Standing in solidarity with the Palestinian people

We at the Racism and Technology Center stand in solidarity with the Palestinian people. We condemn the violence enacted against the innocent people in Palestine and Israel, and mourn alongside all who are dead, injured and still missing. Palestinian communities are being subjected to unlawful collective punishment in Gaza and the West Bank, including the ongoing bombings and the blockade of water, food and energy. We call for an end to the blockade and an immediate ceasefire.

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Setting the record straight: Scientists show that the algorithm that Proctorio used is incredibly biased towards people with a darker skin colour

Do you remember when our Robin Pocornie filed a complaint with the Dutch Human Rights Institute because Proctorio, the spyware that she was forced to use as a proctor for doing her exams from home, couldn’t find her face as it was “too dark”? (If not, read the dossier of her case.)

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Easily developed facial recognition glasses outline how underprepared we are for privacy violations

Two engineering students, Caine Ardayfio and AnnPhu Nguyen, at Harvard University developed real-time facial recognition glasses. They went testing it out on passengers in the Boston subway, and easily identified a former journalist and some of his articles. A great way to produce small-talk conversations of break the ice – you might think.

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Racist Technology in Action: AI detection of emotion rates Black basketball players as ‘angrier’ than their White counterparts

In 2018, Lauren Rhue showed that two leading emotion detection software products had a racial bias against Black Men: Face++ thought they were more angry, and Microsoft AI thought they were more contemptuous.

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Dutch Higher Education continues to use inequitable proctoring software

In October last year, RTL news showed that Proctorio’s software, used to check if students aren’t cheating during online exams, works less for students of colour. Five months later, RTL asked the twelve Dutch educational institutions on Proctorio’s client list whether they were still using the tool. Eight say they still do.

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Automating apartheid in the Occupied Palestinian Territories

In this interview, Matt Mahmoudi explains the Amnesty report titled Automating Apartheid, which he contributed to. The report exposes how the Israeli authorities extensively use surveillance tools, facial recognition technologies, and networks of CCTV cameras to support, intensify and entrench their continued domination and oppression of Palestinians in the Occupied Territories (OPT), Hebron and East Jerusalem. Facial recognition software is used by Israeli authorities to consolidate existing practices of discriminatory policing and segregation, violating Palestinians’ basic rights.

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Judgement of the Dutch Institute for Human Rights shows how difficult it is to legally prove algorithmic discrimination

On October 17th, the Netherlands Institute for Human Rights ruled that the VU did not discriminate against bioinformatics student Robin Pocornie on the basis of race by using anti-cheating software. However, according to the institute, the VU has discriminated on the grounds of race in how they handled her complaint.

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Proctoring software uses fudge-factor for dark skinned students to adjust their suspicion score

Respondus, a vendor of online proctoring software, has been granted a patent for their “systems and methods for assessing data collected by automated proctoring.” The patent shows that their example method for calculating a risk score is adjusted on the basis of people’s skin colour.

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Al Jazeera asks: Can AI eliminate human bias or does it perpetuate it?

In its online series of digital dilemmas, Al Jazeera takes a look at AI in relation to social inequities. Loyal readers of this newsletter will recognise many of the examples they touch on, like how Stable Diffusion exacerbates and amplifies racial and gender disparities or the Dutch childcare benefits scandal.

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France wants to legalise mass surveillance for the Paris Olympics 2024: “Safety” and “security”, for whom?

Many governments are using mass surveillance to support law enforcement for the purposes of safety and security. In France, the French Parliament (and before, the French Senate) have approved the use of automated behavioural video surveillance at the 2024 Paris Olympics. Simply put, France wants to legalise mass surveillance at the national level which can violate many rights, such as the freedom of assembly and association, privacy, and non-discrimination.

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Attempts to eliminate bias through diversifying datasets? A distraction from the root of the problem

In this eloquent and haunting piece by Hito Steyerl, she weaves the ongoing narratives of the eugenicist history of statistics with its integration into machine learning. She elaborates why the attempts to eliminate bias in facial recognition technology through diversifying datasets obscures the root of the problem: machine learning and automation are fundamentally reliant on extracting and exploiting human labour.

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Dutch Institute for Human Rights: Use of anti-cheating software can be algorithmic discrimination (i.e. racist)

Dutch student Robin Pocornie filed a complaint with Dutch Institute for Human Rights. The surveillance software that her university used, had trouble recognising her as human being because of her skin colour. After a hearing, the Institute has now ruled that Robin has presented enough evidence to assume that she was indeed discriminated against. The ball is now in the court of the VU (her university) to prove that the software treated everybody the same.

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Dutch student files complaint with the Netherlands Institute for Human Rights about the use of racist software by her university

During the pandemic, Dutch student Robin Pocornie had to do her exams with a light pointing straight at her face. Her fellow students who were White didn’t have to do that. Her university’s surveillance software discriminated her, and that is why she has filed a complaint (read the full complaint in Dutch) with the Netherlands Institute for Human Rights.

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Racist Technology in Action: Uber’s racially discriminatory facial recognition system firing workers

This example of racist technology in action combines racist facial recognition systems with exploitative working conditions and algorithmic management to produce a perfect example of how technology can exacarbate both economic precarity and racial discrimination.

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Racist Technology in Action: Proctoring software disadvantaging students of colour in the Netherlands

In an opinion piece in Parool, The Racism and Technology Center wrote about how Dutch universities use proctoring software that uses facial recognition technology that systematically disadvantages students of colour (see the English translation of the opinion piece). Earlier the center has written on the racial bias of these systems, leading to black students being excluded from exams or being labeled as frauds because the software did not properly recognise their faces as a face. Despite the clear proof that Procorio disadvantages students of colour, the University of Amsterdam has still used Proctorio extensively in this June’s exam weeks.

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Racist Technology in Action: Amazon’s racist facial ‘Rekognition’

An already infamous example of racist technology is Amazon’s facial recognition system ‘Rekognition’ that had an enormous racial and gender bias. Researcher and founder of the Algorithmic Justice League Joy Buolawini (the ‘poet of code‘), together with Deborah Raji, meticulously reconstructed how accurate Rekognition was in identifying different types of faces. Buolawini and Raji’s study has been extremely consequencial in laying bare the racism and sexism in these facial recognition systems and was featured in the popular Coded Bias documentary.

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Online proctoring excludes and discriminates

The use of software to automatically detect cheating on online exams – online proctoring – has been the go-to solution for many schools and universities in response to the COVID-19 pandemic. In this article, Shea Swauger addresses some of the potential discriminatory, privacy and security harms that can impact groups of students across class, gender, race, and disability lines. Swauger provides a critique on how technologies encode “normal” bodies – cisgender, white, able-bodied, neurotypical, male – as the standard and how students who do not (or cannot) conform, are punished by it.

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