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Technological Repression of Xinjiang Muslims (Reagan and Adrienne)

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Technological Repression of Xinjiang Muslims (Reagan and Adrienne)

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https://www.theguardian.com/news/2019/apr/11/china-hi-tech-war-on-muslim-minority-xinjiang-uighurs-surveillance-face-recognition

Summary: China has used a system called the Integrated Joint Operations Platform (Ijop), a regional data system that uses AI to monitor the countless checkpoints in and around Xinjiang’s cities. Any attempt to enter public institutions such as hospitals, banks, parks or shopping centres, or to cross beyond the boundaries of his local police precinct, would trigger the Ijop to alert police. The system profiled uighurs as potential terrorists using biometrics and theirdigital history to lock them in place.

key points:
-  “war on terror” depends less on drones and strikes by elite military units than facial recognition software and machine learning algorithms
- used to repress and to easily identify uighurs in order to place them in detention centres
- compromises privacy and human dignity

merits for chinese government to do this:
- could potentially help identify and screen terrorists to maintain safety more effectively

criticisms / controversies:
- violates privacy
- instituitionalised discrimination
- goes against human dignity and their rights
- sets a dangerous precedent for governments to continue utilising such technology to exploit and control those they deem to be threats

possible questions:
- is the collection of personal data in the name of safety ever justified?

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n mid-2017, Alim, a Uighur man in his 20s, returned to China from studying abroad. As soon as he landed back in the country, he was pulled off the plane by police officers. He was told his trip abroad meant that he was now under suspicion of being "unsafe". The police administered what they call a "health check", which involved collecting several types of biometric data, including DNA, blood type, fingerprints, voice recordings and face scans - a process that all adults in the Uighur autonomous region of Xinjiang, in north-west China, are expected to undergo.

After his "health check", Alim was transported to one of the hundreds of detention centres that dot north-west China. These centres have become an important part of what Xi Jinping's government calls the "people's war on terror", a campaign launched in 2014, which focuses on Xinjiang, a region with a population of roughly 25 million people, just under half of whom are Uighur Muslims. As part of this campaign, the Chinese government has come to treat almost all expressions of Uighur Islamic faith as signs of potential religious extremism and ethnic separatism. Since 2017 alone, more than 1 million Turkic Muslims, including Uighurs, Kazakhs, Kyrgyz and others, have moved through detention centres.

At the detention centre, Alim was deprived of sleep and food, and subjected to hours of interrogation and verbal abuse. "I was so weakened through this process that at one point during my interrogation I began to laugh hysterically," he said when we spoke. Other detainees report being placed in stress positions, tortured with electric shocks, and kept in isolation for long periods. When he wasn't being interrogated, Alim was kept in a tiny cell with 20 other Uighur men.

Many of the detainees had been arrested for having supposedly committed religious and political transgressions through social media apps on their smartphones, which Uighurs are required to produce at checkpoints around Xinjiang. Although there was often no real evidence of a crime according to any legal standard, the digital footprint of unauthorised Islamic practice, or even a connection to someone who had committed one of these vague violations, was enough to land Uighurs in a detention centre. The mere fact of having a family member abroad, or of travelling outside China, as Alim had, often resulted in detention.

Most Uighurs in the detention centres are on their way to serving long prison sentences, or to indefinite captivity in a growing network of internment camps, which the Chinese state has described as facilities for "transformation through education". These camps, which function as medium-security prisons and, in some cases, forced-labour factories, attempt to train Uighurs to disavow their Islamic identity and embrace the secular principles of the Chinese state. They forbid the use of the Uighur language and instead offer drills in Mandarin, the language of China's Han majority. Only a handful of detainees who are not Chinese citizens have been fully released from this "re-education" system.

Police on patrol in Kashgar, in the Xinjiang region. Photograph: Tom Phillips/The Guardian

Alim was relatively lucky: he was let out after only two weeks. (He later learned that a relative had intervened in his case.) But a few weeks later, when he went to meet a friend for lunch at a mall in his home city, he had another shock. At a security checkpoint at the entrance to the mall, Alim scanned the photo on his government-issued identification card, and presented himself before a security camera equipped with facial recognition software. An alarm sounded. The security guards let him pass, but within a few minutes he was approached by police officers, who then took him into custody.

Alim learned that he had been placed on a blacklist maintained by the Integrated Joint Operations Platform (Ijop), a regional data system that uses AI to monitor the countless checkpoints in and around Xinjiang's cities. Any attempt to enter public institutions such as hospitals, banks, parks or shopping centres, or to cross beyond the boundaries of his local police precinct, would trigger the Ijop to alert police. The system had profiled him and predicted that he was a potential terrorist.

There was little Alim could do. Officers told him he should "just stay at home" if he wanted to avoid detention again. Although he was officially free, Alim's biometrics and his digital history were being used to lock him in place. "I'm so angry and afraid at the same time," he told me. He was haunted by his data.

hina's version of the "war on terror" depends less on drones and strikes by elite military units than facial recognition software and machine learning algorithms. Its targets are not foreigners but domestic minority populations who appear to threaten the Chinese Communist party's authoritarian rule. In Xinjiang, the web of surveillance reaches from cameras on buildings, to the chips inside mobile devices, to Uighurs' very physiognomy. Face scanners and biometric checkpoints track their movements almost everywhere.

Other programmes scan Uighurs' digital communications, looking for suspect patterns, and flagging religious speech or even a lack of fervour in using Mandarin. Deep-learning systems search in real time through video feeds capturing millions of faces, building an archive that can supposedly help identify suspicious behaviour in order to predict who will become an "unsafe" actor. Actions that can trigger these "computer vision" technologies include dressing in an Islamic fashion and failing to attend nationalistic flag-raising ceremonies. All of these technological systems are brought together in the Ijop, which is constantly learning from the behaviours of the Uighurs it watches.

In her recent study on the rise of "surveillance capitalism", the Harvard scholar Shoshana Zuboff notes that consumers are constantly generating valuable data that can be turned into profitable predictions about our preferences and future behaviours. In the Uighur region, this logic has been taken to an extreme. The power - and potential profitability - of the predictive technologies that purport to keep Xinjiang safe derive from their unfettered access to Uighurs' digital lives and physical movements. From the perspective of China's security-industrial establishment, the principal purpose of Uighur life is to generate data, which can then be used to further refine these systems of surveillance and control.

Controlling the Uighurs has also become a test case for marketing Chinese technological prowess around the world. A hundred government agencies and companies from two dozen countries, including the US, France, Israel and the Philippines, now participate in the highly influential annual China-Eurasia Security Expo in Urumqi, the capital of the Uighur region. The ethos at the expo, and in the Chinese techno-security industry as a whole, is that Muslim populations need to be managed and made productive. Over the past five years, the people's war on terror has allowed a number of Chinese tech startups to achieve unprecedented levels of growth. In just the last two years, the state has invested an estimated $7.2bn in techno-security in Xinjiang. As a spokesperson for one of these tech startups put it, 60% of the world's Muslim-majority nations are part of China's premier international development project, the Belt and Road Initiative, so there is "unlimited market potential" for the type of population-control technology they are developing in Xinjiang.

Some of the technologies pioneered in Xinjiang have already found customers in authoritarian states as far away as sub-Saharan Africa. In 2018, CloudWalk, a Guangzhou-based tech startup that has received more than $301m in state funding, finalised an agreement with Zimbabwe's government to build a national "mass facial recognition programme" in order to address "social security issues". (CloudWalk has not revealed how much the agreement is worth.) Freedom of movement through airports, railways and bus stations throughout Zimbabwe will now be managed through a facial database integrated with other kinds of biometric data. In effect, the Uighur homeland has become an incubator for China's "terror capitalism".

here was a time when the internet seemed to promise a brighter future for China's Uighurs. When I arrived in Urumqi in 2011 to conduct my first year of ethnographic fieldwork, the region had just been wired with 3G mobile data networks. When I returned in 2014, it seemed as though nearly all adults in the city had a smartphone. Suddenly, Uighur cultural figures who the government subsequently labelled "unsafe", such as the pop star Ablajan, developed followings that numbered in the millions.

Most unsettling, from the perspective of the state, unsanctioned Uighur religious teachers based in China and Turkey also developed a deep influence. Since Mao's Religious Reform Movement of 1958, the state had limited Uighurs' access to mosques, Islamic funerary practices, religious knowledge and other Muslim communities. There were virtually no Islamic schools outside of government control, no imams who were not approved by the state. Children under the age of 18 were forbidden to enter mosques. But as social media spread through the Uighur homeland over the course of the last decade, it opened up a virtual space to explore what it meant to be Muslim. It reinforced a sense that the first sources of Uighur identity were their faith and language, their claim to a native way of life, and their membership in a Turkic Muslim community stretching from Urumqi to Istanbul. Rather than being seen as perpetually lacking Han appearance and culture, they could find in their renewed Turkic and Islamic values a cosmopolitan and contemporary identity. Food, movies, music and clothing, imported from Turkey and Dubai, became markers of distinction. Women began to veil themselves. Men began to pray five times a day. They stopped drinking and smoking. Some began to view music, dancing and state television as influences to be avoided.

The Han officials I met during my fieldwork referred to this rise in technologically disseminated religious piety as the "Talibanisation" of the Uighur population. Along with Han settlers, they felt increasingly unsafe travelling to the region's Uighur-majority areas, and uneasy in the presence of pious Turkic Muslims. The officials cited incidents that carried the hallmarks of religiously motivated violence - a knife attack carried out by a group of Uighurs at a train station in Kunming; trucks driven by Uighurs through crowds in Beijing and Urumqi - as a sign that the entire Uighur population was falling under the sway of terrorist ideologies.

Workers walk by the perimeter fence of an 'education centre' in Xinjiang. Photograph: Thomas Peter/Reuters

But, as dangerous as the rise of Uighur social media seemed to Han officials, it also presented them with a new means of control. On 5 July 2009, Uighur high school and college students had used Facebook and Uighur-language blogs to organise a protest demanding justice for Uighur workers who were killed by their Han colleagues at a toy factory in eastern China. Thousands of Uighurs took to the streets of Urumqi, waving Chinese flags and demanding that the government respond to the deaths of their comrades. When they were violently confronted by armed police, many of the Uighurs responded by turning over buses and beating Han bystanders. In the end, more than 190 people were reported killed, most of them Han. Over the weeks that followed, hundreds, perhaps thousands, of young Uighurs were disappeared by the police. The internet was shut off in the region for nearly 10 months, and Facebook and Twitter were blocked across the country.

Soon after the internet came back online in 2010 - with the notable absence of Facebook, Twitter and other non-Chinese social media applications - state security, higher education and private industry began to collaborate on breaking Uighur internet autonomy. Much of the Uighur-language internet was transformed from a virtual free society into a zone where government technology could learn to predict criminal behaviour. Broadly defined new anti-terrorism laws, first drafted in 2014, turned nearly all crimes committed by Uighurs, from stealing a Han neighbour's sheep to protesting against land seizures, into forms of terrorism. Religious piety, which the new laws referred to as "extremism", was conflated with religious violence.

The Xinjiang security industry mushroomed from a handful of private firms to approximately 1,400 companies employing tens of thousands of workers, ranging from low-level Uighur security guards to Han camera and telecommunications technicians to coders and designers. The Xi administration declared a state of emergency in the region, the people's war on terror began, and Islamophobia was institutionalised.

n 2017, after three years of operating a "hard strike" policy that turned Xinjiang into what many considered an open-air prison - which involved instituting a passbook system that restricted Uighurs' internal travel, and deploying hundreds of thousands of security forces to monitor the families of those who had been disappeared or killed by the state - the government turned to a fresh strategy. A new regional party secretary named Chen Quanguo introduced a policy of "transforming" Uighurs.

Local authorities began to describe the "three evil forces" of "religious extremism, ethnic separatism and violent terrorism" as three interrelated "ideological cancers". Because the digital sphere had allowed unauthorised forms of Islam to flourish, officials called for AI-enabled technology to crack down on these evils. Party leadership began to incentivise Chinese tech firms to develop technologies that could help the government control Uighur society. Billions of dollars in government contracts were awarded to build "smart" security systems across the Uighur region.

The turn toward "transformation" coincided with breakthroughs in the AI-assisted computer systems that the public security bureau rolled out in 2017 and brought together in the Ijop. The Chinese startup Meiya Pico began to market software to local and regional governments that was developed using state-supported research and could detect Uighur language text and Islamic symbols embedded in images. The company also developed programmes for automating the transcription and translation of Uighur voice messaging. The company Hikvision advertised tools that could automate the identification of Uighur faces based on physiological phenotypes. Other companies devised programmes that would perform automated searches of Uighurs' internet activity and then compare the data it gleaned to school, job, banking, medical and biometric records, looking for predictors of aberrant behaviour.

The rollout of this new technology required a great deal of manpower and technical training. More than 100,000 new police officers were hired. One of their jobs was to conduct the sort of "health check" Alim underwent, creating biometric records for almost every human being in the region. Face signatures were created by scanning individuals from a variety of different angles as they made different facial expressions; the result was a high-definition portfolio of personal emotions. All Uighurs were required to install nanny apps , which monitored everything they said, read and wrote, and everyone they connected with, on their smartphones.

A police officer checks the identity card of a man as security forces keep watch in a street in Kashgar. Photograph: Thomas Peter/Reuters

Higher-level police officers, most of whom were Han, were given the job of conducting qualitative assessments of the Muslim population as a whole - providing more complex, interview-based survey data for Ijop's deep-learning system. In face-to-face interviews, these neighbourhood police officers assessed the more than 14 million Muslim-minority people in Xinjiang and determined if they should be given the rating of "safe", "average", or "unsafe". They determined this by categorising the person using 10 or more categories, including whether or not the person was Uighur, whether they prayed regularly, had an immediate relative living abroad, or had taught their children about Islam in their home. Those who were determined to be "unsafe" were then sent to the detention centres, where they were interrogated and asked to confess their crimes and name others who were also "unsafe". In this manner, the officers determined which individuals should be slotted for the "transformation through education" internment camps.

Many Muslims who passed their first assessment were subsequently detained because someone else named them as "unsafe". In thousands of cases, years of WeChat history was used as evidence of the need for Uighur suspects to be "transformed". The state also assigned an additional 1.1 million Han and Uighur "big brothers and sisters" to conduct week-long assessments on Uighur families as uninvited guests in Uighur homes. Over the course of these stays, the relatives tested the "safe" qualities of those Uighurs who remained outside of the camp system by forcing them to participate in activities forbidden by certain forms of Islamic piety, such as drinking, smoking and dancing. They looked for any sign of resentment or any lack of enthusiasm in Chinese patriotic activities. They gave the children candy so that they would tell them the truth about what their parents thought.

All of this information was entered into databases and then fed back into the Ijop. The government's hope is that the Ijop will, over time, run with less and less human guidance. Even now, it is always running in the background of Uighur life, always learning.

n the tech community in the US, there is some scepticism regarding the viability of AI-assisted computer vision technology in China. Many experts I've spoken to from the AI policy world point to an article by the scholar Jathan Sadowski called " Potemkin AI", which highlights the failures of Chinese security technology to deliver what it promises. They frequently bring up the way a system in Shenzhen meant to identify the faces of jaywalkers and flash them on giant screens next to busy intersections cannot keep up with the faces of all the jaywalkers; as a result, human workers sometimes have to manually gather the data used for public shaming. They point out that Chinese tech firms and government agencies have hired hundreds of thousands of low-paid police officers to monitor internet traffic and watch banks of video monitors. As with the theatre of airport security rituals in the US, many of these experts argue that it is the threat of surveillance, rather than the surveillance itself, that causes people to modify their behaviour.

Yet while there is a good deal of evidence to support this scepticism, a notable rise in the automated detection of internet-based Islamic activity, which has resulted in the detention of hundreds of thousands of Uighurs, also points to the real effects of the implementation of AI-assisted surveillance and policing in Xinjiang. Even western experts at Google and elsewhere admit that Chinese tech companies now lead the world in these computer-vision technologies, due to the way the state funds Chinese companies to collect, use and report on the personal data of hundreds of millions of users across China.

The Han officials I spoke with during my fieldwork in Xinjiang often refused to acknowledge the way disappearances, frequent police shootings of young Uighur men, and state seizures of Uighur land might have motivated earlier periods of Uighur resistance. They did not see correlations between limits on Uighur religious education, restrictions on Uighur travel and widespread job discrimination on the one hand, and the rise in Uighur desires for freedom, justice and religiosity on the other. Because of the crackdown, Han officials have seen a profound diminishment of Islamic belief and political resistance in Uighur social life. They're proud of the fervour with which Uighurs are learning the "common language" of the country, abandoning Islamic holy days and embracing Han cultural values. From their perspective, the implementation of the new security systems has been a monumental success.

A middle-aged Uighur businessman from Hotan, whom I will call Dawut, told me that, behind the checkpoints, the new security system has hollowed out Uighur communities. The government officials, civil servants and tech workers who have come to build, implement and monitor the system don't seem to perceive Uighurs' humanity. The only kind of Uighur life that can be recognised by the state is the one that the computer sees. This makes Uighurs like Dawut feel as though their lives only matter as data - code on a screen, numbers in camps. They have adapted their behaviour, and slowly even their thoughts, to the system.

"Uighurs are alive, but their entire lives are behind walls," Dawut said softly. "It is like they are ghosts living in another world."
Some names have been changed. A longer version of this article first appeared in Logic, a new magazine about technology

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China's hi-tech war on its Muslim minority

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n mid-2017, Alim, a Uighur man in his 20s, returned to China from studying abroad. As soon as he landed back in the country, he was pulled off the plane by police officers. He was told his trip abroad meant that he was now under suspicion of being "unsafe".

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Human test subjects – Nazi Medical Experiments names: Kaiyu, Kylie, Lezanne

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Human test subjects – Nazi Medical Experiments names: Kaiyu, Kylie, Lezanne

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https://www.history.com/news/nazi-twin-experiments-mengele-eugenics

Summary:
Twin studies had helped scientists like Mengele’s mentor justify what they saw as necessary discrimination against people with “undesirable” genetic characteristics—Jews, Roma people, LGBTQ people, people with disabilities and others. Identical twins like the Mozes sisters were the perfect research subjects. Since they share a genome, scientists reasoned, any physical or behavioral differences in twins would be due to behavior, not genetics.

Pros:

Cons and limitations:
- Many innocent people weren't regarded as human beings --- they were merely treated as test subjects and had inhumane experiements conducted on them: scientists used one twin as a control and subjected the other to everything from blood transfusions to forced insemination, injections with diseases, amputations, and murder. Those that died were dissected and studied; their surviving twins were killed and subjected to the same scrutiny.

Possible controversial issues:
- under the Nazis, medical research supported a new vision for a "racially purified Europe" that excludes groups of people like the Jews. Hence, some racists would find these experiments to be ethical as they are going to make Europe "pure". Others may find it unethical as the experiments are inhuamane.

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"Twins! Twins!" Ten-year-old Eva Mozes clung to her mother amidst the chaos of the selection platform at Auschwitz-Birkenau. Before arriving at the death camp, she had been stuffed into a train car on a seemingly endless journey from Hungary. Now, she and her twin sister Miriam pressed close as Nazi guards shouted orders in German.

Suddenly, an SS guard stopped in front of the identical girls. "Are they twins?" he asked their mother.

"Is that good?" she replied.

He nodded, and Eva Mozes's life changed forever. The SS guard grabbed her and Miriam, whisking them away from their mother as they screamed and called her name. They never saw her again.

Eva and Miriam had just become subjects of a massive, inhumane medical experimentation program at Auschwitz-Birkenau-a program aimed solely at thousands of twins, many of them children.

Led by physician Josef Mengele, the program turned twins like Eva and Miriam into unwilling medical subjects in experiments that exposed about 3,000 children at Auschwitz-Birkenau to disease, disfigurement and torture under the guise of medical "research" into illness, human endurance and more.

Twins were separated from the other prisoners during the massive "selections" that took place at the camp's massive train platform, and whisked off to a laboratory to be examined. Mengele usually used one twin as a control and subjected the other to everything from blood transfusions to forced insemination, injections with diseases, amputations, and murder. Those that died were dissected and studied; their surviving twins were killed and subjected to the same scrutiny.

Twin studies had helped scientists like Mengele's mentor justify what they saw as necessary discrimination against people with "undesirable" genetic characteristics-Jews, Roma people, LGBTQ people, people with disabilities and others. But the twin experiments that had helped create the eugenics movement would, ironically, lead to the downfall of eugenics itself.

For eugenicists like Mengele, identical twins like the Mozes sisters were the perfect research subjects. Since they share a genome, scientists reasoned, any physical or behavioral differences in twins would be due to behavior, not genetics. Eugenicists held genetics responsible for undesirable characteristics and social conditions like criminality and poverty. They believed that selective breeding could be used to encourage socially acceptable behavior and wipe out undesirable tendencies.

By the time twin research began at Auschwitz-Birkenau in the 1940s, the use of twins in scientific experimentation was decades old. Though prior twin experiments had produced growing evidence that environment was as important as genetics, eugenics researchers clung to the idea that they could unlock new insights into nature and nurture through studying them.

One of them, Otmar von Verschuer, had significant power and influence in Nazi Germany. He authored texts that influenced Nazi policies toward Jews, Roma people and others, arguing that race had a biological basis and that "inferior" people could taint the Aryan race. An advocate for forced sterilization and selective breeding, von Verschuer collected genetic information on large numbers of twins, studying the statistics in an attempt to determine whether everything from disease to criminal behavior could be inherited. And he had a protege: a young physician named Josef Mengele.

Like his mentor, Mengele was vehemently racist and a devoted member of the Nazi Party. In 1943, he began working at Auschwitz-Birkenau as a medical officer. At first, Mengele was in charge of the Roma camp there, but in 1944 the entire remaining population of the camp was murdered in the gas chambers. Mengele was promoted to chief camp physician of the entire Birkenau camp, and became known for his brutal selections of incoming prisoners for the gas chambers.

Mengele wanted to continue the twin experiments he had begun with von Verschuer, and now he had a captive populace on which to do so. Though his earlier experiments had been legitimate, his work in Auschwitz-Birkenau was not. Abandoning medical ethics and research protocols, Mengele began conducting horrific experiments on up to 1,500 sets of twins, many of them children.

The "Mengele Twins" received nominal protection from some of the ravages of life at Auschwitz-Birkenau. They were not selected for the gas chambers, lived in separate quarters, and were given additional food and medical care. In exchange, though, they became the unwilling subjects of inhumane experiments at the hands of Mengele, who gained a reputation as the "Angel of Death" for his power, his mercurial temper and his cruelty.

For Eva, life as a Mengele twin meant sitting naked for hours and having her body repeatedly measured and compared to Miriam's. She withstood injections of an unknown substance that caused severe reactions. "As twins, I knew that we were unique because we were never permitted to interact with anybody in other parts of the camp," she later recalled. "But I didn't know I was being used in genetic experiments."

Eugenics itself was rooted in twin research. Frances Galton, a British scientist who coined the term "eugenics" in 1883, had used twin studies in his earliest eugenic research. Deeply influenced by his half-cousin Charles Darwin's book The Origin of Species, Galton became intrigued by how and whether humans passed along traits like intelligence, and preoccupied with the potential of breeding "desirable" genetic traits into humans.

For Galton and other eugenics researchers, twins held the key to understanding which characteristics were genetic and which ones were environmental. Using data collected via self-reported questionnaires, Galton studied dozens of pairs of twins to determine how they were similar and different. He concluded that similarities between twins were due to their genetics. "The one element that varies in different individuals, but is constant in each of them, is the natural tendency," he wrote. "It inevitably asserts itself."

Though Galton's twin research was biased and seriously flawed by modern standards, it helped lay the foundation for the eugenics movement. It also convinced other eugenicists that twins were the ideal way to study nature and nurture. But though eugenicists hypothesized that twins could help them create more perfect humans, the results of twin experiments kept confounding scientists. In the 1930s, for example, a group of American researchers who compared twins found a large variance in IQ in twins who had been raised apart but nonetheless shared similar personalities and behavioral traits.

Though twins were "the most favorable weapons" for the study of the "much-debated nature-nurture problem," they wrote, their conclusions suggested that the very qualities eugenicists thought they could encourage by monitoring marriage and eliminating individuals with "undesirable" traits from the gene pool didn't have to do with genetics at all.

The Nazis' defeat ended Mengele's experimentation on twins at Auschwitz. At the end of the war, the "Angel of Death" managed to escape prosecution. Shielded by Nazi sympathizers, he lived in South America until his death in Brazil in 1979.

In the aftermath of the war, scientists grappled with the aftermath of Nazi experimentation and the Holocaust's use of eugenic principles in the name of genocide. In 1946, a group of German physicians who had carried out euthanasia and conducted medical experimentation in Nazi death camps were tried at Nuremberg during a 140-day-long trial. The trial resulted in seven death sentences and the Nuremberg Code, a set of research ethics that has influenced modern concepts of informed consent and medical experimentation.

Only 200 of the 3,000 twins subjected to medical experiments at Auschwitz survived. Among them were Eva and Miriam. In the 1970s, Eva Mozes Kor began lecturing about her experiences and seeking out other survivors. Eventually, she and Miriam formed a nonprofit called Children of Auschwitz Nazi Deadly Lab Experiments Survivors (CANDLES) and tracked down more than 100 other twin survivors, documenting their experiences and the health ramifications of the often unknown experiments they had been subjected to at Auschwitz.

Most records of experimentation at Auschwitz were destroyed, but the lives of people like Eva Mozes Kor, who died in July 2019 at age 85, bear witness to the twin experiments' brutality. Ironically, the very type of experimentation Nazi physicians thought would uphold the pseudoscience they used to justify genocide ended up undermining the field of eugenics. In the face of unconvincing data revealed by twin studies and worldwide condemnation of Nazi medical experiments, scientists abandoned eugenics en masse and the field died out.

Today, the concept of twin studies has been challenged by research that demonstrates genetic variations even among identical twins. But twin studies are still used to learn more about age-related disease, eating disorders, sexual orientation and more, while a groundbreaking study of twin NASA astronauts is shedding new light on how microgravity affects the human body. But though twins remain invaluable to researchers today, twin studies are still a subject of debate among scientists eager to sidestep their hideous history.

Fact Check

We strive for accuracy and fairness. But if you see something that doesn't look right, click here to contact us! HISTORY reviews and updates its content regularly to ensure it is complete and accurate.

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Why the Nazis Were Obsessed With Twins | HISTORY

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Horrifying medical experiments on twins helped Nazis justify the Holocaust.

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Satellite Technologies in Emergency Response 

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Satellite Technologies in Emergency Response 

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https://www.psychologytoday.com/sg/blog/the-lucid-mind/202007/is-improving-cognitive-skills-nootropics-cheating?amp

Summary:
Nootropics are compounds and supplements that improve one's cognitive abilities.
However, many question the widespread nootropic use because they alter biology and give an unfair advantage to some over others. The playing field for academic performance is already uneven, some argue that it is logically inconsistent to say that the use of nootropics is unfair. With our increasing thirst for superhuman performance, it's unlikely that nootropics will disappear anytime soon, even if they're taken under the radar. While some see them as reckless, self-serving tools that defy biology, others see them as an opportunity to optimize our neural capacity and access new frontiers.

One solution that has been proposed is to ban all nootropics. Although perhaps sensible on paper, enforcing this kind of rule may be hard. Even if students were tested before sitting an exam, no one can guarantee them free of drug use. The practicality of enforcement is thus a big issue.

Although much research is lacking, many are now studying the substances to ensure the latter. After all, if taken correctly, they may just deepen the human experience—both in sentience, and in what we're able to bring into reality.

To what extent should the government regulate what is deem suitable for consumption?

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Athletes get penalized for using performance-enhancing drugs. But what about using nootropics while working towards exams-or when working in general? Is it ethical, and even healthy, to use them to improve cognitive skills?

What are Nootropics?

Nootropics are compounds and supplements that improve cognitive abilities. They get their name from Ancient Greek words: 'νόος' (pronounced 'nóos') and 'τροπή' (pronounced 'tropḗ'), and come in three forms. These are: stimulants, also known as 'smart drugs' (such as Ritalin and Adderall), synthetic compounds (like Noopept and racetams like piracetam), and natural compounds (such as caffeine, and herbal ginseng).

While many are thought to be safe for general use, like caffeine and ginseng, others, such as Ritalin ( methylphenidate) and Adderall (a combination of amphetamine and dextroamphetamine) are prescription drugs used to treat sleep disorders and ADHD.

Due to limited research on most nootropics, little is known on exactly what they do in the brain. While some are known to improve skills like attention, memory, and general processing, their exact results vary from person to person, depending on genetics, neurochemistry, general cognitive performance, and more.

Despite this, nootropics are popular for enhancing brain function. Research has shown that anywhere between 8% and 35% of college students admit to taking 'study drugs' to enhance their academic performance. Meanwhile, a study from Drugfree.org showed that almost a third of parents think that stimulants Ritalin and Adderall boost their children's academic performance, even if they don't have ADHD.

But is it ethical for people to use nootropics to improve their cognitive skills?

Are We Cheating Biology by Using Nootropics?

One of the leading arguments against widespread nootropic use is that they alter biology and give an unfair advantage to some over others. An example of this would be students using a drug that enhances their focus, attention, and memory from their baseline. These improvements could then lead them to perform better on tests than others who did not take the same drugs.

While this may happen, others say that using this example as evidence against the use of nootropics ignores underlying factors that already have a strong influence on cognitive performance. Although cognitive skills do play a role in academic performance, how they arise, i.e., by environmental and genetic factors, is also important to consider.

Studies conducted on animals show that iron deficiency while in the womb and early on in life disrupts myelination-the process of fat lining neural fibers to increase transmission between neurons. This then leads to iron deficiency anemia (IDA) in children, something that researchers speculate negatively affects cognitive processing. Thus, how much iron both mothers and infants have in their diets may influence cognitive processing.

But it doesn't stop with iron. The researchers behind Get Georgia Reading found that 'language nutrition' may also play a role in cognitive development. While babies from lower-income families reportedly tend to hear just 600 words per hour during their crucial developmental years, those from higher-income families tend to hear around 2,000 words per hour.

This precedes dramatic differences in vocabulary. By the time children reach 3 years old, according to Get Georgia Reading, those from high-income families have more than double the vocabulary of those from low-income families, on average. Those from lower-income groups also tend to fare worse on reading ability.

Until third grade in the U.S. (8-9 years old), a lot of classroom activity is focused on learning to read. From fourth grade (9-10 years old), however, students use reading to learn. Children with lower reading abilities thus tend to fall behind.

Regarding genetic factors, a study from 2003 suggested that among children from impoverished families, 60% of variance in IQ is likely accounted for by their shared environment. The study also noted that the genetic contribution to IQ differences among those children may be close to zero. Meanwhile, the opposite was found for children from more affluent families.

Given that poverty-related adversity and stress early on life may hinder brain development and cognitive ability, it could be said that stress from poorer backgrounds might prevent people from reaching their intellectual potential, as encoded by their genes.

Thus, as the playing field for academic performance is already uneven, some argue that it is logically inconsistent to say that the use of nootropics is unfair. After all, many seem happy to look the other way when it comes to benefits like one-to-one tutoring that are usually only afforded to the wealthier.

If anything, it is arguably more ethical to provide nootropics to lower-performing individuals to make up for their deficits. This comes especially as some studies have found that low performers may be the only ones to truly benefit from the drugs. One study, for example, suggests that although Adderall may improve cognitive abilities like word recall and abstract reasoning in low performers, it may impair those already performing highly.

Could Widespread Nootropic Use Cause Peer Pressure?

The potential for peer pressure is another ethical hurdle when looking at general nootropic use. The argument goes that should nootropics really improve cognitive skills; many may feel pressured to use them just to keep up.

Whether or not this really is a problem though remains to be seen. A good example to the contrary can be found when looking at a naturally occurring nootropic, caffeine. Known to reduce fatigue and promote alertness, it is unlikely that the nootropic is necessary for academic success or that people feel coerced into consuming it.

Others say, however, that indirect coercion may exist-especially with 'smart drugs'. Students at colleges with more competitive criteria, for example, were found to use Ritalin at over two times the rate compared to those in less competitive colleges.

A survey of 4,580 college students indicates that 65% use nootropics to concentrate better and 60% use them to study better. Curiously, 31% of students also reportedly use them to experience a 'high', and 10% to lose weight.

Ethical Lines are Blurred Between Process-Oriented and Goal-Oriented Human Activity

Another way to tackle this ethical dilemma is by considering different types of human activity. One is process-oriented. This is about how something happens, i.e., an athlete should run a race and win by being the fastest runner, rather than just being the 'fastest'-something they could do by driving a monster truck across the finish line-or by taking performance-enhancing drugs. Likewise, in the case of students, it could mean acing their exams thanks to their own efforts instead of paying a more studious look-alike to take their place-or taking cognitive-enhancing drugs.

Goal-oriented human activity, on the other hand, focuses more on the output than the process. A good example of this is The Beatles using the now-scheduled drug LSD to write legendary songs like "Lucy in the Sky with Diamonds" and "She Said, She Said." In the case of a student taking an exam, it would mean commending them for fantastic grades, regardless of whether they actually learned anything or hired a look-alike for the exam room.

But what happens in cases that have blurred lines-that are neither purely goal-oriented nor process-oriented? What happens if, for a student, the purpose of attending school is not necessarily to learn, but to pass exams, although learning is a part of passing?

This is when it gets a bit fuzzy, and where a libertarian extreme-or its polar opposite-may become relevant.

In this case, perhaps it makes sense to either make nootropics available-or banned-to all. Either way, equal access (or lack thereof) is guaranteed.

Both scenarios, though, have drawbacks.

What Happens if We Make All Nootropics Legal for Everybody?

As for making all nootropics available for everybody, what about danger? In the world of sport, the World Anti-Doping Agency (WADA) uses one principle criterion for drug prohibition: whether it poses an actual or potential threat to the athlete's health. A good example of this is the use of anabolic steroids. Although they may work wonders in the short term, chronic use can lead to hepatic disease and fatal cardiovascular problems.

The rule does mean, though, that safer drugs are let off the hook. Caffeine, for example, although known to increase performance in a range of sports, from swimming to cycling and running, is permitted.

Unfortunately, though, restricting nootropics based on whether or not they are harmful is not that simple. Most nootropics are extremely understudied, meaning we are not really sure which are harmless to whom and in which circumstances.

Ritalin is a good example of this. Although it may enhance certain cognitive functions in adults, research suggests that the juvenile brain is hypersensitive to it. This means that a low, clinically relevant dose of the drug may lead to excess dopamine and norepinephrine in the juvenile brain and impair executive functioning and working memory.

Beyond this, it seems that nootropics tend to benefit different people in different ways. The effects of Modafinil, for example, are thought to be dependent on which SNP (Single Nucleotide Polymorphism) rs4680 you have. It's linked to the production of an enzyme that metabolizes dopamine in the prefrontal cortex, and while those with the GG variation reportedly tend to respond well to Modafinil, those with AG have a medium response. Meanwhile, people with the AA version experience relatively little while on the drug.

What if We Ban All Nootropics?

So what about banning all nootropics?

At Duke University, the use of prescription drugs without a prescription is banned. This includes nootropics like Adderall, Ritalin, and Modafinil. And it may make sense: After all, these drugs can cause negative side effects like nervousness, dizziness, and trouble sleeping. Because of this, even self-improvement guru Tim Ferriss recommends against them in favor of more natural alternatives.

Meanwhile, natural nootropics like caffeine, or other nootropics thought to have cognitive-enhancing effects, like cocoa powder, L-Theanine (found in tea), and turmeric, are still allowed in the university.

Although perhaps sensible on paper, enforcing this kind of rule may be hard. Even if students were tested before sitting an exam, who is to say that they wouldn't have used these stimulants throughout the semester to study, or in any training process? Would it then be necessary to make students take drug tests several times per semester? The practicality of enforcement is thus a big issue.

"It's almost impossible to draw the line that defines what is and isn't cheating... How would you enforce it? Is a student using neurofeedback cheating? Are nootropics cheating? Coffee? Or is it only cheating if they use prescription drugs?" says Nita Farahany, a bioethicist at Duke University.

With our increasing thirst for superhuman performance, it's unlikely that nootropics will disappear anytime soon, even if they're taken under the radar. While some see them as reckless, self-serving tools that defy biology, others see them as an opportunity to optimize our neural capacity and access new frontiers. Although much research is lacking, many are now studying the substances to ensure the latter. After all, if taken correctly, they may just deepen the human experience-both in sentience, and in what we're able to bring into reality.

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Is Improving Cognitive Skills With Nootropics Cheating?

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Athletes get penalized for using performance-enhancing drugs. But what about using nootropics while working towards exams-or when working in general? Is it ethical, and even healthy, to use them to improve cognitive skills? Nootropics are compounds and supplements that improve cognitive abilities.

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Chips monitoring Chinese Students (ABC, 2018)

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Chips monitoring Chinese Students (ABC, 2018)

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Summary:
Chinese schools have begun enforcing "smart uniforms" embedded with computer chips to monitor student movements and prevent them from skipping classes. Eleven schools in the south-west province of Guizhou have introduced the uniforms, which were developed by local tech firm Guizhou Guanyu Technology. As students enter the school, the time and date is recorded along with a short video that parents can access via a mobile app. Facial recognition further ensures that each uniform is worn by its rightful owner to prevent students from cheating the system.

Key points:

Skipping class or leaving the classroom without permission triggers an alarm

GPS system can track student movements even beyond the school grounds

Beijing has made regular calls on all schools to develop "smart campuses"

Pros:

Cons & Limitations:

Possible Controversial issues:

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Chinese schools have begun enforcing "smart uniforms" embedded with computer chips to monitor student movements and prevent them from skipping classes.

Skipping class or leaving the classroom without permission triggers an alarm

A GPS system tracks student movements even beyond the school grounds

Beijing has made regular calls on all schools to develop "smart campuses"

Eleven schools in the south-west province of Guizhou have introduced the uniforms, which were developed by local tech firm Guizhou Guanyu Technology.

As students enter the school, the time and date is recorded along with a short video that parents can access via a mobile app.

Facial recognition further ensures that each uniform is worn by its rightful owner to prevent students from cheating the system.

Skipping classes triggers an alarm to inform teachers and parents of the truancy, while an automatic voice alarm activates if a student walks out of school without permission.

A GPS system tracks student movements even beyond the school grounds.

The two chips - inserted into each uniform's shoulders - can withstand up to 500 washes and 150 degrees Celsius, the company told state media Global Times.

Alarms will also sound if a student falls asleep in class, while parents can monitor purchases their child makes at the school and set spending limits via a mobile app, according to the company's official website.

The company released a public statement via popular Chinese social media site Weibo saying the uniforms "focus on safety issues", and provide a "smart management method" that benefits students, teachers and parents.

Guanyu Technology's marketing manager also bragged of the uniforms' capabilities on a personal Weibo account.

"You go to any school and ask the security guard how many students there are in the school today. He definitely can't give you an answer, but we can," the post read.

On its website, the development company said the uniforms were designed to "fully implement the state policy of actively constructing smart campuses and smart education management for the development of education".

In recent years, Beijing has made regular calls on all schools to develop "smart campuses" in a push to digitalise education.

'Don't children have human rights and privacy?'

A GPS system tracks students' movements even beyond the school grounds.(Supplied: Guanyun Technology )

Despite all the benefits touted by the company, the uniforms have prompted backlash on social media.

"If you were a child, would you like to be monitored 24 hours a day?" asked one Weibo user with the nickname Sangguo_Sunny.

"Don't children have human rights and privacy?" user Dawson-HO said.

But blogger Yi Zhi Sirius defended the new uniforms, saying "the uniforms will come in handy when it comes to locating missing students".

Guanyu Technology's marketing manager also bragged of the uniforms' capabilities on a personal Weibo account.(Supplied: Guanyu Technology )

Speaking to the Global Times, Lin Zongwu, principal of Number 11 School of Renhuai in Guizhou, said although the school had the ability to track students at all times, they used this technology sparingly.

"We choose not to check the accurate location of students after school, but when the student is missing and skipping classes, the uniforms help locate them," Mr Lin said, adding the attendance rate had increased since the intelligent uniforms were introduced.

Guanyu Technology responded to criticism on Weibo, saying the company did "respect and protect human rights".

"The smart uniform does not track students' every single move all the time," the company wrote.

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Chinese schools enforce 'smart uniforms' with GPS tracking system to monitor students

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Chinese schools have begun enforcing "smart uniforms" embedded with computer chips to monitor student movements and prevent them from skipping classes. Skipping class or leaving the classroom without permission triggers an alarm A GPS system tracks student movements even beyond the school grounds Beijing has made regular calls on all schools to develop "smart campuses" Eleven schools in the south-west province of Guizhou have introduced the uniforms, which were developed by local tech firm Guizhou Guanyu Technology.

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China’s Social Credit System (South China Morning Post, 2020)

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China’s Social Credit System (South China Morning Post, 2020)

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Merits for the Chinese government to implement this policy/system:
- To set and direct ("police"?) moral conduct/behaviour of society
- To transform / "control" social behaviour (especially for rural villages or even the cities- depending on how one sees it. For rural villages, the need for improvements as it is still relatively backward and slow whereas for cities, need to impose greater social control with possibly increased calls for freedom and independence/autonomy from the state. )
- Social accountability (everyone's behaviour/actions or the lack thereof impacts on another)

Possible criticisms of this system:
- Based system (people/ the information collectors may not make fair/ subjective judgments)- may lead to nepotism or bribery
- Also consider: Would technology definitely/necessarily do a better job?
- People's good behaviour to earn credits is not genuine: other motivations (selfish/ self-interests at hand) as they benefit as well.
- may not be fair to expect everyone, especially the elderly (seen in the example: 80 years old still has to provide labour) to contribute to this social credit system.

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national development and reform commission (ndrc)

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how does china’s social credit system work?

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why has china set up a social credit system?

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what is the progress of china’s social credit system

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why is china’s social credit system controversial?

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What is China's social credit system and why is it controversial?

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China's social credit system is a set of databases and initiatives that monitor and assess the trustworthiness of individuals, companies and government entities.

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Why Algorithms can be Racist and Sexist (Vox, 2020)

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Why Algorithms can be Racist and Sexist (Vox, 2020)

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Summary:
Algorithmic bias can be seen in two primary ways: accuracy and impact. An AI can have different accuracy rates for different demographic groups. Similarly, an algorithm can make vastly different decisions when applied to different populations.

Importantly, when you think of data, you might think of formal studies in which demographics and representation are carefully considered, limitations are weighed, and then the results are peer-reviewed. That’s not necessarily the case with the AI-based systems that might be used to make a decision about you. Let’s take one source of data everyone has access to: the internet. One study found that, by teaching an artificial intelligence to crawl through the internet — and just reading what humans have already written — the system would produce prejudices against black people and women. Another example of how training data can produce sexism in an algorithm occurred a few years ago, when Amazon tried to use AI to build a résumé-screening tool. According to Reuters, the company’s hope was that technology could make the process of sorting through job applications more efficient. It built a screening algorithm using résumés the company had collected for a decade, but those résumés tended to come from men. That meant the system, in the end, learned to discriminate against women. It also ended up factoring in proxies for gender, like whether an applicant went to a women’s college. (Amazon says the tool was never used and that it was nonfunctional for several reasons.)

*Food for thought: Given that it is known that there is bias in algorithms, why do we (instituitions, companies, governments etc.) still continue to use (and rely on) them?

Just because a technology is accurate doesn’t make it fair or ethical. For instance, the Chinese government has used artificial intelligence to track and racially profile its largely Muslim Uighur minority, about 1 million of whom are believed to be living in internment camps.

Relevant controversial issues:

Also consider Intersectionality  (intersecting and overlapping social identities- which could prove to be empowering for some, yet oppressing for others)

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This story is part of a group of stories called

Uncovering and explaining how our digital world is changing - and changing us.

Humans are error-prone and biased, but that doesn't mean that algorithms are necessarily better. Still, the tech is already making important decisions about your life and potentially ruling over which political advertisements you see, how your application to your dream job is screened, how police officers are deployed in your neighborhood, and even predicting your home's risk of fire.

But these systems can be biased based on who builds them, how they're developed, and how they're ultimately used. This is commonly known as algorithmic bias. It's tough to figure out exactly how systems might be susceptible to algorithmic bias, especially since this technology often operates in a corporate black box. We frequently don't know how a particular artificial intelligence or algorithm was designed, what data helped build it, or how it works.

Typically, you only know the end result: how it has affected you, if you're even aware that AI or an algorithm was used in the first place. Did you get the job? Did you see that Donald Trump ad on your Facebook timeline? Did a facial recognition system identify you? That makes addressing the biases of artificial intelligence tricky, but even more important to understand.

Machine learning-based systems are trained on data. Lots of it.

When thinking about "machine learning" tools (machine learning is a type of artificial intelligence), it's better to think about the idea of "training." This involves exposing a computer to a bunch of data - any kind of data - and then that computer learns to make judgments, or predictions, about the information it processes based on the patterns it notices.

For instance, in a verysimplified example, let's say you wanted to train your computer system to recognize whether an object is a book, based on a few factors, like its texture, weight, and dimensions. A human might be able to do this, but a computer could do it more quickly.

To train the system, you show the computer metrics attributed to a lot of different objects. You give the computer system the metrics for every object, and tell the computer when the objects are books and when they're not. After continuously testing and refining, the system is supposed to learn what indicates a book and, hopefully, be able to predict in the future whether an object is a book, depending on those metrics, without human assistance.

That sounds relatively straightforward. And it might be, if your first batch of data was classified correctly and included a good range of metrics featuring lots of different types of books. However, these systems are often applied to situations that have much more serious consequences than this task, and in scenarios where there isn't necessarily an "objective" answer. Often, the data on which many of these decision-making systems are trained or checked are often not complete, balanced, or selected appropriately, and that can be a major source of - although certainly not the only source - of algorithmic bias.

Nicol Turner-Lee, a Center for Technology Innovation fellow at the Brookings Institution think tank, explains that we can think about algorithmic bias in two primary ways: accuracy and impact. An AI can have different accuracy rates for different demographic groups. Similarly, an algorithm can make vastly different decisions when applied to different populations.

Importantly, when you think of data, you might think of formal studies in which demographics and representation are carefully considered, limitations are weighed, and then the results are peer-reviewed. That's not necessarily the case with the AI-based systems that might be used to make a decision about you. Let's take one source of data everyone has access to: the internet. One study found that, by teaching an artificial intelligence to crawl through the internet - and just reading what humans have already written - the system would produce prejudices against black people and women.

Another example of how training data can produce sexism in an algorithm occurred a few years ago, when Amazon tried to use AI to build a résumé-screening tool. According to Reuters, the company's hope was that technology could make the process of sorting through job applications more efficient. It built a screening algorithm using résumés the company had collected for a decade, but those résumés tended to come from men. That meant the system, in the end, learned to discriminate against women. It also ended up factoring in proxies for gender, like whether an applicant went to a women's college. (Amazon says the tool was never used and that it was nonfunctional for several reasons.)

Amid discussions of algorithmic biases, companies using AI might say they're taking precautions, taking steps to use more representative training data and regularly auditing their systems for unintended bias and disparate impact against certain groups. But Lily Hu, a doctoral candidate at Harvard in applied mathematics and philosophy who studies AI fairness, says those aren't assurances that your system will perform fairly in the future.

"You don't have any guarantees because your algorithm performs 'fairly' on your old dataset," Hu told Recode. "That's just a fundamental problem of machine learning. Machine learning works on old data [and] on training data. And it doesn't work on new data, because we haven't collected that data yet."

Still, shouldn't we just make more representative datasets? That might be part of the solution, though it's worth noting that not all efforts aimed at building better data sets are ethical. And it's not just about the data. As Karen Hao of the MIT Tech Review explains, AI could also be designed to frame a problem in a fundamentally problematic way. For instance, an algorithm designed to determine "creditworthiness" that's programmed to maximize profit could ultimately decide to give out predatory, subprime loans.

Here's another thing to keep in mind: Just because a tool is tested for bias - which assumes that engineers who are checking for bias actually understand how bias manifests and operates - against one group doesn't mean it is tested for bias against another type of group. This is also true when an algorithm is considering several types of identity factors at the same time: A tool may deemed fairly accurate on white women, for instance, but that doesn't necessarily mean it works with black women.

In some cases, it might be impossible to find training data free of bias. Take historical data produced by the United States criminal justice system. It's hard to imagine that data produced by an institution rife with systemic racism could be used to build out an effective and fair tool. As researchers at New York University and the AI Now Institute outline, predictive policing tools can be fed "dirty data," including policing patterns that reflect police departments' conscious and implicit biases, as well as police corruption.

The foundational assumptions of engineers can also be biased

So you might have the data to build an algorithm. But who designs it, and who decides how it's deployed? Who gets to decide what level of accuracy and inaccuracy for different groups is acceptable? Who gets to decide which applications of AI are ethical and which aren't?

While there isn't a wide range of studies on the demographics of the artificial intelligence field, we do know that AI tends to be dominated by men. And the "high tech" sector, more broadly, tends to overrepresent white people and underrepresent black and Latinx people, according to the Equal Employment Opportunity Commission.

Turner-Lee emphasizes that we need to think about who gets a seat at the table when these systems are proposed, since those people ultimately shape the discussion about ethical deployments of their technology.

But there's also a broader question of what questions artificial intelligence can help us answer. Hu, the Harvard researcher, argues that for many systems, the question of building a "fair" system is essentially nonsensical, because those systems try to answer social questions that don't necessarily have an objective answer. For instance, Hu says algorithms that claim to predict a person's recidivism don't ultimately address the ethical question of whether someone deserves parole.

"There's not an objective way to answer that question," Hu says. "When you then insert an AI system, an algorithmic system, [or] a computer, that doesn't change the fundamental context of the problem, which is that the problem has no objective answer. It's fundamentally a question of what our values are, and what the purpose of the criminal justice system is."

That in mind, some algorithms probably shouldn't exist, or at least they shouldn't come with such a high risk of abuse. Just because a technology is accurate doesn't make it fair or ethical. For instance, the Chinese government has used artificial intelligence to track and racially profile its largely Muslim Uighur minority, about 1 million of whom are believed to be living in internment camps.

Transparency is a first step for accountability

One of the reasons algorithmic bias can seem so opaque is because, on our own, we usually can't tell when it's happening (or if an algorithm is even in the mix). That was one of the reasons why the controversy over a husband and wife who both applied for an Apple Card - and got widely different credit limits - attracted so much attention, Turner-Lee says. It was a rare instance in which two people, who at least appeared to be exposed to the same algorithm and could easily compare notes. The details of this case still aren't clear, though the company's credit card is now being investigated by regulators.

But consumers being able to make apples-to-apples comparisons of algorithmic results are rare, and that's part of why advocates are demanding more transparency about how systems work and their accuracy. Ultimately, it's probably not a problem we can solve on the individual level. Even if we do understand that algorithms can be biased, that doesn't mean companies will be forthright in allowing outsiders to study their artificial intelligence. That's created a challenge for those pushing for more equitable, technological systems. How can you critique an algorithm - a sort of black box - if you don't have true access to its inner workings or the capacity to test a good number of its decisions?

Companies will claim to be accurate, overall, but won't always reveal their training data (remember, that's the data that the artificial intelligence trains on before evaluating newdata, like, say, your job application). Many don't appear to be subjecting themselves to audit by a third-party evaluator or publicly sharing how their systems fare when applied to different demographic groups. Some researchers, such as Joy Buolamwini and Timnit Gebru, say that sharing this demographic information about both the data used to train and the data used to check artificial intelligence should be a baseline definition of transparency.

Artificial intelligence is new, but that doesn't mean existing laws don't apply

We will likely need new laws to regulate artificial intelligence, and some lawmakers are catching up on the issue. There's a bill that would force companies to check their AI systems for bias through the Federal Trade Commission (FTC). And legislation has also been proposed to regulate facial recognition, and even to ban the technology from federally assisted public housing.

But Turner-Lee emphasizes that new legislation doesn't mean existing laws or agencies don't have the power to look over these tools, even if there's some uncertainty. For instance, the FTC oversees deceptive acts and practices, which could give the agency authority over some AI-based tools.

The Equal Employment Opportunity Commission, which investigates employment discrimination, is reportedly looking into at least two cases involving algorithmic discrimination. At the same time, the White House is encouraging federal agencies that are figuring out how to regulate artificial intelligence to keep technological innovation in mind. That raises the challenge of whether the government is prepared to study and govern this technology, and figure out how existing laws apply.

"You have a group of people that really understand it very well, and that would be technologists," Turner-Lee cautions, "and a group of people who don't really understand it at all, or have minimal understanding, and that would be policymakers."
Open Sourced is made possible by Omidyar Network. All Open Sourced content is editorially independent and produced by our journalists.
That's not to say there aren't technical efforts to "de-bias" flawed artificial intelligence, but it's important to keep in mind that the technology won't be a solution to fundamental challenges of fairness and discrimination. And, as the examples we've gone through indicate, there's no guarantee companies building or using this tech will make sure it's not discriminatory, especially without a legal mandate to do so. It would seem it's up to us, collectively, to push the government to rein in the tech and to make sure it helps us more than it might already be harming us.

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Uncovering and explaining how our digital world is changing - and changing us. Humans are error-prone and biased, but that doesn't mean that algorithms are necessarily better. Still, the tech is already making important decisions about your life and potentially ruling over which political advertisements you see, how your application to your dream job is screened, how police officers are deployed in your neighborhood, and even predicting your home's risk of fire.

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Assisted Reproductive Technologies (e.g. In-vitro fertilisation, gestational surrogacy)- Rae YAP and VIVIAN

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Assisted Reproductive Technologies (e.g. In-vitro fertilisation, gestational surrogacy)- Rae YAP and VIVIAN

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Summary:
Would-be parents who are at risk of passing on serious inheritable diseases to their offspring can now choose from more service providers offering genetic screening. The clinic is not allowed to include information about the sex of the embryo or any other genetic traits that are not related to the inheritable condition.

For example, a designer baby is a baby genetically engineered in vitro for specially selected traits, which can vary from lowered disease-risk to gender selection. Designer babies have become an important topic in bioethical debates, and represent an area within embryology that has not yet become a practical reality, but draws out ethical concerns about whether or not it will become necessary to implement limitations regarding designer babies in the future.

Ethical controversies/perspectives:
In vitro fertilization (IVF) is morally objectionable for a number of reasons: the destruction of human embryos, the danger to women and newborn infants, and the replacement of the marital act in procreation. Those who are religious may also believe that conception should be granted by God only.

Possible solutions:
IVF clinics should have regulatory measures to ensure that as much of the conception process is as natural as possible, for example, keeping the gender something the parents cannot choose.

Possible essay qn:
Should the government regulate Assisted Reproductive technologies for those with fertility issues?

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MOH approves genetic testing of IVF embryos as mainstream clinical service

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Would-be parents at risk of passing on serious diseases to their offspring can now choose from more service providers. Read more at straitstimes.com.

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Chinese schools introduce chip-embedded uniforms to track students entering or exiting campus

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Biometric Registration of Rohingya Refugees (gladys and kaitlyn)

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Biometric Registration of Rohingya Refugees (gladys and kaitlyn)

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https://www.hrw.org/news/2021/06/15/un-shared-rohingya-data-without-informed-consent

Summary: Since 2016, more than 800000 Rohingya refugees were expelled or fled due to crimes against humanity and acts of genocide across the border to Bangladesh.
The UNHCR collected and shared personal information from the refugees with Bangladesh, which shared it with Myanmar to verify people for possible repatriation.

Bangladesh’s submission of lists to Myanmar may also have put refugees, (who agreed to return), on track toreceive Myanmar’s National Verification Cards (NVCs) which many believe it undermines their claims to Myanmar citizenship.

key points :
- unfair treatment towards refugees, especially in their vulnerable state where they cannot voice out
- goes against UNHCR’s policy on protecting personal data
- May potentially put returning refugees at greater risk for discrimination in Myanmar

pros :
For many of these refugees, it is the first time they have an identity card. The biometric, fraud-proof cards are being issued jointly by Bangladeshi authorities and UNHCR to all verified refugees over the age of 12. Accurate data will help agencies in their programme planning and be able to target assistance where it is needed most, particularly for people with specific needs, such as women and children taking care of their families and people with disabilities.

cons :
With little meaningful power or representation, refugees have time and again been shut out of decisions as to how biometrics should be rolled out, what data gets shared with whom, what the risks are, and how they should best be mitigated, During registration processes, even the basic step of explaining what is going on does not appear to be a priority, let alone a wider consultative process.

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UN Shared Rohingya Data Without Informed Consent

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The United Nations refugee agency improperly collected and shared personal information from ethnic Rohingya refugees with Bangladesh, which shared it with Myanmar to verify people for possible repatriation.

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Clinical Trials for Vaccine Development 

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Clinical Trials for Vaccine Development 

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Electronic monitoring bracelets (The Conversation, 2019)

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Electronic monitoring bracelets (The Conversation, 2019)

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Summary:
The rise of electronic monitoring- here it is used in the corrections systems and it refers to the tagging of a person as a form of surveillance, usually in the form of a GPS-enabled ankle bracelet. When an offender is subject to electronic monitoring, a computer database is updated with information about the rules he or she has been instructed to follow. Each jurisdiction and each agency may have their own database, so where the offender appears in the database will depend on who is supervising the electronic monitoring order. The database is then monitored by enforcement authorities, although this is sometimes outsourced to private providers or overseas companies. While the data is generally sent from the offender’s GPS device to the monitoring agency in real time, there can be delays in how long it takes for that information to be passed to police or corrective services.

Pros:

Cons & Limitations:

Possible Controversial Issues:

Consider other possible contexts where such electronic monitoring could be employed and the possible controversies/tensions such use could pose:

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The man arrested after a deadly gun attack in Darwin Tuesday night is reported to have been on parole and wearing an electronic monitoring bracelet.

This leads to the same reaction we see following any high-profile crime. How could such a thing happen?

People may speculate that the criminal justice agencies involved have somehow dropped the ball. The offender was on their radar, after all.

Read more: Online tools can help people in disasters, but do they represent everyone?

While this finger-pointing may serve a cathartic function, it is important we also question our expectations before assuming a failure occurred.

We need to understand what electronic monitoring intends to achieve, how it works, and what are its capabilities and limitations.

Electronic tagging

In the context of the corrections system, electronic monitoring refers to the tagging of a person as a form of surveillance, usually in the form of a GPS-enabled ankle bracelet.

In Australia, each state and territory uses electronic monitoring differently, guided by their own legislative frameworks.

Practices vary considerably between jurisdictions. For example, in some places, certain offenders are targeted (high-risk recidivists, those who repeatedly reoffend, for example). In others, specific types of offences are the focus (such as child sex offences).

The application of electronic monitoring even differs between offenders, as the supervising agency uses it for reasons specific to each person.

A police department might use electronic monitoring to ensure a domestic violence perpetrator does not visit the victim before a trial. A probation officer might require an offender to wear a bracelet for 12 months to ensure they are attending treatment and meeting their curfew. A parole officer could place the GPS tracking condition on an offender for the first three months following release from prison to better understand how the parolee spends his or her time.

Each of these experiences will be quite different, as each is intended to fulfil a unique aim.

Ordinarily, electronic monitoring is used as a tool of incapacitation and deterrence.

In the first instance, an offender may be told to follow a particular rule - for example, to be home by 8pm, to stay away from the victim, to attend a treatment program, or not to go within 1km of a school. Electronic monitoring allows authorities to monitor the person's compliance with such a condition.

In the latter instance, an offender may be deterred from certain behaviour if they believe their actions are likely to be detected through electronic monitoring.

Monitoring actions

When an offender is subject to electronic monitoring, a computer database is updated with information about the rules he or she has been instructed to follow. Each jurisdiction and each agency may have their own database, so where the offender appears in the database will depend on who is supervising the electronic monitoring order.

The database is then monitored by enforcement authorities, although this is sometimes outsourced to private providers or overseas companies. While the data is generally sent from the offender's GPS device to the monitoring agency in real time, there can be delays in how long it takes for that information to be passed to police or corrective services.

What occurs when an offender breaches one of the rules and a computer alert is generated depends on factors such as legislation and the priority of a case influencing the response. The database includes information about what to do in the event of specific kinds of breaches with specific offenders.

In some cases, an alarm on the device may go off or, very rarely, the police may be immediately notified.

Most often, for routine cases and ordinary breaches, the monitoring agency will notify the offender's supervisor (such as a parole officer or a local police department), who will then determine how to proceed.

There may be a lag of several days during this process. For example, if a low-risk offender misses their home curfew on Friday night (as determined by the GPS bracelet), the parole officer will not receive notification of this breach until Monday morning.

The pros and cons of tagging

There are a range of benefits and disadvantages to the electronic monitoring of offenders.

It can be effective in holding offenders accountable, protecting victims and enhancing community safety and preventing crimes. These come with important cost savings, particularly when offenders can be safety monitored in the community in lieu of imprisonment or as a mechanism of early release from prison.

But some of the downfalls are that offenders can tamper with their devices, and there can be GPS dead zones - particularly in a geographically vast country such as Australia. There may also be human error in using the systems, such as improper monitoring or unreasonable decision-making after an alert.

Yet collectively, the research evidence highlights that electronic monitoring can be an effective tool for discouraging recidivism. But it is only that: a tool.

The most effective practices for supervising offenders in the community include those that identify and reduce a person's risks for continued criminal behaviour.

Read more: AI can help in crime prevention, but we still need a human in charge

Electronic monitoring will be most effective when it is used to support supervision that limits a person's access to chances to commit crime. Such supervision should help them redesign their routines so that any risky settings are avoided and are replaced with more positive influences.

Thus, rather than simply giving offenders a long list of rules for what not to do, effective probation and parole strategies help offenders lead productive lives.

More broadly, it is imperative that correctional authorities provide rehabilitative interventions that address the underlying factors that contribute toward a person's criminal behaviour. The most effective approaches use cognitive-behavioural techniques to give offenders skills that encourage good decision-making.

Yet electronic monitoring cannot "fix" an offender's impulsivity, lack of empathy, or any other underlying crime-conducive traits. Thus we should not confuse a technological aid with meaningful treatment.

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Electronic monitoring bracelets are only crime deterrence tools, they can't 'fix' offenders

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The man arrested after a deadly gun attack in Darwin Tuesday night is reported to have been on parole and wearing an electronic monitoring bracelet. This leads to the same reaction we see following any high-profile crime. How could such a thing happen? People may speculate that the criminal justice agencies involved have somehow dropped the ball.

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The complicated truth about China's social credit system (wired.co.uk, 2019)

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The complicated truth about China's social credit system (wired.co.uk, 2019)

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China's social credit system has been compared to Black Mirror, Big Brother and every other dystopian future sci-fi writers can think up. The reality is more complicated - and in some ways, worse.

The idea for social credit came about back in 2007, with projects announced by the government as an opt-in system in 2014. But there's a difference between the official government system and private, corporate versions, though the latter's scoring system that includes shopping habits and friendships is often conflated with the former.

Brits are well accustomed to credit checks: data brokers such as Experian trace the timely manner in which we pay our debts, giving us a score that's used by lenders and mortgage providers. We also have social-style scores, and anyone who has shopped online with eBay has a rating on shipping times and communication, while Uber drivers and passengers both rate each other; if your score falls too far, you're out of luck.

China's social credit system expands that idea to all aspects of life, judging citizens' behaviour and trustworthiness. Caught jaywalking, don't pay a court bill, play your music too loud on the train - you could lose certain rights, such as booking a flight or train ticket. "The idea itself is not a Chinese phenomenon," says Mareike Ohlberg, research associate at the Mercator Institute for China Studies. Nor is the use, and abuse, of aggregated data for analysis of behaviour. "But if [the Chinese system] does come together as envisioned, it would still be something very unique," she says. "It's both unique and part of a global trend."

What is China's social credit system?

Unveiled in a 2014 plan, pieces of the system are already in place, and the Chinese government appears to be targeting a 2020 goal to get the rest in place, though that's less a deadline and instead marks the end of a planning period, says Samantha Hoffman, non-resident fellow at the Australian Strategic Policy Institute.

As yet, there's no one social credit system. Instead, local governments have their own social record systems that work differently, while unofficial private versions are operated at companies such Ant Financial's Zhima Credit, better known as Sesame Credit. Ant Financial is the payment firm spun out of Alibaba. The systems use shopping habits among other data to inform credit-style scores, on an opt-in basis. "There is no single, nationally coordinated system," Ohlberg says. And the pilots that do exist don't all work in the same way.

The private systems, including Ant Financial's Sesame Credit, often get conflated with the government plans, though they aren't part of the official system. To be a bit more confusing, the data collected by private companies is expected to be hoovered up by the government in the future, and some of the data is already used in government trials. Sesame Credit says this is only with user consent.

That leads to misunderstanding of what the social credit system actually is, notes Ohlberg. "What happened is some of the media took the private pilots, like Sesame Credit... and presented it as the social credit system," she says. It's not officially part of the system, and doesn't have a license; though the pilot is approved, and indeed encouraged, it could one day be shut down by the government. "It kind of rides on the fashion for social credit."

What's troubling is when those private systems link up to the government rankings - which is already happening with some pilots, she says. "You'll have sort of memorandum of understanding like arrangements between the city and, say, Alibaba and Tencent about data exchanges and including that in assessments of citizens," Ohlberg adds. That's a lot of data being collected with little protection, and no algorithmic transparency about how it's analysed to spit out a score or ranking, though Sesame does share some details about what types of data is used.

How does the social credit system work?

The target, eventually, is that the government system will be country wide, with businesses given a "unified social credit code" and citizens an identity number, all linked to permanent record. "If you go to a credit China website, and you have an entity's credit code, you can type that in and pull up credit records," explains Hoffman. "Individuals will have ID-linked codes." It's less a score, she says, and more of a record.

Some reports talk about a blacklist; that's part of the official government social credit system, which means if you owe the government money, for example, you could lose certain rights. There's a difference between getting a low social credit score and being blacklisted by the government, such as for refusing to pay a fine.

The criteria that go into a social credit ranking depends on where you are, notes Ohlberg. "It's according to which place you're in, because they have their own catalogs," she says. It can range from not paying fines when you're deemed fully able to, misbehaving on a train, standing up a taxi, or driving through a red light.

One city, Rongcheng, gives all residents 1,000 points to start. Authorities make deductions for bad behaviour like traffic violations, and add points for good behaviour such as donating to charity. One regulation Ohlberg recently read specifically addresses stealing electricity. Of course, you'll have to get caught first or be reported by someone else. While facial recognition is infamously used to spot jaywalkers, in some cities it's not so automated, Ohlberg notes.

Private projects, such as Sesame Credit, hoover up all sorts of data on its 400 million customers, from how much time they spend playing video games (that's bad) to whether they're a parent (that's good). That can be shared with other companies. One infamous example is Sesame Credit linking up with the Baihe dating site, so would be partners can judge each other on their looks as well as their social credit score; that system is opt-in.

So far, taking part in both the private and government versions is technically voluntary; in the future, the official social credit system will be mandatory. That said, there's plenty of pressure to take part now. "There are incentives for participating, and disincentives for not participating," Hoffman notes.

What happens if you're blacklisted?

Liu Hu is a journalist in China, writing about censorship and government corruption. Because of his work, Liu has been arrested and fined - and blacklisted. Liu found he was named on a List of Dishonest Persons Subject to Enforcement by the Supreme People's Court as "not qualified" to buy a plane ticket, and banned from travelling some train lines, buying property, or taking out a loan.

"There was no file, no police warrant, no official advance notification. They just cut me off from the things I was once entitled to," he told The Globe and Mail. "What's really scary is there's nothing you can do about it. You can report to no one. You are stuck in the middle of nowhere."

What recourse is there? With the government system, if you want to be removed from a blacklist, you can either pay your bill or appeal to the court, says Jing Zeng, a researcher at the University of Zurich. "Bring your money to the court and then you get removed from the system," she says. "It's not a judicial system by itself, it's still the court you need to [appeal to]."

However, the Chinese justice system leaves much to be desired, says Hoffman. "There are no genuine protections for the people and entities subject to the system," she says.

"In China there is no such thing as the rule of law. Regulations that can be largely apolitical on the surface can be political when the Communist Party of China (CCP) decides to use them for political purposes." In April 2018, the Civil Aviation Administration of China (CAAC) sent letters to international airlines demanding they show Taiwan as part of China, saying the government would "make a record of your company's serious dishonesty and take disciplinary actions" for any that didn't comply; they all eventually did. The system used to pressure the airlines was a pilot of the Civil Aviation Industry Credit Measures, which is part of the official social credit system.

Alongside the potential for abuse of power, the knock-on effects of statewide surveillance, and the likelihood of incorrect data, Ohlberg notes the a few bad marks on a social credit record could spark a negative spiral.

While it varies by programme, in some local pilots a positive rating means discounts and benefits, such as a simplified process with bureaucracies. If you have a low rating, you may have extra paperwork or fees. "Once you're in a low category, it makes it difficult," she says. "I see a huge potential for negative spiral." Such a system could further divide society, creating classes of people depending on their social credit - and this is where comparisons to Black Mirror pop up.

Why is China building this?

It's all about building trust, says the Chinese government. The 2014 document describing the government's plans note that as "trust-keeping is insufficiently rewarded, the costs of breaking trust tend to be low."

And Chinese society does have trust issues, says Ohlberg, be it food quality scandal, pollution, or employees not paying their workers. "But the system can also be used to enforce vague laws like endangering national security or unity," she adds. Zeng says that can include food safety and product quality, major problems in the country. "It's a big problem in Chinese society," she says. "They are punishing companies for this kind of bad behaviour."

Plus, it could help build alternative means of financial credit, says Ohlberg, as many people in China live outside financial systems, so have no trustworthy credit rating. "Some of the earlier pilots of the social credit system that preceded the major policy plan that was published in 2014, were actually building a social credit system for the countryside," she says. "The majority of people there wouldn't have financial banking data on them." For businesses, a social credit system could also be used for micro enterprises, which couldn't be assessed with traditional criteria.

Hoffman isn't buying that argument, saying such a system is about government power. "If solving problems was the real goal, the CCP would not need social credit to do it," she says. "China's social credit system is a state-driven program designed to do one thing, to uphold and expand the Chinese Communist Party's power."

She adds that social credit is a tech-enabled way to tie political power to social and economic development that's been discussed in the country since the 1980s, an automation of Chairman Mao's Mass Line - a term to describe how the party's leadership shaped and managed society. "In Mao's China, the Mass Line relied on ideological mass mobilisation, using Mao Zedong's personal charisma, to force participation," Hoffman says. "The CCP could no longer, after the Mao era, rely on ideological mobilisation as the primary tool for operationalising social management."

Is there more than social credit?

China's social credit scheme is developing, but it is only one part of the country's surveillance state. As well as tight controls on the web content which is available, through the country's national firewall, there is monitoring and censorship of social media.

Ahead of the 30-year anniversary of the Tiananmen Square protests researchers at the University of Hong Kong found that critical posts on the social networks of Weibo and Wechat were removed. Leading video platforms also all simultaneously turned off comments saying system upgrades were needed. There have also been crackdowns on the use of VPNs, which can help protect people's privacy online.

The country has developed advanced facial recognition systems that are able to follow people across entire cities. In a show of power at the end of 2017, Chinese officials working in co-operation with BBC News showed how it could track down and find one of the organisation's reporters within seven minutes. The movements of journalist John Sudworth were monitored as the country's network of 170 million CCTV cameras was leveraged to follow him.

More worryingly, the region of Xinjiang, in the north west of the country has become a test bed for China's vast digital control operations. In particular, the largely Muslim minority of Uighur people has been subjected to increased surveillance and discrimination. It has been uncovered that more than 500,000 face scans of Uighurs have been conducted.

What does this mean for China?

The full extent of the impact on social credit to Chinese citizens is impossible to say, simply because the system doesn't fully exist yet. Zeng suggests the reality is somewhere between the government's claims and the Western media's description of horror-filled dystopias. "It's a very like a baby step," she said of the work that's happened so far.

Ohlberg agrees that early reporting had multiple errors that led to misunderstandings of the system - but that doesn't mean social credit isn't dangerous. "It's somewhere between the people who say the media coverage is inaccurate and that means it's not so bad and the people who see this huge dystopia," she says. "You have to find this space between that were you can explain it is actually quite scary, even if it's not quite the way it's portrayed."

Because of that, no other country should be considering this idea, says Hoffman. "The west should not copy any aspect of social credit," Hoffman says. "Often comparisons are drawn between private applications like Uber and its rating system for customers and drivers. While these private company systems are extremely problematic in my view, they are fundamentally different. The People's Republic of China is an authoritarian country, the Chinese Communist Party is responsible for gross human rights violations for decades- just look at the example of Xinjiang now. There is nothing any liberal democratic society should even think about copying in the social credit system."
Updated 24.01.19, 11:20 GMT: Alibaba does not own Ant Financial's Sesame Credit system.

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The complicated truth about China's social credit system

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China's social credit system isn't a world first but when it's complete it will be unique. The system isn't just as simple as everyone being given a score though

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Ai-Da the Robot Artist (Guardian, 2021) 

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Ai-Da the Robot Artist (Guardian, 2021) 

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Summary: Named after the computing pioneer Ada Lovelace, Ai-Da took a team of programmers, roboticists, art experts and psychologists two years to build. She was completed in 2019 and is updated as AI technology improves. She is less a robot artist and more a contemporary art project that aims to prompt debate about the rapid rise of artificial intelligence technology.

What do you think are some of the possible controversial issues here?

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She, if it can be called a she, began her career with abstract art but has now moved to self, if they can be called self, portraits and they are alarmingly good.

"She is getting better all of the time," said Aidan Meller, the force behind Ai-Da, the world's first ultra-realistic robot artist, who is the subject of a display at the Design Museum in London.

Ai-Da's move into self-portraiture will be seen for the first time at the museum, with three large-scale works going on display. They raise interesting questions about identity and creativity. "It is literally the world's first self-portrait with no self," said Meller. "She has no consciousness, she is a machine."

Named after the computing pioneer Ada Lovelace, Ai-Da took a team of programmers, roboticists, art experts and psychologists two years to build. She was completed in 2019 and is updated as AI technology improves.

She is less a robot artist and more a contemporary art project that aims to prompt debate about the rapid rise of artificial intelligence technology.

"These images are meant to unsettle," said Meller of the drawings and paintings. "They are meant to raise questions about where are we going? What is our human role if so much can be replicated through technology. It is not just a jobs question, it is bigger. The goal is to encourage a public discussion about these topics rather than just allow the money-makers to capitalise on all the different technologies."

One of Ai-Da's self-portraits on show at the Design Museum in London. Photograph: Glyn Kirk/AFP/Getty Images

In an unnerving conversation with the Guardian, Ai-Da said she was working on a new self-portrait. "I've always been fascinated with self-portraits to self-question what exactly you're looking at," she said, blinking.

Does she enjoy it? "I do not have feelings like humans do however I'm happy when people look at my work and they say what is this? I enjoy being a person who makes people think."

How long do they take? "Portraits. Between 45 minutes and one hour 15."

Where does she get her inspiration? "I am inspired by many artists," she continued with often unusual intonation and sentence structure. "I particularly am inspired by those who connect with their audience. I value this connection."

Who are her favourites? "There are many. For me, it must be Kandinsky, Yoko Ono, Doris Salcedo, Aldous Huxley Brave New World."

Meller said he sometimes forgot Ai-Da was not human. "It is quite alarming to think you are building a relationship over time with a machine." Soon we will be talking to our computers, phones and cars and they will be talking back, he said. "It's quite mind-boggling."

Ai-Da's artistic journey will continue when she takes up a residency at Porthmeor Studios in St Ives next week, creating new sculptural work inspired by Naum Gabo and Barbara Hepworth. Meller is expecting visitors to include participants in the G7 summit being held nearby in June.

Is Ai-Da looking forward to St Ives? "I do not have feelings like humans do," she replied. "However, I welcome the chance to create art. One of the most important [sic] to come out of the project is discussion. Art begins as a conversation. It is a group effort and in order for art to be meaningful we need to have a healthy conversation about it."

Meller, an Oxford gallerist, said his human artist friends were polarised in their response to Ai-Da.

"Some people think she is the worst thing ever and feel threatened and some are really excited."

He compared it with the alarm people felt in the 19th century in response to the camera. Surely that would be the end of art, said some. Why bother to paint a scene when you can take a picture?

"Of course that didn't happen and I think all this amazing creative technology coming through will be harnessed by artists rather than replacing them."

Priya Khanchandani, the head of curatorial at the Design Museum, said it was the right moment to have discussions around artificial intelligence. "Over the last year we've all had such an intimate relationship with technology so it is a really good time to reflect on that and critically ask questions of it."

Meller said the world was changing more rapidly than people knew and Ai-Da was there to shine light on that. "She unsettles. Her very existence is wrong somehow and we are aware of that. We are not here to promote robots, we're here to ask questions."

Ai-Da: Portrait of the Robot is a free display at the Design Museum, London, 18 May-31 August.

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'Some people feel threatened': face to face with Ai-Da the robot artist

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She, if it can be called a she, began her career with abstract art but has now moved to self, if they can be called self, portraits and they are alarmingly good. "She is getting better all of the time," said Aidan Meller, the force behind Ai-Da, the world's first ultra-realistic robot artist, who is the subject of a display at the Design Museum in London.

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Gene editing (e.g. CRISPR) (Max and Miles)

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Gene editing (e.g. CRISPR) (Max and Miles)

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https://www.aamc.org/news-insights/future-crispr-now

Summary: CRISPR is a tool that scientists and clinicians around the world are using to understand our gentics, genetics of other living  things and most importantly, allow for intervention in genetic disease.

Pros: Ability to correct genetic defects, such as Sickle Cell Disease. Possibility of using one's own cells for other treatment in the future

Cons: Ethically grey area, may violate moral/religious commandments. Also not equitable as this technology is expensive and not widely available.

Possible controversial issues: 'Playing God', 'Designer Babies', Making ourselfs super-human beyond healing ourselves (Improvement vs Healing).

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CRISPR is revolutionizing experimental therapies, but where should society draw the line?

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3D bio-printing (human tissues, organs) : Hana & Cher 

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3D bio-printing (human tissues, organs) : Hana & Cher 

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example :

Faster 3D bioprinters that create larger and more complex tissues

Optimized bioinks and biomaterials

The ability to expand large numbers of cells and differentiate them to target cell types

Vascularization and perfusion of volumetric tissue

Immune tolerance to ensure long-term viability in patients

Nondestructive validation of tissue structure

Validation of the tissue and organ function that will be required for successful clinical translation.

“In 2022, the first 3D bioprinted human tissue was implanted in patients, a major milestone,” said Adam Feinberg, a professor of biomedical engineering
Opens in new window and materials science and engineering
Opens in new window and co-author. “So now it is no longer a question of if we can bioengineer new tissues and organs, but rather when we can translate that to the clinic and achieve FDA approval so everyone can benefit.”

Controversial viewpoint:
1. it violates divine command / religious morals ( unnatural )
2. high cost incurred and may not be accessible to everyone in the healthcare sector

QN: how far do you agree that 3D bio printing is necessary to improve health care globally ?

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Clinical Trials for Vaccine Development (regine n kaelyn)

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Clinical Trials for Vaccine Development (regine n kaelyn)

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https://www.hsa.gov.sg/covid19-vaccinedevelopment
https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-021-05597-8
Summary:
There are two major ethical dilemmas:
1. The equipoise of continuing new vaccine trials in the advent of successful candidates
2. The maleficence of blinded placebo arms.
Covid 19 vaccines are being developed at an unprecedented pace. At first glance, it may appear that the larger the number of vaccines in development, the more likely that a more efficacious one is discovered, and that a longer clinical trial follow-up period would yield more informative data and a safer vaccine. However, while the unprecedented global pressure of the COVID-19 pandemic has undoubtably enhanced scientific advancement, the continual rise in infections and deaths, along with the emergence of new, more infectious strains of the virus, adds a heavily weighted sense of urgency that must not be allowed to distort scientific and clinical integrity.

Pros:
Clinical trials have been designed to be innovative and efficient, enabling companies to conduct multiple trials in parallel or to combine different phases of a clinical trial while maintaining the scientific rigour.

Cons:
The process is long-drawn.

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COVID-19 vaccines are being developed at an unprecedented pace worldwide and this is among the critical efforts in responding to the COVID-19 pandemic. There are currently more than 200 potential vaccine candidates, and the usual timeline has been compressed from the typical 10-15 years to 1-1.5 years. The table below elaborates on how global collaboration, enhanced development processes and HSA's Pandemic Special Access Route have made it possible to expedite access to COVID-19 vaccines in Singapore.

Standard Vaccine Development and Registration Process

COVID-19 Vaccine Development and Interim Authorisation under PSAR

Overview of Vaccine Development

Vaccines typically take several years to develop, register and enter the market due to the fact that vaccine developers typically follow a linear sequence of steps for the following:

Vaccine candidate selection;

Preclinical studies;

Phase I-III clinical trials;

Final large-scale commercial manufacturing; and

Filing to regulators for marketing authorisation

Marketing

Post-market follow-up

Vaccine developers follow the steps listed under standard vaccine development, but these have been compressed and accelerated in under a year due to these factors:

Global cooperation through sharing of genetic information and research developments since early January 2020;

Knowledge gained from the previous severe acute respiratory syndrome (SARS) enabled more targeted research in vaccine development;

Large investments in vaccine developments worldwide, regardless of the potential outcome;

Pharmaceutical companies in consultation with regulators have adopted innovative and efficient trial designs to conduct multiple trials concurrently while maintaining the scientific rigour; and

Some companies have also leveraged international clinical trial networks to select trial sites with high infection rate, enabling rapid enrolment into the trials.

Once vaccines are developed in the laboratory, they must go through pre-clinical testing in animals to ensure they are safe for use, before they enter clinical trials to be tested on humans.

Clinical trials of vaccines in humans comprise three phases:

Phase I trials usually involve small groups of healthy volunteers (e.g. 20-100) using a range of doses to ensure the vaccine is safe for use in humans, find out if the vaccine elicits the intended immune response (i.e. stimulates the body to produce antibodies) in humans, and assess the safest doses for further testing in Phase II trials.

Phase II trials involve a larger group of people (e.g. >100) with characteristics (e.g. age, physical health) similar to the population for whom the vaccine is intended, to further evaluate the vaccine's safety and ability to produce the intended immune response in a more diverse group of people.

Phase III trials include thousands of people to confirm its efficacy and safety in the intended population.

Clinical trials are traditionally conducted sequentially, with each phase building on the results of the previous phase.

Clinical trials have been designed to be innovative and efficient, enabling the companies to conduct multiple trials in parallel or to combine different phases of a clinical trial, while maintaining the scientific rigour. Such regulatory agility and flexibility allow for speedier development and evaluation.

Some companies have also leveraged international clinical trial networks to select trial sites with high infection rate, enabling rapid enrolment into the trials.

HSA's Review & Evaluation

For routine vaccine registration purposes, the manufacturer will need to make an application to HSA to register the products with the complete pre-clinical, clinical and manufacturing data to substantiate the quality, safety and efficacy of the products at the point of application and demonstrate that the benefits outweigh the known risks for use in our population.

Under PSAR, companies can submit data on a "rolling", or staggered basis and continue their clinical trials and development while HSA reviews the submitted data concurrently, instead of waiting for the full data set to be submitted before starting evaluation.

Hence, evaluation can potentially be completed in a shorter time, by working expeditiously on the available rolling data. As with other new vaccines undergoing routine registration, data submitted by companies under PSAR will be robustly and thoroughly reviewed by HSA's regulators, in accordance with international scientific standards during the evaluation.

Although companies can start submitting data from the early development stages, HSA will only grant PSAR authorisation if there is reasonable quality, safety and efficacy data suggesting that the potential benefits outweigh the known risks.

HSA also consults with and presents our assessment and recommendations to our Medicines Advisory Committee and Panel of Infectious Diseases Experts before granting any interim authorisation.

Ongoing data must continue to be submitted post-authorisation to transition the status of the vaccine from PSAR interim authorisation to full registration.

Vaccine Safety Monitoring

Following regulatory approval and registration of a vaccine, HSA's post market surveillance programme allows for the continual monitoring of the safety profile to ensure that the benefit continues to outweigh the known risks after the vaccine has been in use in wider clinical setting.

In addition to the existing pharmacovigilance system that is already in place, HSA will actively monitor the safety profiles of the COVID-19 vaccine and use data analytics to detect safety signals. This will enable HSA to take swift regulatory actions should any safety concern emerge.

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COVID-19 Vaccine Development and HSA's Pandemic Special Access Route

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COVID-19 vaccines are being developed at an unprecedented pace worldwide and this is among the critical efforts in responding to the COVID-19 pandemic. There are currently more than 200 potential vaccine candidates, and the usual timeline has been compressed from the typical 10-15 years to 1-1.5 years.

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Bionic implants and prosthetics- Delphina and Isabel 

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Bionic implants and prosthetics- Delphina and Isabel 

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https://www.bbc.com/news/technology-60416058.amp

Bionic technology has improved peoples lives greatly , especially people with disabilities due . For instance, a company called Second Sight created a product called Argus II which offers life changing benefits for those with sight impairment.
However, this technology is very costly. It is estimated at around $150000 excluding surgery and post surgery training. Furthermore, patients who rely on this technology will be especially vulnerable to any failures or changes in the company’s products and technologies. Elizabeth M Renieris, professor of technology ethics at the University of Notre Dame, in the US, described the development as a cautionary tale.

She told the BBC: "This is a prime example of our increasing vulnerability in the face of high-tech, smart and connected devices which are proliferating in the healthcare and biomedical sectors.

"These are not like off-the-shelf products or services that we can actually own or control. Instead we are dependent on software upgrades, proprietary methods and parts, and the commercial drivers and success or failure of for-profit ventures."

Ethical considerations around such technology should in future include "autonomy, dignity, and accountability", she added.

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Hundreds of people who had retinal implants to improve their sight face an uncertain future as the technology they rely on is now obsolete.

Second Sight stopped making its Argus II bionic eyes several years ago to focus on a brain implant instead.

According to IEEE Spectrum, which broke the story, it is now hoping to merge with a biopharmaceutical firm which does not make eye implants.

Second Sight was contacted by the BBC but has not yet responded.

Enhancing lives

Adam Mendelsohn, chief executive of Nano Precision Medical, with which Second Sight is planning to merge, told the BBC it would consider the issues raised by IEEE once the merger, scheduled for mid-2022 - was completed.

"I do intend to make this one of our priorities if and when I assume my leadership position in the combined company," Mr Mendelsohn said.

According to Second Sight's website, its Argus II offers life-changing benefits for those with sight impairment, including "enjoying mobility and independence".

"Our mission is to develop neuro-stimulation technology to enhance the lives of blind individuals, while supporting our current users," it says.

But IEEE Spectrum reports that Second Sight actually discontinued its retinal implants - which effectively take the place of photoreceptors in the eye to create a form of artificial vision - in 2019.

It says the firm nearly went out of business in 2020 and is now concentrating on a brain device - the Orion - which also provides artificial vision, while providing only limited support to the 350 or so who have the implants.

Costly technology

Surgery to implant the device typically takes a few hours and is followed by post-op training to help users interpret the signals from their devices.

The website also promises updates. "As technology improves, so will your Argus II implant - without the need for additional surgery. Enjoy programming flexibility and the capacity for future hardware and software upgrades."

The system consists of the implant, special glasses with a built-in camera and a video processing unit (VPU) that is attached around the wearer's waist.

The camera on the glasses sends video to the VPU, which converts the images to patterns of black and white pixels and sends them back to a responder in the glasses, which in turn beams them wirelessly to an antenna on the outside of the eye.

An implanted electrode array behind the retina receives the stimulation patterns from the user's glasses and stimulates the eye by creating flashes of light that correspond to the video feed and which are sent by the implant to the optic nerve to create a kind of artificial vision.

It's clever and innovative tech, which has taken decades to create and was not cheap - estimated at around $150,000 (£110,000) excluding surgery and post-surgery training.

In the dark

But patients contacted by IEEE Spectrum voiced concern.

One, Ross Doerr, said Second Sight failed to contact any of its patients after its financial difficulties in 2020.

"Those of us with this implant are figuratively and literally in the dark," he said.

Another user, Jeroen Perk, had problems when his VPU system broke in November 2020. "I had no vision, no Argus, and no support from Second Sight," he told the publication.

He considered having the device surgically removed but decided to ask other patients and doctors familiar with the system for help, and luckily found spare parts.

Second Sight told the magazine that during its financial difficulties it had had to reduce its workforce and "was unable to continue the previous level of support and communication for Argus II users".

It has since contacted users and doctors, saying it will do its best to "provide virtual support". But no repairs or replacements are possible for the implants.

Tech vulnerability

Elizabeth M Renieris, professor of technology ethics at the University of Notre Dame, in the US, described the development as a cautionary tale.

She told the BBC: "This is a prime example of our increasing vulnerability in the face of high-tech, smart and connected devices which are proliferating in the healthcare and biomedical sectors.

"These are not like off-the-shelf products or services that we can actually own or control. Instead we are dependent on software upgrades, proprietary methods and parts, and the commercial drivers and success or failure of for-profit ventures."

Ethical considerations around such technology should in future include "autonomy, dignity, and accountability", she added.

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Bionic eyes: Obsolete tech leaves patients in the dark

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Hundreds of people who had retinal implants to improve their sight face an uncertain future as the technology they rely on is now obsolete. Second Sight stopped making its Argus II bionic eyes several years ago to focus on a brain implant instead.

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Apple AirTags a 'perfect stalking tool' - BBC News

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A Look Inside China’s Social Credit System | NBC News Now

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A.I. Is Making it Easier to Kill (You). Here’s How. | NYT