirements ahead of the legal deadline.

This is all the more important given that in the past few months technological developments and the mainstream adoption of generative and general purpose AI systems have been accelerating. While many players in the field have already taken steps to alleviate concerns, further urgent actions are necessary.

1. What will the Pact consist of?

The AI Pact is a scheme that will foster early implementation of the measures foreseen by the AI Act. Companies will have the opportunity to demonstrate and share their commitment towards the objectives of the future AI Act and prepare early on to be ready for its implementation. More specifically, the Pact will encourage companies to voluntarily communicate the processes and practices they are putting in place to prepare for compliance and ensure that the design, development and use of AI is trustworthy.

Industry commitments will take the form of pledges (declarations of engagement) to work towards compliance with the upcoming AI Act accompanied with details about concrete actions being carried out or planned to address specific requirements of the future AI Act. Such commitments can include a gradual approach, i.e. outline plans to move, within a defined timeframe, towards higher levels of ambition than actions already implemented.

The pledges would be collected and published by the Commission, in order to provide visibility, increase credibility, and build additional trust in the technologies developed by companies taking part in the Pact.

2. Which actors will be involved?

The AI Pact will convene, on a voluntary basis, key EU and non-EU industry players to take part in a community of exchange of best practices that will aim to increase awareness of the principles underpinning the future AI Act, and (upon adoption of the Act) ensure commitment to anticipate and bridge the gap before the applicability of the AI regulation.

3. What are the benefits of the Pact for participants?

The Commission will work together with the participants and support for them in:

building of common understanding of the objectives of the future AI Act;

taking concrete actions to understand, adapt and prepare for the future implementation of the AI Act (e.g. build internal processes, prepare staff and self-assess AI systems);

sharing knowledge and increase the visibility and credibility of the safeguards put in place to demonstrate trustworthy AI; and ultimately

building additional trust in AI technologies.

The Pact will allow front-runners and ambitious participants to test and share their solutions with the wider community, giving them a first-mover advantage.

4. What are the next steps?

In November 2023, the Commission launched a "call for interest" for organisations willing to get actively involved in the AI Pact. As a next step, the Commission will bring together interested parties, in the first half of 2024, to discuss the ambitions of the Pact and collect preliminary ideas and best practices which could inspire future pledges. Following the formal adoption of the AI Act, the AI Pact will be officially launched and "frontrunner" organisations will be invited to make their first pledges public.
Interested to be an active stakeholder in the AI Pact? Join the initiative on behalf of your company! Your company has already produced internal guidelines or processes to ensure the design, development and use of trustworthy AI systems? Share and test them with the AI Pact community!

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The AI Pact will encourage and support companies in planning ahead for the measures provided for in the AI Act.

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The EU AI Act was proposed in April 2021, politically agreed in December 2023 and published in the Official Journal of the EU 12 July 2024. It will be a keystone regulation for the development and deployment of AI in the EU and around the world.

This resource shows some of the most important dates and milestones for the future implementation of the AI Act. The IAPP additionally hosts an " EU AI Act" topic page, which regularly updates with the latest news and resources.

Entry into force: 1 Aug. 2024

20 days after publication in the official journal of the EU.

Entry into application: 2 Aug. 2026

Exceptions exist for specific provisions.

* The EU AI Office has launched the AI Pact which calls on AI system providers and deployer to voluntarily implement some of the key provisions of the AI Act, prior to entry into application.

Six months after entry into force

* Prohibitions on unacceptable risk AI.

12 months after entry into force

* Obligations go into effect for providers of general purpose AI models.

* Appointment of member state competent authorities.

* Annual Commission review of, and possible legislative amendments to, the list of prohibited AI..

18 months after entry into force

* Commission implements act on post-market monitoring.

24 months after entry into force

* Obligations go into effect for high-risk AI systems specifically listed in Annex III, including systems in biometrics, critical infrastructure, education, employment, access to essential public services, law enforcement, immigration and administration of justice.

* Member states to have implemented rules on penalties, including administrative fines.

* Member state authorities to have established at least one operational AI regulatory sandbox.

* Commission review, and possible amendment of, the list of high-risk AI systems.

36 months after entry into force

* Obligations go into effect for high-risk AI systems that are not prescribed in Annex III but are intended to be used as a safety component of a product.

* Obligations go into effect for high-risk AI systems in which the AI itself is a product and the product is required to undergo a third-party conformity assessment under existing specific EU laws, for example toys, radio equipment, in vitro diagnostic medical devices, civil aviation security and agricultural vehicles.

* Obligations go into effect for certain AI systems that are components of the large-scale information technology systems established by EU law in the areas of freedom, security and justice, such as the Schengen Information System.

* The Commission can issue delegated acts on:

Definition of AI system.

Criteria and use cases for high-risk AI.

Thresholds for general purpose AI models with systemic risk.

Technical documentation requirements for general purpose AI.

Conformity assessments.

EU declaration of conformity.

* The Commission's power to issue delegated acts lasts for an initial period ending 2 Aug. 2029 and is extendable for another five years.

* The AI Office is to draw up codes of practice covering, but not necessarily limited to, obligations for providers of general purpose AI models. Codes of practice should be ready by 2 May 2025 and should provide at least a three-month period before taking effect.

* The Commission can issue guidance on:

High-risk AI incident reporting by 2. Aug 2025.

Practical implementation of high-risk AI requirements, with a list of practical examples of high-risk and not high-risk use cases by 2 Feb. 2026.

Prohibited AI practices "when deemed necessary."

Application of the definition of an AI system "when deemed necessary."

Requirements for high-risk AI systems "when deemed necessary."

Practical implementation of transparency obligations "when deemed necessary."

Relationship of the AI Act and its enforcement with other EU law "when deemed necessary."

* The Commission is to issue its report on its delegated powers no later than nine months before five years after entry into force.

Related Stories

This topic page contains a curation of the IAPP's coverage, analysis and relevant resources covering artificial intelligence....

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EU AI Act: Next Steps for Implementation

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This resource shows some of the most important dates and milestones for the future implementation of the AI Act.

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FPF Resources on the EU AI Act - Future of Privacy Forum

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The EU AI Act is expected to play a crucial role in global development of AI Governance frameworks. We are compiling on this page a continuously updated list of FPF Resources dedicated to the EU AI Act, as well as to its relationship to the EU GDPR and other privacy…

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Which specific risks should a person, company or government consider when using an AI system, or crafting rules to govern its use? It's not an easy question to answer. If it's an AI with control over critical infrastructure, there's the obvious risk to human safety. But what about an AI designed to score exams, sort resumes or verify travel documents at immigration control? Those each carry their own, categorically different risks, albeit risks no less severe.

In crafting laws to regulate AI, like the EU AI Act or California's SB 1047, policymakers have struggled to come to a consensus on which risks the laws should cover. To help provide a guidepost for them, as well for stakeholders across the AI industry and academia, MIT researchers have developed what they're calling an AI "risk repository" - a sort of database of AI risks.

"This is an attempt to rigorously curate and analyze AI risks into a publicly accessible, comprehensive, extensible and categorized risk database that anyone can copy and use, and that will be kept up to date over time," Peter Slattery, a researcher at MIT's FutureTech group and lead on the AI risk repository project, told TechCrunch. "We created it now because we needed it for our project, and had realized that many others needed it, too."

Slattery says that the AI risk repository, which includes over 700 AI risks grouped by causal factors (e.g. intentionality), domains (e.g. discrimination) and subdomains (e.g. disinformation and cyberattacks), was borne out of a desire to understand the overlaps and disconnects in AI safety research. Other risk frameworks exist. But they cover only a fraction of the risks identified in the repository, Slattery says, and these omissions could have major consequences for AI development, usage and policymaking.

"People may assume there is a consensus on AI risks, but our findings suggest otherwise," Slattery added. "We found that the average frameworks mentioned just 34% of the 23 risk subdomains we identified, and nearly a quarter covered less than 20%. No document or overview mentioned all 23 risk subdomains, and the most comprehensive covered only 70%. When the literature is this fragmented, we shouldn't assume that we are all on the same page about these risks."

To build the repository, the MIT researchers worked with colleagues at the University of Queensland, the nonprofit Future of Life Institute, KU Leuven and AI startup Harmony Intelligence to scour academic databases and retrieve thousands of documents relating to AI risk evaluations.

The researchers found that the third-party frameworks they canvassed mentioned certain risks more often than others. For example, over 70% of the frameworks included the privacy and security implications of AI, whereas only 44% covered misinformation. And while over 50% discussed the forms of discrimination and misrepresentation that AI could perpetuate, only 12% talked about "pollution of the information ecosystem" - i.e. the increasing volume of AI-generated spam.

"A takeaway for researchers and policymakers, and anyone working with risks, is that this database could provide a foundation to build on when doing more specific work," Slattery said. "Before this, people like us had two choices. They could invest significant time to review the scattered literature to develop a comprehensive overview, or they could use a limited number of existing frameworks, which might miss relevant risks. Now they have a more comprehensive database, so our repository will hopefully save time and increase oversight."

But will anyone use it? It's true that AI regulation around the world today is at best a hodgepodge: a spectrum of different approaches disunified in their goals. Had an AI risk repository like MIT's existed before, would it have changed anything? Could it have? That's tough to say.

Another fair question to ask is whether simply being aligned on the risks that AI poses is enough to spur moves toward competently regulating it. Many safety evaluations for AI systems have significant limitations, and a database of risks won't necessarily solve that problem.

The MIT researchers plan to try, though. Neil Thompson, head of the FutureTech lab, tells TechCrunch that the group plans in its next phase of research to use the repository to evaluate how well different AI risks are being addressed.

"Our repository will help us in the next step of our research, when we will be evaluating how well different risks are being addressed," Thompson said. "We plan to use this to identify shortcomings in organizational responses. For instance, if everyone focuses on one type of risk while overlooking others of similar importance, that's something we should notice and address.

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MIT researchers release a repository of AI risks | TechCrunch

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A group of researchers at MIT and elsewhere have compiled what they claim is the most thorough databases of possible risks around AI use.

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Regulation (EU) No 1025/2012 on European standardisation

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Regulation (EU) No 1025/2012 on European standardisation

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Regulation (EU) No 1025/2012 of the European Parliament and of the Council of 25 October 2012 on European standardisation, amending Council Directives 89/686/EEC and 93/15/EEC and Directives 94/9/EC, 94/25/EC, 95/16/EC, 97/23/EC, 98/34/EC, 2004/22/EC, 2007/23/EC, 2009/23/EC and 2009/105/EC of the European Parliament and of the Council and repealing Council Decision 87/95/EEC and Decision No 1673/2006/EC of the European Parliament and of the Council Text with EEA relevance

OJ L 316, 14.11.2012, p. 12-33 (BG, ES, CS, DA, DE, ET, EL, EN, FR, GA, IT, LV, LT, HU, MT, NL, PL, PT, RO, SK, SL, FI, SV)
⏵This document has been published in a special edition(s) (HR)

In force: This act has been changed. Current consolidated version: 09/07/2023

ELI: http://data.europa.eu/eli/reg/2012/1025/oj

Languages, formats and link to OJ

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Regulation (EU) No 1025/2012 of the European Parliament and of the Council of 25 October 2012 on European standardisation, amending Council Directives 89/686/EEC and 93/15/EEC and Directives 94/9/EC, 94/25/EC, 95/16/EC, 97/23/EC, 98/34/EC, 2004/22/EC, 2007/23/EC, 2009/23/EC and 2009/105/EC of the European Parliament and of the Council and repealing Council Decision 87/95/EEC and Decision No 1673/2006/EC of the European Parliament and of the Council Text with EEA relevance OJ L 316, 14.11.2012, p.

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Regulation (EU) 2023/988 on general product safety

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Regulation (EU) 2023/988 on general product safety

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The NIST AI Risk Management Framework (AI RMF)

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The NIST AI Risk Management Framework (AI RMF)

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NIST AI Risk Management Framework (AI RMF) is intended for voluntary use and to improve the ability to incorporate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems.

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In the summer I passed the AIGP by the International Association of Privacy Professionals. At the time, I provided a review of my experience along with my opinions the positives and negatives of the certification.