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Biometric Registration of Rohingya Refugees 

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Biometric Registration of Rohingya Refugees 

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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?

Consider how technology has impacted art.

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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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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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Technological Repression of Xinjiang Muslims  

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Technological Repression of Xinjiang Muslims  

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https://www.hrw.org/news/2020/12/09/china-big-data-program-targets-xinjiangs-muslims

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(New York) - A big data program for policing in China's Xinjiang region arbitrarily selects Turkic Muslims for possible detention, Human Rights Watch said today. A leaked list of over 2,000 detainees from Aksu prefecture provided to Human Rights Watch is further evidence of China's use of technology in its repression of the Muslim population.

The big data program, the Integrated Joint Operations Platform (IJOP), apparently flagged the people on the Aksu List, whom officials then evaluated and sent to "political education" camps in Xinjiang.

"The Aksu List provides further insights into how China's brutal repression of Xinjiang's Turkic Muslims is being turbocharged by technology," said Maya Wang, senior China researcher. "The Chinese government owes answers to the families of those on the list: why were they detained, and where are they now?"

Human Rights Watch first reported on the IJOP in February 2018, noting that the policing program aggregates data about people from various sensory systems in Xinjiang, and flags to officials those it deems potentially threatening. Officials then evaluate these individuals' "general performance" together with other sources of information, and send some to political education camps and other facilities. Human Rights Watch " reverse engineered" the IJOP mobile app in May 2019 and revealed the dubious criteria this mass surveillance system was programmed to flag, including many lawful behaviors.

The Aksu List, dated around late 2018, is similar to another leaked file, the Karakax List. That list-of people detained for having relatives abroad-dated around June 2019, provides an assessment of whether an individual should remain in detention. The IJOP is also repeatedly mentioned in the Karakax List. Together the lists provide two snapshots of Xinjiang's bureaucracy, as it picks and vets its victims in the process of coerced thought transformation: the decision to detain people and the decision to keep them in detention. At both stages, the IJOP system assists officials in selecting targets.

The entry for "Ms. T" on the Aksu List illustrates how the program's algorithms identify legal behaviors as grounds for detention. It notes that she was detained because the IJOP system had flagged her for "links to sensitive countries." It reported that Ms. T had received four calls from a foreign number in March 2017, down to the number of seconds. In other words, the IJOP system is programed to pick out particular behavior, calls to a foreign number, noting the precise duration of the calls. Human Rights Watch called that number and found that it belongs to Ms. T's sister.

Ms. T's sister said that Xinjiang police interrogated Ms. T around the time the Aksu List recorded her detention date. The police had specifically asked about her sister because she lives abroad. Ms. T's sister said she has had no direct contact with her family in Xinjiang since then, but heard via an intermediary that Ms. T-presumably upon her release from a political education camp-was now working in a factory five days a week and allowed to go home only on weekends. Ms. T's sister believes Ms. T is being forced to work in a factory against her will, noting that Ms. T had been training for a different career before she was detained.

Human Rights Watch's analysis of the Aksu List strongly suggests that the vast majority of the people flagged by the IJOP system are detained for everyday lawful, non-violent behavior. This contradicts the Chinese authorities' claims that their "sophisticated," "predictive" technologies, like the IJOP, are keeping Xinjiang safe by "targeting" criminals "with precision."

The mass surveillance and arbitrary detention of Xinjiang's Turkic Muslims violate fundamental rights under China's constitution and international human rights law. Article 37 of the constitution states that all arrests must be approved by either the procuratorate (the state prosecution agency) or the courts.

Yet Human Rights Watch research indicates that neither agency appears to be involved in these detentions. Rather, administrative officials, including police officers, make the sole decision to detain someone. Those facing detention have no right to due process, including access to lawyers and family members, or a chance to stand trial to contest such allegations. The use of intrusive surveillance, including in and around people's homes, also violates everyone's right to privacy.

"'Predictive policing' platforms are really just a pseudo-scientific fig leaf for the Chinese government to justify vast repression of Turkic Muslims," Wang said. "The Chinese government should immediately shut down the IJOP, delete all the data it has collected, and release everyone arbitrarily detained in Xinjiang."

The Aksu List: Authentication
In August, Radio Free Asia's Uyghur Service provided Human Rights Watch with an Excel spreadsheet titled "List of IJOP Trainees" with the names of over 2,000 people obtained from an anonymous Xinjiang source in late 2018. The sheet has columns that include the person's name, gender, the date of their detention in a political education camp, the reason for their detention, the number of their detention facility or cell, the batch number from which the IJOP systems picked them out, and the reason why, usually no more than a sentence or two.

Although the sender has not been identified, the list appears to come from a part of Aksu prefecture where 80 percent of the residents are Uyghurs. Human Rights Watch is confident that all the people on the Aksu List are Uyghurs. About half of the list are men and the other half women. Their detention dates ranged from mid-2016 to late 2018. At the peak, well over 100 people were detained on a single day. To protect the source, Human Rights Watch is obscuring the precise location of the Aksu List, precise dates, and some of the numbers throughout the analysis.

The file's metadata suggests that it was last modified in late 2018. Human Rights Watch used various methods to verify the Aksu List:

Human Rights Watch shared the Excel sheet with Uyghur diaspora communities from that region, who identified 18 names on the list as their immediate family members.

The list also contains nearly 200 unique ID numbers, which were checked against the ID numbers on an official website of people who have been blacklisted under China's social credit system, run by the Supreme People's Court; and two of those numbers matched. The rate of 1 percent is consistent with the matching rate of those in the Karakax List, which contained more identifying personal information for extensive verification.

Some entries say the individual was detained in a camp after completing a prison sentence, and 20 list the crimes. Human Rights Watch searched the Supreme People's Court's database of Chinese court verdicts for these 20 people's full names, but it did not yield results, though the court verdict database is far from comprehensive.

The Aksu List also contains 27 unique Chinese mobile phone numbers. Human Rights Watch was able to find 14 of them on WeChat. In most cases, their photos, names, and locations indicate that they are Uyghurs from Aksu.

The Aksu List contains two mobile phone numbers from outside China. One is still functional and, as noted, the person who picked up the phone confirmed she is the sister of the woman on the list we have called Ms. T.

The language and terms used in the Aksu List are also consistent with those in other Xinjiang official documents that Human Rights Watch reviewed. Human Rights Watch has shown the full Aksu List to two experts who have extensively documented Xinjiang's repression. They determined that the list appears authentic based on details such as detention duration and the language used.

The same Xinjiang source who provided the Aksu List also provided other audiovisual content to Radio Free Asia's Uyghur Service between mid and late 2018. Human Rights Watch analyzed this material to assess the credibility of the Excel spreadsheet, as it was obtained from the same source.

To protect the anonymous source, Human Rights Watch will not describe specifics of the analysis performed, but concluded that the audiovisual content was taken from inside a detention facility in Aksu. The embedded geographic coordinates suggest that they were taken from within a large building complex previously identified as a political education camp by the Australian Strategic Policy Institute, a think tank. This analysis provides Human Rights Watch with additional confidence in the authenticity of the Aksu List.

The Aksu List: Analysis
According to the Aksu List, the IJOP can flag people at both the prefecture and regional levels, though it is unclear how, or if, those two levels of analysis differ. At both levels, most people were flagged for their relationships, their communications (通联), or for being related to (家族人员 or 亲属), or traveling, or staying with (同行同住) someone the authorities consider suspicious. Column F appears to be the reasons officials give for detaining a person. An examination of the Aksu List suggests that the authorities consider the following behavior suspicious:

Practicing Islam in the following ways:

Studying the Quran without state permission or allowing one's children to study the Quran;

Reciting the Quran, including Khitma [海提玛], the recitation of the entire Quran;

Preaching the Quran without state permission or listening to such preaching;

Wearing religious clothing, such as the burqa or veil, or having a long beard;

Having more children than allowed by China's family planning policy;

Marrying or divorcing outside of official Chinese legal requirements; for example, marrying before reaching the legal age (22 for men and 20 for women), marrying through a Nikah (an Islamic law marriage contract), or practicing polygamy;

Going on Hajj (the annual pilgrimage to Mecca in Saudi Arabia, considered a religious duty in Islam) without state permission;

Performing the Hijra (伊吉拉特), a form of migration to escape religious persecution following the pattern of the immigration of the Prophet Mohammed from Mecca to Medina in 622 CE, which the authorities consider to be motivated by adherence to Islam.

Using suspicious (or "minority" 小众) software, in particular peer-to-peer file sharing application Zapya (快牙), but also Virtual Private Network, Skype, Payeco (易联), L2TP, and imo.

Traveling:

Internationally to "sensitive" countries, including Turkey, Afghanistan, Saudi Arabia, and Kyrgyzstan;

Domestically outside Aksu, including elsewhere in Xinjiang such as Urumqi and Kashgar, or to other parts of China such as Beijing and Shanghai;

Without notifying local officials. People are also detained for having no fixed address.

Going "off grid" (去向不明 or 轨迹不明), for example "switching off their phone repeatedly" or being missing for periods of time.

Having mismatched identity, including using a cellphone number or ID card not registered in one's name, having more than one hukou (residency registration), or having falsified official documents like marriage certificates. In one case, losing an ID-subsequently used by someone else-was a cause for detention.

Having "extremist thoughts" or downloading "extremist" audiovisual content.

Having relatives in a group the authorities have labeled as terrorist, including the East Turkistan Islamic Movement (ETIM) and a couple of Aksu local groups.

Having previously been a target of Xinjiang government actions, such as being detained or convicted of ordinary crimes or political crimes. In one case, a man was subjected to "political education" because he had been detained in 2014 for 15 days for carrying a knife and for not "properly explaining" the incident.

Resisting official policies or official "management." In one case, a man was detained for not paying rent on his land.

Being generally untrustworthy (不放心人员).

Being young; that is, "born after the 1980s" (80, 90后不放心人员).

"Generally acting suspiciously," "having complex social ties" or "unstable thoughts," or "having improper [sexual] relations."

In some cases, the alleged "problematic" behaviors dated to years earlier, revealing broad surveillance of legal and non-violent behavior going back decades. In one case, a man was detained for having studied the Quran in the mid-80s, and having "let his wife wear a veil" in the early 2000s. In another case, a woman was detained for once going to Kashgar, and once staying overnight in Hotan, both in 2013.

The authorities listed "terrorism" and "extremism," both perilously over-expansive terms in Chinese law, as the reasons for detaining about 10 percent (or over 200) of the people on the list. Yet the authorities did not allege that these detainees committed, incited, supported, or plotted any acts of violence, much less any acts that would rise to the level of terrorism. About one in five in this group were tagged for downloading or sharing "terrorism" or "extremism" content. About four in five were listed as being related to someone who had downloaded or shared such content, or to someone who was detained for terrorism or extremism. The Aksu List does not provide any additional information on the content of such audiovisual materials.

Governments may prosecute speech that incites criminal acts-speech that directly encourages the commission of a crime, is intended to result in criminal action, or is likely to result in criminal action-whether or not criminal action does, in fact, result. But laws that impose criminal punishment for what has been called "indirect incitement"-for example, justifying or glorifying terrorism-encroach on expression protected under international human rights law.

An examination of the Aksu List suggests that Xinjiang's Turkic Muslims are presumed guilty until proven innocent. In one case, a man was sent to political education camp because "suspicion [of him] cannot be eliminated and would require further interrogation." The evidence suggests that, consistent with official rhetoric, political education is akin to a form of preventive detention, where people's behaviors are deemed vaguely suspicious but not criminal. They are being held until their loyalty can be ascertained and, as needed, instilled.

Notably, three cases in the Aksu List suggest that people are treated with different levels of "strictness" depending on their level of obedience, and that people who disobey or "talk back" are placed in areas with stricter management. There appear to be three levels: "common management" (普管区), "strict management" (严管区), and "strong management" (强管区). The list also shows that some people are allowed to return home when they are sick (or in one case, breastfeeding), but are sent back to detention once they regain their health.

Human Cogs in the Machine
Previous Human Rights Watch research suggests that the IJOP system's requirements for officials to respond to many perceived abnormalities in people's lives is grueling. In mid-2019, Human Rights Watch was able to speak with an official in the region involved in carrying out the IJOP system. The person said:

From 2016 to mid-2018 we were arresting people. In the beginning we were arresting those who spread terrorism videos, those who receive or give funds to ETIM, [and] those who participated in riots, and we would send them to the local political education centers. Later on ... there were quotas for arrests in all the locales, and so we began to arrest people randomly: people who argue in the neighborhood, people who street fight, drunkards, people who are lazy; we would arrest them and accuse them of being extremists. There was not enough room for them all in the centers, so they built new ones....

In the beginning when the IJOP system came live, if [we] labeled someone as suspicious during evaluation, the local village committee and the police would go and take the person into custody. Later on, we rarely marked someone as suspicious. Often ... we asked them leading questions. Let's say we had to evaluate a person whom the system had lost track of. We'd [go to his home and] ask, "these last few days you were working the fields? You didn't go anywhere?" As long as they said yes, we'd fill out [the form in the app] noting the villager said he was working in the fields, he didn't go anywhere but everything was fine. It was like that for all other verification tasks."

The use of automation-which the authorities claim helps them identify those harboring the "ideological virus" of being disloyal to the Chinese Communist Party in a thorough and "precise" manner-can also lead to sloppy policing. The official said:

[W]e wouldn't be able to finish the many verification tasks if we were to go through them all seriously.... But because we've been working [like this] for so long, whether it is our conscience or that we are tired, right now what's left [among officials] is just grievances and complaints; everyone wants to leave, nobody is doing this work properly.

Mission Creep
Information that has recently come to light from 2018 and 2019 suggests that the IJOP is used not only for picking out targets for detention, as described in the May 2019 Human Rights Watch report, but also to provide data for Xinjiang's larger government information system, that powers a range of government functions. This suggests that the authorities are increasingly sharing personal information across government agencies.

Government reports state that data collected via the IJOP system is also being used for a variety of vetting tasks, from screening applicants for police jobs or public services such as poverty alleviation programs, to picking out model Communist Party members. Neither the initial collection of personal data nor the sharing and use of such data involve asking for consent, illustrating how powerless Xinjiang's residents are.

In Turpan County, for example, officials vet people using the IJOP system to select politically reliable people to take part in a "labor transfer" scheme; a program that involves organizing and transporting groups of Uyghurs to work in factories elsewhere in China under closely supervised, and often coercive, conditions. The same Turpan County scheme also draws on information gathered from " Physicals for All," another compulsory data collection program in which medical and health data is collected.

The integration of the IJOP system with other government systems, illustrates China's expansive definition of security and perceived need for extensive surveillance and control. In Xinjiang, the IJOP system is connected to information databases on second-hand cars, allowing the authorities to "compare information between persons and vehicles in real time, to discover suspicious clues in a timely manner, and to use information technology to effectively eliminate and prevent criminals from using second-hand vehicles to engage in various criminal activities that endanger the safety of society, as a publicly-available Xinjiang Department of Commerce notice says." The notice further explains:

Each automobile trading hall in our region is equipped with ID card recognition devices and video image capture systems to examine the ID cards, residence permits, community certificates, convenient contact card, vehicle information ... of both buyers and sellers, to ensure that the person and their identity match. The information is uploaded to the Xinjiang Traffic Police Headquarters in a timely manner.

There is some preliminary evidence that the IJOP system itself is being used in China outside of Xinjiang. China Electronics Technology Group Corporation (CETC), the same company that built the IJOP in Xinjiang, built an IJOP system in Yinchuan, the capital of Ningxia province, says a procurement document dated January 2020 (for RMB 280.98 million, nearly US$43 million). CETC did not respond to a Human Rights Watch request for comment. Ningxia has the country's highest concentration of ethnic Hui, also a Muslim (though not Turkic) minority. While it is unclear how the system is being used, religious restrictions on Hui Muslims-closing mosques and Arabic-language schools, scrubbing Arabic scripts from Halal restaurants-have been on the rise in Ningxia and other Hui Muslim areas since 2019.

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China: Big Data Program Targets Xinjiang's Muslims

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(New York) - A big data program for policing in China's Xinjiang region arbitrarily selects Turkic Muslims for possible detention, Human Rights Watch said today. A leaked list of over 2,000 detainees from Aksu prefecture provided to Human Rights Watch is further evidence of China's use of technology in its repression of the Muslim population.

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Human test subjects – Nazi Medical Experiments 

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Human test subjects – Nazi Medical Experiments 

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ASHWIN AND KHENG ZHE
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4822534/

Summary:
During Nazi regime, about a minimum of 15,754 documented human experiments were conducted. Almost all of these experiments were highly unethical, with severely harsh conditions and treatment which brought victims to the brink of death.

Pros: Through the research done, Nerve agents such as Tabun and Sarin (which would fuel the development of new insecticides as well as weapons of mass destruction), the antimalarial chloroquine, methadone and methamphetamines, as well as medical research into hypothermia, hypoxia, dehydration and more, were all generated on the back of human experiments in concentration camps. tldr; research created innovations which benefited society.

Cons: Nearly a quarter of confirmed victims were either killed to obtain their organs for research, or died as a result of experiments taking the research subject to the point of death (notoriously, the experiments on freezing and low pressure at Dachau). The euthanasia killings and executions were sources of bodies for research, and the extent that this happened and research conducted before and after the end of the war is still being documented. Of the fully documented victims died 781 died before the end of the war as a result of the experiments: research subjects were weakened by the strain of the experiment such as a deliberate infection or severe cold, or they were deliberately killed because it was feared that they would testify against the perpetrators.

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Highlights

Human experiments were more extensive than often assumed with a minimum of 15,750 documented victims.

Experiments rapidly increased from 1942, reaching a high point in 1943 and sustained until the end of the war.

There were more victims who survived than were killed as part of or as a result of the experiments. Many survived with severe injuries.

Victims came from diverse nationalities with Poles (Jews and Roman Catholics) as the largest national cohort.

Body parts, especially from euthanasia killings, were often retained for research and teaching after 1945.

Keywords: Unethical human experiments, German National Socialism, Holocaust, Jewish victims, Gypsy victims, Mengele, Auschwitz, Concentration camps, Nazi euthanasia

Abstract

There has been no full evaluation of the numbers of victims of Nazi research, who the victims were, and of the frequency and types of experiments and research. This paper gives the first results of a comprehensive evidence-based evaluation of the different categories of victims. Human experiments were more extensive than often assumed with a minimum of 15,754 documented victims. Experiments rapidly increased from 1942, reaching a high point in 1943. The experiments remained at a high level of intensity despite imminent German defeat in 1945. There were more victims who survived than were killed as part of or as a result of the experiments, and the survivors often had severe injuries.

Keywords: Unethical human experiments, German National Socialism, Holocaust, Jewish victims, Gypsy victims, Mengele, Auschwitz, Concentration camps, Nazi euthanasia

Background

The coerced human experiments and research under National Socialism constitute a reference point in modern bioethics. Yet discussions of consent and the need for safeguards for research subjects to date lack a firm basis in historical evidence. There has been no full evaluation of the numbers of victims of Nazi research, who the victims were, and of the frequency and types of experiments and research. The one partial estimate is restricted to experiments cited at the Nuremberg Medical Trial. This paper gives the first results of a comprehensive evidence-based evaluation of the different categories of victims. In 1945 liberated prisoners from German concentration camps began to collect evidence of the experiments.

The scientific intelligence officer John Thompson then pointed out not only that 90% of all medical research under National Socialism was criminal, but also the need to evaluate all criminal experiments under National Socialism, and not just those whose perpetrators were available for arrest and prosecution. The Nuremberg Medical Trial of 1946-47 was necessarily selective as to who was available for prosecution, and since then only clusters of victims have been identified. In the early 1980s Günther Schwarberg named a set of child victims: his reconstruction the life histories of the 'twenty children' killed after transport from Auschwitz for a tuberculosis immunisation experiment at Neuengamme concentration camp was exemplary. The question arises whether what Schwarberg achieved in microcosm can be achieved for the totality of victims. Our aim is to identify not just clusters of victims but all victims of unethical medical research under National Socialism. The methodology is that of record linkage to reconstruct life histories of the total population of all such research victims. This allows one to place individual survivors and groups of victims within a wider context.

This project on the victims of Nazi medical research represents the fulfilment of Thompson's original scheme of a complete record of all coerced experiments and their victims. Our project identifies for the first time the victims of Nazi coercive research, and reconstructs their life histories as far as possible. Biographical data found in many different archives and collections is linked to compile a full life history, and subjective narratives and administrative data are compared. Results are aggregated here as cohorts because of undertakings as regards anonymisation, given in order to gain access to key sources. All data is verifiable through the project database.

The criterion for unethical research is whether coercion by researchers was involved, or whether the location was coercive. The project has covered involuntary research in clinical contexts as psychiatric hospitals, incarceration in concentration camps and prisoner of war camps, the 'euthanasia' killings of psychiatric patients with subsequent retention of body parts for research, and executions of political victims, when body parts were sent to university anatomical institutes, and persons subjected to anthropological research in coercive and life threatening situations as ghettoes and concentration camps.

Without a reliable, evidence-based historical analysis, compensation for surviving victims has involved many problems. Victim numbers have been consistently underestimated from the first compensation scheme in 1951 when the assumption was of only few hundred survivors. The assumption was that most experiments were fatal. This project's use of several thousand compensation records in countries where victims lived (as Poland) or migrated to (as Israel), or were collected by the United Nations or the German government has corrected this impression. The availability of person-related evidence from the International Tracing Service at Bad Arolsen further helps to determine whether a victim survived. Major repositories of documents like the United States Holocaust Memorial Museum and the Yad Vashem archives, court records in war crimes proceedings, and oral history collections notably the Shoah Foundation have been consulted. Record linkage of named records is essential for the project, and shows how a single person could be the victim of research on multiple occasions. Father Leon Michałowski, born 22 March 1909 in Wąbrzeźno, was subjected to malaria in August 1942 and then to freezing experiments in October 1942 ().

A further issue relates to the methods and organisation of the research. From the 1950s the experiments were viewed as 'pseudo-science', in effect marginalising them from mainstream science under National Socialism. For the purpose of this study, the experiments have been viewed as part of mainstream German medical research, as this renders rationales and supportive networks historically intelligible. It is clear that prestigious research institutions such as the Kaiser Wilhelm Society and funding agencies such as the German Research Fund were involved. It has been argued more recently that some experiments were cutting edge science. Another view is that the approach and methods were scientific albeit of varying quality. For the purpose of this study, the experiments have been viewed as part of mainstream German medical research, as this renders rationales and supportive networks intelligible.

Defining what constitutes research is problematic. For example, a listing of operations in a concentration camp may be nothing more than a clinical record, may have been undertaken by young surgeons seeking to improve their skills, or may indeed have involved research. As stated above, only confirmed data of research has been utilised in the project's category of a verified instance of unethical research. The only exception is the corpses sent to anatomical institutes for research purposes. Separating these out often does not appear possible, but the project includes anatomical research on body parts and brains as separate categories.

The project has graded victim evidence into two categories, so that there should be a set of verifiable and proven victims established as incontestable evidence of having been a victim. The unexpectedly high numbers of identified experiment victims makes this necessary. The two categories are:

those who were identified as confirmed victims through a reliable source such as experimental records kept at the time.

those who have claimed to have been experimented on, but confirmation could not so far be obtained.

The project did not set out to adjudicate on the authenticity of victims' claims. In Warsaw ca. 3600 compensation files of victims of human experiments were viewed, while there are a further 10,000 files representing claims deemed unsuccessful. It is sometimes unclear whether extensive injuries were retrospectively defined to have resulted from an experiment to meet the criteria of the compensation scheme offered by the Federal Republic of Germany in various forms since 1951, or whether experimentation had taken place in a hitherto unknown location. The project discounted claims of abuse when no experiment or research was involved, or when victims having misunderstood compensation schemes for experiments being about 'experiences'. It is hoped that further research will provide confirmation of experiments in disputed locations like the concentration camps of Stutthof and Theresienstadt. While Yugoslav victims were abused for experiments in German concentration camps, claims for experiments in the former Yugoslavia and Northern Norway have not so far been confirmed. The grading of victims' claims into the verified and as yet unverified enable the project to establish verifiable minimum numbers, while indicating the possibility of higher numbers being confirmed by further research.

Project findings

The project is able to present results on: how many victims were killed in the course of the experiment, how many died from the consequences of the experiment or were killed as potential evidence of Nazi criminality, and how many survived? The project has covered experiments, as the most notorious experiments taken to the point of death and supported by the SS in concentration camps, as well as dispersed experiments in a variety of clinical contexts, particularly on psychiatric patients. Some sets of experiments and locations, not least those sponsored by German pharmaceutical companies remain shadowy, and require more detailed research possibly on the basis of further disclosure of documents held in company archives. The extent of involvement of German pharmaceutical companies like that of IG-Farben (using the branded product names of 'Bayer', 'Hoechst' and 'Behringwerke') remains contentious. The company supplied Helmuth Vetter with samples for experiments at Auschwitz and Mauthausen. Similarly problematic is the extent that Schering-Kahlbaum supported Clauberg's uses of X-ray contrast fluids and a substance to seal the fallopian tubes at Auschwitz. Initially, Clauberg asked for deliveries to his clinic at Königshütte (so making the experiments appear as taking place in a consensual clinical context), but later on to Auschwitz. The extent that the company's senior staff knew that their employee and Clauberg's pharmaceutical assistant Johannes Goebel worked at Auschwitz is contentious ().

The occurrence of unethical research provides insight into the structure of Nazi medical research. The project traced how Nazi coercive research began in the context of eugenic research in the mid-1930s. After numbers of experiments dipped in 1940 due to military call-up of medical researchers, the research rapidly intensified both in terms of numbers of experiments and victims, and in terms of severity for victims. This can be seen from 1942 with the notorious and often fatal experiments on low pressure, exposure to freezing temperatures, and infectious diseases when research could be taken to the point of death. Pharmacological experiments on therapies for tetanus, typhus and typhoid were spurred by the realisation that Allied military medical research on infectious diseases was outstripping German military medical expertise. From November 1942 racial priorities came increasingly to the fore, as exemplified by Schumann's X-ray sterilisation experiments on Jews in Auschwitz.

Victims were a highly international group. The above table () shows numbers of nationalities, using nationality as in 1938. The table indicates the distribution of nationalities. The largest national group, that of Polish victims, includes both Roman Catholics and Jews. There were high numbers of German and Austrian victims, in part as a result of the experiments and dissections that accompanied the killing of psychiatric patients. While there were other large groups, there are also smaller national groups, as Swiss, British and Irish, all highly remarkable in how their citizens became caught up in the experimentation. We find victims include a Swiss conscientious objector used for malaria experiments at Dachau, and British commandos captured in Norway used for amphetamine and high performance experiments on the shoe track at Sachsenhausen, and subsequently executed.

Statistics on gender indicate a proportion of male to female of approximately 2:1 (). One possible reason is the high number of military experiments as related to infectious diseases. Another is that more men than women were held in concentration camps, so that there was a higher male availability in the predominately male camps. In Ravensbrück the situation was reversed with the large female camp and a small male compound ().

While for most nationalities male victims were the majority, in the case of certain national groups, female victims were in the majority. This is the case for victim groups from the Netherlands (in the case of sterilisation at Auschwitz), and Greece (for the Jewish skeleton collection). Children were often victims of experiments in psychiatric clinics. Later in the war, Roma and Jewish children were targeted for research by Mengele in Auschwitz.

The statistics show the age distribution was the same for men and women. While there was a very wide age spectrum, the peak is of victims born in 1921, so in their early twenties at the time of the experiment (). Several hundred Jewish children were held by Mengele for twin research, and batches of Jewish children were dispatched for hepatitis and tuberculosis research, and body parts of small children were retained by psychiatric researchers.

Ethnicity and religion have been recorded, as for the definitively confirmed experiment victims (). Here, one is thrown back on the categories imposed by the Nazis. Thus a victim of the Jewish skeleton collection for the anatomy department at Strasbourg was baptised Protestant. Generally, the Nazis used the generic and stigmatising term of 'Zigeuner' or gypsy rather than the self-identifying terms of 'Sinti' and 'Roma'.

In addition to the experiment victims are Roma and Sinti victims of large scale anthropological investigations of Ritter, Justin, and Ehrhardt, amounting to at least a further 21,498 persons ().

If however one takes the year 1943 we find a higher proportion of Jewish victims, in part because of the intensification of experiments on Jews (particularly on women and children) at Auschwitz and Auschwitz-Birkenau. This would again indicate that there was an intensification of racial research ().

Victim number indicates how from 1942 onwards there was an overall intensification of research ().

The life history approach allows appraisal of both experiments and victim numbers over time. The period 1933-39 shows sporadic experimentation in the context of racial hygiene. Mixed race adolescents were sterilised and evaluated by anthropologists. The concerns of racial hygiene with mental illness explain why psychiatrists and neurologists conducted experiments in psychiatric institutions. The psychiatrist Georg Schaltenbrand pointed out that his neurological research subjects were transferred to other institutions, many as we now know to be killed. This interrupted his research on the transmissibility of multiple sclerosis. The numbers of brains and body parts increased. From 1942 onwards there was an overall intensification of research.

The chart () shows when experiments started, but not the distribution of victims over time.

The largest series of experiments were for infectious diseases. Malaria research at Dachau between 1942 and 1945 had 1091 confirmed victims, and after infection different combinations of drugs were tested. These experiments by Schilling began in 1942 and remarkably Schilling tried to continue the research after the liberation of the camp.

He pleaded at his trial to be allowed to continue the research, albeit on volunteers. The highest numbers were in 1943. The momentum continued even though the war was clearly lost. Other large groups included the twins researched on by Mengele, and to date 618 individuals are known ().

The overall findings provide an accurate basis for analysis of experiments to date. First, nearly a quarter of confirmed victims were either killed to obtain their organs for research, or died as a result of experiments taking the research subject to the point of death (notoriously, the experiments on freezing and low pressure at Dachau). The euthanasia killings and executions were sources of bodies for research, and the extent that this happened and research conducted before and after the end of the war is still being documented. Of the fully documented victims died 781 died before the end of the war as a result of the experiments: research subjects were weakened by the strain of the experiment such as a deliberate infection or severe cold, or they were deliberately killed because it was feared that they would testify against the perpetrators ().

While, most subjects survived, amounting to 24,010 persons, many had severe physical disabilities with life-long consequences.

Conclusion

The analysis presented here shows that several types of unethical medical research occurred under National Socialism. Not only were large numbers of victims affected, but also overall, numbers of surviving victims were far higher than anticipated. The survivors were often seriously disabled and handicapped for the remainder of their lives. The experiments gained in numbers with the war and the implementation of the Holocaust, and were sustained at a high level of intensity despite imminent defeat.

One issue arising is that body parts of deceased victims were retained by medical research and teaching institutes, notably for anatomy and brain research. While there was meant to be full disclosure of specimens deriving from euthanasia victims and executed persons by 1990, specimens continue to be identified. The complex data is to be further augmented and refined, the history of specimens retained for research during and after WW2 is being documented, and the narratives of survivors analysed in order to understand more fully the consequences of coerced research. This research provides a basis in historical evidence for discussions of the ethics of coerced medical research.

Acknowledgments

Wellcome Trust Grant No 096580/Z/11/A on research subject narratives.

AHRC GRANT AH/E509398/1 Human Experiments under National Socialism.

Conference for Jewish Material Claims Against Germany Application 8229/Fund SO 29.

Footnotes

⁷Annas G, Grodin M. The Nazi Doctors and the Nuremberg Code. New York: Oxford University Press; 1992; Weindling P. Nazi Medicine and the Nuremberg Trials: From Medical War Crimes to Informed Consent. Basingstoke: Palgrave Macmillan; 2000.

⁸Weindling P. John Thompson (1906-1965): Psychiatrist in the Shadow of the Holocaust. Rochester: Rochester University Press; 2010.

⁹Klee E. Auschwitz, die NS-Medizin und ihre Opfer. Frankfurt am Main: S. Fischer Verlag; 1997; Mitscherlich A, Mielke F. Wissenschaft ohne Menschlichkeit. Heidelberg: Lambert Schneider; 1949. See also Schwarberg G. The Murders at Bullenhuser Damm: The SS Doctor and the Children. Bloomington: Indiana University Press; 1984.

¹⁰Lang H-J. Die Namen der Nummern: Wie es gelang, die 86 Opfer eines NS-Verbrechens zu identifizieren. Hamburg: Hoffmann und Campe; 2004.

¹¹Brody H, Leonard S, Nie J-B, Weindling P. United States Responses to Japanese Wartime Inhuman Experimentation after World War II: National Security and Wartime Exigency. Cambridge Quarterly of Healthcare Ethics 2014; 23: 220-230.

¹²Baumann S. Menschenversuche und Wiedergutmachung. München: Oldenbourg; 2009.

¹³Schwerin A von. Experimentalisierung des Menschen: Der Genetiker Hans Nachtsheim und die vergleichende Erbpathologie 1920-1945. Göttingen: Wallstein Verlag; 2004; Schmuhl H-W. The Kaiser Wilhelm Institute for Anthropology, Human Heredity and Eugenics, 1927-1945: Crossing Boundaries. Dordrecht: Springer; 2008.

¹⁴Roelcke V. Fortschritt ohne Rücksicht, In: Eschebach I, Ley A. eds. Geschlecht und "Rasse" in der NS-Medizin. Berlin: Metropol Verlag; 2012: 101-114.

¹⁵Hildebrandt S. Anatomy in the Third Reich: An outline, Part 1. National Socialist politics, anatomical institutions, and anatomists. Clinical Anatomy 2009; 22: 883-893.

¹⁶Hunt N. The Soviet Experience of Nazi Medicine: Statistics, Stories and Stereotypes. MPhil thesis, Oxfrod Brookes University; 2011; and Loewenau A. The impact of Nazi medical experiments on Polish inmates at Dachau, Auschwitz and Ravensbück. PhD thesis, Oxford Brookes University; 2012.

¹⁷Weindling, P. Victims and Survivors of Nazi Human Experiments: Science and suffering in the Holocaust. London: Bloomsbury; 2014.

¹⁸ www.die-namen-der-nummern.de/html/the_names.html (accessed 8 October 2014).

¹⁹Eckart WU, Vondra H. Malaria and World War II: German malaria experiments 1939-45. Parassitologia 2000; 42:53-58.

²⁰Loewenau A. Die "Kaninchen" von Ravensbrück: Eine Fotogeschichte. In: Eschebach I, Ley A eds. Geschlecht und "Rasse" in der NS-Medizin. Berlin: Metropol Verlag; 2012:115-140.

²¹Weindling P. "Cleansing" Anatomical Collections: The Politics of Removing Specimens from German Anatomical and Medical Collections 1988-92. Annals of Anatomy 2012; 194:237-242.

# data[].attributes.attachment_link.title
The victims of unethical human experiments and coerced research under National Socialism

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There has been no full evaluation of the numbers of victims of Nazi research, who the victims were, and of the frequency and types of experiments and research. This paper gives the first results of a comprehensive evidence-based evaluation of the different ...

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Satellite Technologies in Emergency Response 

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Satellite Technologies in Emergency Response 

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[kaleb &kaixin]

https://www.youtube.com/watch?v=7XsviBxbLvI
https://time.com/5509993/nootropics-smart-drugs-brain/

Summary
Nootropics or “smart drugs,” are a class of substances that can boost brain performance. They are sometimes called cognition enhancers or memory enhancing substances. ~MedicalNewsToday
^ Some nootropics are often used as medications, as they are known for their stimulant effects that counteract symptoms of medical conditions like attention deficit hyperactivity disorder (ADHD), narcolepsy, or Alzheimer’s disease.
A particular common nootropic is one that is found in most people's coffee every morning: caffeine.

Pros

Cons

Controversies

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Nootropics, or 'Smart Drugs,' Are Gaining Popularity. But Should You Take Them?

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The research on these pills and supplements is intriguing, but inconclusive. Here's what the science says about nootropics, or smart drugs.

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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:
- Biased 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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Winwin Tom Yuanhao
https://americanpregnancy.org/getting-pregnant/infertility/in-vitro-fertilization/
https://my.clevelandclinic.org/health/articles/23186-gestational-surrogacy

Summary
Gestational surrogacy is when a person carries and gives birth to a baby for another person or couple. It’s usually done through IVF (in vitro fertilization). The person who carries the pregnancy has no genetic relation to the baby.

Pros

Cons

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

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

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Clinical Trials for Vaccine Development 

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Clinical Trials for Vaccine Development 

# data[].attributes.body
Audrey and runxi

Summary
Bionic implants refer to electronic or mechatronic parts that augment or restore physical functionality to a differently-abled person.
Prosthetics is an artificial device that replaces a missing body part, which may be lost through trauma, disease, or a condition present at birth (congenital disorder). Prostheses are intended to restore the normal functions of the missing body part.
Pros
- Bionic limbs eases the attachment and removal of prosthesis. It also provides a much more comfortable sitting position as well as allows a much larger range of movements, increasing motion.
- Prosthetics allows people that have missing body parts function in society. It helps amputee take care of necessary daily activities such as eating, walking and being able to get dressed on their own.
- Having a prosthetic to fill out clothes and allow for more natural movements can make a big difference for those who are feeling self-conscious about their appearance. The result for these people can be greater self-esteem and confidence when doing everyday activities.

Cons and Limitations
- Prosthetics can cause skin irritation at the sight where they are fitted, and most patients undergo some level of physical therapy as they get used to using the new device.
- Bionic implants and prosthetics are expensive and may not be covered by insurance. Hence, people of low-income family may not be able to afford it, increasing inequity.
- Bionic limbs can potentially cause issues with implant stability, bone fracture, breakage of the implant parts and infection.

Controversies
For some, that might seem a slightly unsettling idea. Obviously, wearable robotics and bionic implants could have multiple benefits as medical devices, such as for improving prosthetics. But beyond that, bionics and wearable robotics could potentially enhance people’s capabilities in the workplace and boost productivity.

Given such rapid advances, Prof Makin said the question arises about how the human body and brain adapt to and assimilate these devices. ‘I was feeling like a big chunk that’s often left out of this discussion is how the brain and cognition of users will relate to an artificial body part,’ she said.

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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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Charlotte shermaine yuetong

Summary:

Pros: Enhanced soldiers are able the endure harsher conditions, get tired less easily and are more resilient.

Cons:

Controversies: soldiers might not have consent towards the potentially risky treatment.

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3D bio-printing (human tissues, organs) 

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3D bio-printing (human tissues, organs) 

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Dylan, Nishanth, Jun Wei

Summary:
3D bioprinting is an additive manufacturing process where organic and biological materials such as living cells and nutrients are combined to create artificial structures that imitate natural human tissues.

In other words, bioprinting is a type of 3D printing that can potentially produce anything from bone tissue and blood vessels to living tissues for various medical applications, including tissue engineering and drug testing and development.

Pros
-Bioprinting may be used to increase human performance, strength, speed, or endurance. For instance, bioprinting may be used to manufacture enhanced bones and replace regular human bones that are stronger and more flexible. The 3D printer could also be used to increase muscle performance by making muscles more "resilient and less likely to become fatigued". Lung capacity could also be improved by replacing it with an artificial lung that can increase oxygen efficiency in the blood.
-Bioprinting could create a culture without disease or imperfection.

Cons:
- Design inaccuracies that may lead to the production of poor quality organs or biomaterial that may cause harm to the acceptor of the bio-printed material.

- It limits genetic diversity: Bioengineering has also been blamed for the diminishing genetic diversity that is being experienced across the world. This may render some species extinct before their time.

- The research is insufficient: The research around Bioengineering has not been vast or sufficient enough to give conclusive results, especially in cases where animals are concerned.

- May lead to allergic reactions: In creating organic foods, Bioengineering may result in other types of foods that react with the body. This ends up being counter-productive as far as the research is concerned.

- It is irresponsible because many embryos die as a result of bioengineering: Some people have argued that Bioengineering is irresponsible because, in order to get the desired results, many embryos being subjected to tests end up dying.

Controversies:
These are expensive technoscientific solutions likely to benefit only a few members of a particular subgroup. Therefore, 3D bioprinting is another solution that will not be a game-changer for everyone and certainly not for most in its immediate applications. Despite the promise of organs printed on demand for all, it is likely that the spectre of a ‘social stratification of bio-fabrication’ will emerge, with those who can afford to pay for their ‘own’ organs benefitting. A tiered system of therapeutic organ replacement is likely with those who can afford to pay for self-organs living longer; perhaps enjoying a significantly high quality of life avoiding the negative physical consequences of taking immune-suppressant drugs. While others will wait until a human organ donor becomes available and then have to undertake a punishing drug regime for the rest of their lives to prevent episodes of rejection of the transplanted organ. Others who cannot afford to pay then will make do with ‘second-hand’ organs from another living or deceased donor once available (as is the current system).

Essay question:

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What Is 3D Bioprinting? - Simply Explained | All3DP

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All3DP is an editorially independent publication. Editorial content, on principle, can not be bought or influenced. To keep All3DP free and independent, we finance ourselves through advertising and affiliate revenues. When you purchase using a shopping link on our site we earn an affiliate commission. Learn more Please activate JavaScript to read this article.

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Clinical Trials for Vaccine Development 

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Clinical Trials for Vaccine Development 

# data[].attributes.body
Jovan and Aden
Summary

Bionic limbs are artificial limbs that work using signals from an individual's muscles to move seamlessly, while prosthetic limbs are artificial limbs that require an individual's body power to move
Pros
bionic vs prosthetics?
Bionic implants ease attachment and removal of the prosthesis. It also provides a much more comfortable sitting position and allows a much larger range of movements. There is overwhelming evidence that bionic limbs attached to osseointegrated implants significantly improve mobility
Cons
cons of bionic implants?
Bionic limbs can potentially cause issues with implant stability, bone fracture, breakage of the implant parts and infection. All these adverse events have several common negative effects. They cause pain. They significantly disturb the lifestyle because they limit the usage of the prosthesis for a prolonged duration

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Jenson & Dylan R
https://youtu.be/jAhjPd4uNFY

Summary: CRISPR, also known as Clustered Regularly Interspaced Short Palindromic Repeats, is a genetic engineering technology that utilises enzymes called Cas9 to disrupt, delete and reconnect DNA strands which allows for unique mixtures of beneficial traits to be inherited by the new DNA strands. Common uses of CRISPR is in agriculture to form pest or climate resistant crops, or to increase yield or nutritional value of crops, and in healthcare, where this gene editing is used to treat genetic illnesses like sickle cell anemia or cystic fibrosis

Pros:
- Cheaper way to treat virus infection. As shown in the video, by injecting CRISPR into a rat's body, it is able to eradicate 50% of HIV virus in the rat's cells
- Cure for hard to cure or incurable diseases like cancera and genetic diseases
- improve yield of crop production by genetically modifying them with traits to improve its survivability - pest-resistant, extreme climates, low-nutrient needs

Cons:
Unequal access to the technology will lead to bigger gap between the rich and poor. The rich can continously ensure that their generation are genetically modified to improve their knowledge, abilities, healthiness, and many more.

Widen military gap between countries due to possibly of making superhuman or bioweapon to edit genes of the enemy

Controversial:
Genetically modifications to human embryos and reproductive cells such as eggs and sperms are called germline editing. Changes to the germline can be passed to the next generation. Hence, there is a controversy on which gene is ethical to be edited

The United States and the United Kingdom are testing the water by considering exemptions in the case of monogenic hereditary disorders such as muscular dystrophy, cystic fibrosis, and Huntington’s disease

Random GP question: Should the use of genetic technology be more widespread

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Apple AirTags a 'perfect stalking tool' - BBC News

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The eventual goal is to be able to identify a target within five seconds based on their cardiac signal, or 'heartprint.' At the moment, however, the Pentagon's system has a number of limitations: the target needs to be standing still, needs to be wearing light clothing (thick clothing, like a heavy coat, can interfere with the signal), and most importantly there needs to be a clear line of sight between the laser and the target.

Coats, walls, even rocks and rubble are no obstacle for another nascent surveillance technology, however. Researchers are hard at work developing radar-based systems capable of tracking vital signs for a range of purposes, from non-invasive monitoring of patients and aiding in medical diagnoses to finding survivors in search and rescue operations.

Monitoring indoor movements

But why bother installing new radars when we're already bathed in a different sort of radiation pretty much all the time? Wi-Fi can also be used to locate individuals, identify their position in the room and whether they're sitting or standing, and even track vital signs.

Until recently, it was thought a dedicated Wi-Fi network was required, in part because the technique depends on knowing the exact position of the Wi-Fi transmitters. In 2018, however, a group of researchers at the University of California built an app which allowed them to figure out the exact location of existing Wi-Fi transmitters in a building. With that information, they were able to use normal smartphones and existing ambient Wi-Fi networks to detect human presence and movement from outside the room. "With more than two Wi-Fi devices in a regular room, our attack can detect more than 99 per cent of user presence and movement in each room tested," the researchers claim.

Some research groups want to go further than just using Wi-Fi to identify people. Based on movement and vital signs, they claim it is possible to monitor the subject's emotional state and analyse their behavioural patterns. These researchers have formed a company to market a 'touchless sensor and machine learning platform for health analytics', which they claim has been deployed in over 200 homes and is being used by doctors and drug companies.

Beyond the potential benefits for healthcare and emergency responders, however, the technology also has obvious applications for surveillance. Technology which is capable of building up a profile of a person's heartbeat and breathing in order to watch for abnormalities in a health context is readily adaptable to being used to identify one person from another. Radar-based security surveillance systems capable of detecting people are already on the market, It's only a matter of time, and perhaps not even very much time, before the ability to identify individual people is layered on top.

Tracking your microbial cells

Every person emits around 36 million microbial cells per hour, and human microbiomes are unique for a certain period of time (a 2015 study found that around 80 per cent of people could be re-identified using their microbiome up to a year later). This means that the constant trail of microbial traces we leave behind us, as well as those we pick up from our surroundings, can be used to help reconstruct a picture of a person's activities and movements, like where they walked, what objects they touched and what environments they have been in.

Monitoring your scent

Identifying people by smell is actually one of the oldest police tricks in the book, but doing it with computers instead of bloodhounds is still in its infancy in comparison with facial and fingerprint recognition. The field of odor biometrics may be useful for individual authentication but is not well suited to mass surveillance - separating exactly who smells like that in a crowd can be tricky, as anyone who has been stuck in public transport on a hot day probably knows.

Bum detection

Then there are the identification techniques designed for very specific use cases. One pioneering suggestion from a team of Japanese researchers for an anti-theft system for cars was based on using 360 sensors to measure the unique shape of the driver's rear end. Despite achieving a 98 per cent accuracy rate in trials, tragically this important security innovation does not seem to have gone any further than lab testing.

The regulation problem

Trying to regulate surveillance technologies one by one is likely to be futile. The surveillance industry is simply developing too fast, and it is too easy to switch from one kind of surveillance to another. The difference between a facial recognition system and one based on behavioural biometrics may simply be a matter of swapping the software on an existing camera network, for example.

Increasing cooperation between government agencies and the private sector also means that regulations like San Francisco's, which limits only government use of certain types of surveillance, are insufficient according to Katina Michael, a professor in the School for the Future of Innovation in Society and School of Computing, Informatics and Decision Systems Engineering at Arizona State University.

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New surveillance tech means you'll never be anonymous again

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The eventual goal is to be able to identify a target within five seconds based on their cardiac signal, or 'heartprint.' At the moment, however, the Pentagon's system has a number of limitations: the target needs to be standing still, needs to be wearing light clothing (thick clothing, like a heavy coat, can interfere with the signal), and most importantly there needs to be a clear line of sight between the laser and the target.

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How China’s Surveillance Is Growing More Invasive | Visual Investigations

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