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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Late Night Talks: Studenten slepen universiteit voor de rechter vanwege discriminerende AI-software

Vrije Universiteit Amsterdam student Robin Pocornie en Naomi Appelman, co-founder van non-profitorganisatie Racism and Technology Center, gaan met elkaar in gesprek over discriminatie binnen kunstmatige intelligentie (artificial intelligence). Wat zijn de voor- en nadelen van kunstmatige intelligentie en in hoeverre hebben we grip en hoe kunnen we discriminatie tegengaan in de snelle ontwikkelingen van technologie?

By Charisa Chotoe, Naomi Appelman and Robin Pocornie for YouTube on December 3, 2023

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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Waarom we zwarte vrouwen meer zouden moeten geloven dan techbedrijven

Stel je voor dat bedrijven technologie bouwen die fundamenteel racistisch is: het is bekend dat die technologie voor zwarte mensen bijna 30 procent vaker niet werkt dan voor witte mensen. Stel je vervolgens voor dat deze technologie wordt ingezet op een cruciaal gebied van je leven: je werk, onderwijs, gezondheidszorg. En stel je tot slot voor dat je een zwarte vrouw bent en dat de technologie werkt zoals verwacht: niet voor jou. Je dient een klacht in. Om vervolgens van de nationale mensenrechteninstantie te horen dat het in dit geval waarschijnlijk geen racisme was.

By Nani Jansen Reventlow for Volkskrant on October 22, 2023

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

Today, 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, the VU has discriminated on the grounds of race when handling her complaint.

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Uitspraak College voor de Rechten van de Mens laat zien hoe moeilijk het is om algoritmische discriminatie juridisch te bewijzen

Vandaag heeft het College van de Rechten van de Mens geoordeeld dat de VU de student bioinformatica Robin Pocornie niet heeft gediscrimineerd op basis van ras door de inzet van antispieksoftware. Wel heeft de VU verboden onderscheid op grond van ras gemaakt bij de klachtbehandeling.

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Zwarte mensen vaker niet herkend door antispieksoftware Proctorio

Gezichten van mensen met een zwarte huidskleur worden veel minder goed herkend door tentamensoftware Proctorio, blijkt uit onderzoek van RTL Nieuws. De software, die fraude moet herkennen, zoekt bij online tentamens naar het gezicht van een student. Dat zwarte gezichten beduidend slechter worden herkend, leidt tot discriminatie, zeggen deskundigen die het onderzoek van RTL Nieuws beoordeelden.

By Stan Hulsen for RTL Nieuws on October 7, 2023

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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GPT detectors are biased against non-native English writers

The rapid adoption of generative language models has brought about substantial advancements in digital communication, while simultaneously raising concerns regarding the potential misuse of AI-generated content. Although numerous detection methods have been proposed to differentiate between AI and human-generated content, the fairness and robustness of these detectors remain underexplored. In this study, we evaluate the performance of several widely-used GPT detectors using writing samples from native and non-native English writers. Our findings reveal that these detectors consistently misclassify non-native English writing samples as AI-generated, whereas native writing samples are accurately identified. Furthermore, we demonstrate that simple prompting strategies can not only mitigate this bias but also effectively bypass GPT detectors, suggesting that GPT detectors may unintentionally penalize writers with constrained linguistic expressions. Our results call for a broader conversation about the ethical implications of deploying ChatGPT content detectors and caution against their use in evaluative or educational settings, particularly when they may inadvertently penalize or exclude non-native English speakers from the global discourse.

By Eric Wu, James Zou, Mert Yuksekgonul, Weixin Liang and Yining Mao for arXiv.org on April 18, 2023

Watching the watchers: bias and vulnerability in remote proctoring software

Educators are rapidly switching to remote proctoring and examination software for their testing needs, both due to the COVID-19 pandemic and the expanding virtualization of the education sector. State boards are increasingly utilizing these software for high stakes legal and medical licensing exams. Three key concerns arise with the use of these complex software: exam integrity, exam procedural fairness, and exam-taker security and privacy. We conduct the first technical analysis of each of these concerns through a case study of four primary proctoring suites used in U.S. law school and state attorney licensing exams. We reverse engineer these proctoring suites and find that despite promises of high-security, all their anti-cheating measures can be trivially bypassed and can pose significant user security risks. We evaluate current facial recognition classifiers alongside the classifier used by Examplify, the legal exam proctoring suite with the largest market share, to ascertain their accuracy and determine whether faces with certain skin tones are more readily flagged for cheating. Finally, we offer recommendations to improve the integrity and fairness of the remotely proctored exam experience.

By Avi Ginsberg, Ben Burgess, Edward W. Felten and Shaanan Cohney for arXiv.org on May 6, 2022

What problems are AI-systems even solving? “Apparently, too few people ask that question”

In this interview with Felienne Hermans, Professor Computer Science at the Vrije Universiteit Amsterdam, she discusses the sore lack of divesity in the white male-dominated world of programming, the importance of teaching people how to code and, the problematic uses of AI-systems.

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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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Antispieksoftware op de VU discrimineert

Antispieksoftware checkt voorafgaand aan een tentamen of jij wel echt een mens bent. Maar wat als het systeem je niet herkent, omdat je een donkere huidskleur hebt? Dat overkwam student Robin Pocornie, zij stapte naar het College voor de Rechten van de Mens. Samen met Naomi Appelman van het Racism and Technology Centre, die Robin bijstond in haar zaak, vertelt ze erover.

By Naomi Appelman, Natasja Gibbs and Robin Pocornie for NPO Radio 1 on December 12, 2022

Eerste keer vermoeden van algoritmische discriminatie succesvol onderbouwd

Een student is erin geslaagd voldoende feiten aan te dragen voor een vermoeden van algoritmische discriminatie. De vrouw klaagt dat de Vrije Universiteit haar discrimineerde door antispieksoftware in te zetten. Deze software maakt gebruik van gezichtsdetectiealgoritmes. De software detecteerde haar niet als ze moest inloggen voor tentamens. De vrouw vermoedt dat dit komt door haar donkere huidskleur. De universiteit krijgt tien weken de tijd om aan te tonen dat de software niet heeft gediscrimineerd. Dat blijkt uit het tussenoordeel dat het College publiceerde.  

From College voor de Rechten van de Mens on December 9, 2022

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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Student meldt discriminatie met antispieksoftware bij College Rechten van de Mens

Een student van de Vrije Universiteit Amsterdam (VU) dient een klacht in bij het College voor de Rechten van de Mens (pdf). Bij het gebruik van de antispieksoftware voor tentamens werd ze alleen herkend als ze met een lamp in haar gezicht scheen. De VU had volgens haar vooraf moeten controleren of studenten met een zwarte huidskleur even goed herkend zouden worden als witte studenten.

From NU.nl on July 15, 2022

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