Knowledge base
Our knowledge base is a collection of readworthy articles, books and other publications from various disciplines about algorithmic fairness. Each piece of writing has been summarized and/or reviewed.
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Articles
Guidelines for AI Act implementation
Author(s): Algorithm Audit
Guidelines for AI Act implementation
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Indirect discrimination in Meta’s ML-driven advertising system
Author(s): The Netherlands Institute for Human Rights
Meta’s ML-driven advertising system indirectly discriminates against women
Read moreGuidelines for AI Act implementation
Author(s): Algorithm Audit
Guidelines for AI Act implementation
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Public standard profiling algorithms
Author(s): Algorithm Audit
Public standard profiling algorithms
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Algoprudence: Jurisprudence for algorithms
Author(s): Algorithm Audit
Introducing Algoprudence: Case-based and decentralized judgements for ethical AI
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Algorithm Audit (white paper) – Feedback on DSA Delegated Regulation (conducting independent audits)
Author(s): Algorithm Audit
Plea to include the normative dimension of AI auditing in delegated regulation of the Digital Services Act (DSA). Current limitations are illustrated by focussing on a recommender systems example
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Algorithm Audit (op-ed) – Human vs machine bias
Author(s): Jurriaan Parie, Vardâyani Djwalapersad
Based on bias testing results from the Municipality of Amsterdam, it is argued that that algorithms can play an important role in mitigating biases originating from humans
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Algorithm Audit (op-ed) – A new algorithmic regulatory body in The Netherlands
Author(s): Algorithm Audit
A new algorithmic regulatory body is institutionalized in The Netherlands. We say: Make it a bulldog 🐺, not a lap dog 🐶
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Algorithm Audit (op-ed) – Reversing the burden of proof
Author(s): Algorithm Audit
Algorithm Audit’s first white paper on the reversal on the burden of proof in the context of (semi-)automated decision-making
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A is voor algoritme
Author(s): O.A. al Khatib, M.H.A.F. Lokin, R.J.H. Bruggeman & A.C.M. Meuwese
Scientific legal paper delayering the relation between Dutch Public Administration Law and algorithmic systems
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Algorithmic Discrimination in Europe
Author(s): Janneke Gerards and Raphaële Xenidis
This EU report investigates how algorithmic discrimination challenges the set of legal guarantees put in place in Europe to combat discrimination and ensure equal treatment.
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Algorithms and Fundamental Rights
Author(s): Janneke Gerards, Remco Nehmelman, Max Vetzo
Overview how automated decision-making has a profound impact on fundamental rights in the context of the Dutch legal system
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Automated Decision-Making Under the GDPR – A comphrehensive case-law analysis
Author(s): Sebastião Barros Vale, Gabriela Zanfir-Fortuna
The Future of Privacy Forum (FPF) launched a comprehensive report analyzing case-law under the General Data Protection Regulation (GDPR) applied to real-life cases involving Automated Decision Making (ADM).
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Bias report Short Stay Visum – SigmaRed for the Dutch Ministry of Ministry of Foreign Affairs
Author(s): SigmaRed
Bias assessment of Dutch Ministry of Ministry of Foreign Affairs’ short stay visa classification model by SigmaRed Technologies
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Digitalization and the (Dis)balanced Trias Politica
Author(s): Reijer Passchier
Scientific legal paper arguing why new checks and balances are needed to guarantee a separation of state powers in the digital era.
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Discrimination through Risk Profiling
Author(s): Dutch College for Human Rights
Framework for discrimination through risk-profiling
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Examining confirmation bias using the F-test
Author(s): Onbekend
Applied to test confirmation bias of civil servant in an algorithmic-driven visa application process
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Practical Fairness
Author(s): Aileen Nielsen
A wide-ranging book that informs data and AI ethics practitioners about recent advances in open-source toolkits and legal frameworks.
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Protected grounds and the system of non-discrimination law in the context of algorithmic decision-making and AI
Author(s): Janneke Gerards and Frederik Zudierveen Borgesius
Plea that a hybrid system of non-discrimination law, with a semi-closed list of grounds and an open possibility for exemptions and justification, is best-suited to deal with the particularities of AI-driven discrimination.
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The Ethical Algorithm
Author(s): Michael Kearns, Aaron Roth
Technically accesible and compelling book. Filled with fresh thoughts from a frontier in the fair ML community. Written by two top-tier computer scientists.
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The Measure and Mismeasure of Fairness
Author(s): Sam Corbett-Davies, Sharad Goel
Why are formulas for fairness troublesome? Why prevailing definitions of fairness typically do not map on to traditional social, economic or legal understandings of the concept? This paper provides answers.
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Why Fairness cannot be Automated
Author(s): Sandra Wachter, Brent Mittelstadt, Chris Russell
Must-read scientific paper proposing ideas to bridge the qualitative (legal) and quantitative (statistical) doctrine
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