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summary: it discusses the growing concerns among reproductive-rights advocates regarding the future accessibility of IVF in the United States. advocates fear that recognizing embryos as persons could lead to restrictions or bans on IVF procedures, as the process often involves the creation and sometimes destruction of of fetuses. it introduced uncertainty for individuals and couples relying on IVF to conceive, prompting discussions about the balance between protecting potential life and ensuring reproductive freedoms.

pros:

ethical considerations: Assigning personhood to embryos may align with certain ethical or religious beliefs that life begins at conception, promoting the protection of potential human life.

legal clarity: provide consistency in laws related to reproductive technologies

cons:

restricted access to IVF: defining embryos as persons could lead to legal challenges against IVF practices, potentially limiting access for individuals and couples seeking fertility treatments.

medical implications: medical professionals might face legal risks when handling embryos, possibly deterring them from offering IVF services or leading to more conservative practices that reduce the procedure’s effectiveness.

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IVF Changed America. But Its Future Is Under Threat

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It may be the next battle in the reproductive-rights war.

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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?

Possible criticisms of this system?

Possible controversial issues:

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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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Technological Repression of Xinjiang Muslims ( Lizzie and Euan ) 

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Technological Repression of Xinjiang Muslims ( Lizzie and Euan ) 

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Summary :

In 2017, Alim, a Uighur man, returned to China after studying abroad and was detained by police for being suspected of extremism. He was subjected to harsh interrogation, forced to undergo biometric data collection, and later sent to a "re-education" camp in Xinjiang, where Uighurs face indoctrination and harsh conditions. After being released, Alim discovered that his data had placed him on a government blacklist, subjecting him to constant surveillance. Despite being "free," he was tracked by facial recognition and AI-driven systems, which monitored his movements and made him feel trapped by his own digital footprint. This surveillance is part of China's broader effort to control and suppress Uighur Muslims through technology and surveillance.

Solutions :

International Pressure and Diplomacy

Promoting Digital Privacy Rights

Support for Uighur Communities

Pressuring Tech Companies

Raising Awareness and Education

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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

Follow the Long Read on Twitter at @gdnlongread, and sign up to the long read weekly email here.

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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 (Fakhira & Rebekah)

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Human test subjects – Nazi Medical Experiments (Fakhira & Rebekah)

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Summary

This article documents the inhumane Nazi medical experiments during World War II. It highlights experiments such as high-altitude testing, forced amputations, and exposure to deadly diseases. The review contextualizes these atrocities with broader ethical issues in modern medical practices, questioning how far society has progressed in upholding patients rights

Pros and Cons:

Pros: It exposes unethical medical practices; serves as a critical historical lesson on ethics. The Nazi doctors conducted cruel experiments in the name of medicine, and although it was not prohibited at that point in time, it was not viewed as ethical, thus teaching a good lesson on how just because something is allowed does not mean it is ethical.

Cons: Graphic content may be distressing; challenges universal medical standards. Although the experiments were cruel and inhumane, the result became something that was beneficial in the future world.

Possible Solution: Strengthen global medical ethics education and oversight.

Controversial Issues: Exploitation of vulnerable populations; lingering eugenics influence.

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Columbia University College of Physicians and Surgeons, New York, New York, USA. E-mail: arm42columbia.edu

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Doctors from hell: The horrific account of Nazi experiments on humans

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This shocking first-hand account of the monstrous behaviors of Nazi physicians by Vivien Spitz should be required reading for all medical, dental, nursing, and public health students and faculty. Time is better spent reading this book than filling out HIPAA forms and other well-intentioned but even less effective tools designed to protect patients’ interests.

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Satellite Technologies in Emergency Response 

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Satellite Technologies in Emergency Response 

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[SAMPLE] Chips monitoring Chinese Students (ABC, 2018)                                 

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[SAMPLE] 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:
- Ensures protection / safety for the child / safety for students at large (especially useful in Covid-19 context- contact tracing)
- Accountability by the school/teachers
- Parents are more assured (child's safety and whereabouts)

Cons & Limitations:
- Lack of privacy
- Restrict freedom (constantly tracked)
- Data leak/ data security
- Are there any health risks?

Possible Controversial issues:
- Privacy vs Security
- The issue of consent (students/parents/school)

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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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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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Biometric Registration of Rohingya Refugees 

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Biometric Registration of Rohingya Refugees 

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Bionic implants and prosthetics (cedric and felicia)

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Bionic implants and prosthetics (cedric and felicia)

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Researchers at Chalmers University of Technology have developed a groundbreaking method to restore complex tactile sensations in the limbs of paraplegic individuals. The approach uses an external device attached to the wheelchair, which performs movements, with the tactile signals transmitted directly to the patient's brain via targeted stimulation.

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An artificial sense of touch for paraplegics

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(Bild: Chalmers University of Technology) Researchers at Chalmers University of Technology have developed a groundbreaking method to restore complex tactile sensations in the limbs of paraplegic individuals. The approach uses an external device attached to the wheelchair, which performs movements, with the tactile signals transmitted directly to the patient’s brain via targeted stimulation.

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https://www.nbcnews.com/politics/national-security/china-has-done-human-testing-create-biologically-enhanced-super-soldiers-n1249914

The article discusses claims by U.S. intelligence officials that China has conducted human testing to create biologically enhanced soldiers, raising concerns about ethical boundaries and international security. In a Wall Street Journal op-ed, then-Director of National Intelligence John Ratcliffe accused Beijing of using gene-editing technologies like CRISPR on members of the People’s Liberation Army (PLA) to develop “super-soldiers.”

These allegations are supported by research published in 2020 that examined China’s interest in leveraging biotechnology for military purposes, such as enhancing physical and cognitive abilities. The study highlighted China’s focus on cutting-edge genetic technologies and its potential integration into defense strategies.

Critics argue that China’s pursuit of such capabilities demonstrates a willingness to ignore ethical considerations in its quest for global dominance. However, Chinese officials have dismissed these accusations, calling them baseless and politically motivated.

The article also addresses the broader ethical and security implications of gene-editing in warfare, as the technology could revolutionize the battlefield by creating soldiers with heightened strength, endurance, or resistance to disease. Experts warn of the potential dangers of unregulated use of biotechnology, including an arms race in biological enhancement that could destabilize global security.The article discusses claims by U.S. intelligence officials that China has conducted human testing to create biologically enhanced soldiers, raising concerns about ethical boundaries and international security. In a Wall Street Journal op-ed, then-Director of National Intelligence John Ratcliffe accused Beijing of using gene-editing technologies like CRISPR on members of the People’s Liberation Army (PLA) to develop “super-soldiers.”

These allegations are supported by research published in 2020 that examined China’s interest in leveraging biotechnology for military purposes, such as enhancing physical and cognitive abilities. The study highlighted China’s focus on cutting-edge genetic technologies and its potential integration into defense strategies.

Critics argue that China’s pursuit of such capabilities demonstrates a willingness to ignore ethical considerations in its quest for global dominance. However, Chinese officials have dismissed these accusations, calling them baseless and politically motivated.

The article also addresses the broader ethical and security implications of gene-editing in warfare, as the technology could revolutionize the battlefield by creating soldiers with heightened strength, endurance, or resistance to disease. Experts warn of the potential dangers of unregulated use of biotechnology, including an arms race in biological enhancement that could destabilize global security.

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U.S. spy chief: China has done human testing to make super soldiers

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U.S. intelligence agencies didn’t immediately respond to requests for comment about whether China seeks super soldiers like those in such films as “Captain America.”

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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?
- [What is art?] Is it considered as art if it is produced by a robot artist? (Other related issues: copyright issues to do with art)
- [Technology & Art] How far should boundaries be drawn with the use of technology in art?
- Security issues: https://www.thetimes.co.uk/article/ai-da-the-robot-artist-detained-in-egypt-over-security-risk-6gf7hmlb0

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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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Clinical Trials for Vaccine Development (FengZhou Kendrik)

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Clinical Trials for Vaccine Development (FengZhou Kendrik)

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Participating in clinical trials is a significant decision that requires thorough understanding and consideration. The Health Sciences Authority (HSA) of Singapore provides comprehensive guidelines to ensure participants are well-informed and protected throughout the process

Controversies and Ethical Perspectives:

1. Informed Consent: Ensuring participants fully understand the trial's nature, potential risks, and benefits is crucial. Miscommunication or lack of comprehension can lead to ethical breaches.

2. Public Trust: Unethical practices or perceived misconduct can lead to skepticism towards clinical research. The trials are conducted transparently to uphold public confidence.

3. Equitable Access: Ensuring that diverse populations are included in trials promotes equity and generalizability of results. Excluding certain groups can lead to disparities in treatment efficacy and acceptance.

Potential Solutions and Safeguards in the Singapore Context:

Robust Ethical Oversight: Singapore's HSA provides stringent ethical and regulatory reviews to ensure clinical trials are scientifically sound and ethically justified.

Community Engagement: Actively involving communities in the trial process can enhance understanding and trust. Transparent communication about trial purposes, processes, and outcomes is essential.

Continuous Monitoring: Implementing ongoing monitoring mechanisms ensures participant safety and addresses ethical concerns promptly.

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Understand the possible benefits, risks and your rights as a participant should you decide to participate in a clinical trial. 

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Assisted dying now accounts for one in 20 Canada deaths - BBC News https://search.app/JH4KyDT6D9AF59YR8

https://www.reddit.com/r/changemyview/s/emjaOCRh67

People should have the right to their bodies, after all, nobody asked to be born.

However,

suicide could be an impulsive action in some situations, while it could be a rational one in a different context. In what situations is euthanasia a valid option? And how do we prevent impulsive and otherwise unwilling people to commit suicide thanks to the ease of access of euthanasia if it's legalised?

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Individuals in high-stress, high-performance roles have reported benefits from nootropic supplementation.

Research into psilocybin, the active compound in "magic mushrooms," has shown promise for treating mental health conditions such as depression, anxiety, PTSD, and addiction.

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How ‘magic mushrooms’ could transform medicine - from depression to addiction

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PSYCHEDELIC drugs might still invoke images of The Beatles, Woodstock and flower power – but one day they could be prescribed by a doctor. An emerging area of science is focusing on the idea that a…

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Pros:

satellite communications are a critical part of emergency response to restore communications when cellular networks are out of service.

The satellites are also used to connect back to their enterprise applications, to manage supply chains, track inbound supplies and personnel, and collect data for assessing the damage after a disaster

Cons:

Adverse weather conditions can affect its effectiveness

Summary:

During the recent storm (Hurricane Helene), satellite technology allowed the telco to maintain communication services despite damaged infrastructure.

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Critical Connections: Satellite’s Role in the Wake of Hurricane Helene | November 2024

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In situations like Hurricane Helene and other natural disasters, satellite communications are a critical part of emergency response to restore communications when cellular networks are out of service.

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Summary: tracetogether was an app produced during Covid 19 to track close contacts of patients so as to reduce the rate of infection among the public.

Pros: mitigates the possibility of excessive mingling between patients, potential patients and the rest of the public.

Criticisms: major concerns arose regarding the use of tracetogether data for other intents. Eg: police investigations which infringes one’s privacy and shows a lack of transparency.

https://www.todayonline.com/singapore/some-tracetogether-users-upset-govts-revelation-police-access-data-say-theyll-use-it-less

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Some TraceTogether users upset with Govt's revelation on police access to data, say they'll use it less

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SINGAPORE - Singapore writer Ng Yi-Sheng had been using the TraceTogether mobile application for months during the Covid-19 pandemic. He even carried the token out with him when it is not necessary to use both together, because just holding the token made him feel safe.

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Chinese doctors have cautioned students preparing for "gaokao", China's university entrance exam, against using unregulated "smart drugs" marketed online to boost academic performance. These substances, often sold without proper oversight, pose risks such as addiction, side effects, and long-term health damage.

This in turn is unfair to other students, and patients who actually need them for ADHD.

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Doctors warn gaokao candidates against black market stimulant drugs

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Students who take the medication to stay awake while they cram for exams told they may experience side effects including headaches and insomnia.