Netherlands/Research external link

1029, pp: 164-175

Abstract

How are AI-based systems being used by private companies and public authorities in Europe? The new report by AlgorithmWatch and Bertelsmann Stiftung sheds light on what role automated decision-making (ADM) systems play in our lives. As a result of the most comprehensive research on the issue conducted in Europe so far, the report covers the current use of and policy debates around ADM systems in 16 European countries and at EU level.

ai, automated decision making, frontpage, Technologie en recht

Bibtex

Discrimination, artificial intelligence, and algorithmic decision-making external link

vol. 2019, 2019

Abstract

This report, written for the Anti-discrimination department of the Council of Europe, concerns discrimination caused by algorithmic decision-making and other types of artificial intelligence (AI). AI advances important goals, such as efficiency, health and economic growth but it can also have discriminatory effects, for instance when AI systems learn from biased human decisions. In the public and the private sector, organisations can take AI-driven decisions with farreaching effects for people. Public sector bodies can use AI for predictive policing for example, or for making decisions on eligibility for pension payments, housing assistance or unemployment benefits. In the private sector, AI can be used to select job applicants, and banks can use AI to decide whether to grant individual consumers credit and set interest rates for them. Moreover, many small decisions, taken together, can have large effects. By way of illustration, AI-driven price discrimination could lead to certain groups in society consistently paying more. The most relevant legal tools to mitigate the risks of AI-driven discrimination are nondiscrimination law and data protection law. If effectively enforced, both these legal tools could help to fight illegal discrimination. Council of Europe member States, human rights monitoring bodies, such as the European Commission against Racism and Intolerance, and Equality Bodies should aim for better enforcement of current nondiscrimination norms. But AI also opens the way for new types of unfair differentiation (some might say discrimination) that escape current laws. Most non-discrimination statutes apply only to discrimination on the basis of protected characteristics, such as skin colour. Such statutes do not apply if an AI system invents new classes, which do not correlate with protected characteristics, to differentiate between people. Such differentiation could still be unfair, however, for instance when it reinforces social inequality. We probably need additional regulation to protect fairness and human rights in the area of AI. But regulating AI in general is not the right approach, as the use of AI systems is too varied for one set of rules. In different sectors, different values are at stake, and different problems arise. Therefore, sector-specific rules should be considered. More research and debate are needed.

ai, discriminatie, frontpage, kunstmatige intelligentie, Mensenrechten

Bibtex

Automated Decision-Making Fairness in an AI-driven World: Public Perceptions, Hopes and Concerns external link

Araujo, T., Vreese, C.H. de, Helberger, N., Kruikemeier, S., Weert, J. van,, Bol, N., Oberski, D., Pechenizkiy, M., Schaap, G. & Taylor, L.
2018

Abstract

Ongoing advances in artificial intelligence (AI) are increasingly part of scientific efforts as well as the public debate and the media agenda, raising hopes and concerns about the impact of automated decision making across different sectors of our society. This topic is receiving increasing attention at both national and cross- national levels. The present report contributes to informing this public debate, providing the results of a survey with 958 participants recruited from high-quality sample of the Dutch population. It provides an overview of public knowledge, perceptions, hopes and concerns about the adoption of AI and ADM across different societal sectors in the Netherlands. This report is part of a research collaboration between the Universities of Amsterdam, Tilburg, Radboud, Utrecht and Eindhoven (TU/e) on automated decision making, and forms input to the groups’ research on fairness in automated decision making.

ai, algoritmes, Artificial intelligence, automated decision making, frontpage

Bibtex

Before the Singularity: Copyright and the Challenges of Artificial Intelligence external link

González Otero, B., & Quintais, J.
Kluwer Copyright Blog, vol. 2018, 2018

ai, Copyright, frontpage

Bibtex

The paradox of lawful text and data mining? Some experiences from the research sector and where we (should) go from here external link

GRUR International, vol. 74, iss. : 4, pp: 307-319, 2025

Abstract

Scientific research can be tricky business. This paper critically explores the 'lawful access' requirement in European copyright law which applies to text and data mining (TDM) carried out for the purpose of scientific research. Whereas TDM is essential for data analysis, artificial intelligence (AI) and innovation, the paper argues that the 'lawful access' requirement in Article 3 CDSM Directive may actually restrict research by complicating the applicability of the TDM provision or even rendering it inoperable. Although the requirement is intended to ensure that researchers act in good faith before deploying TMD tools for purposes such as machine learning, it forces them to ask for permission to access data, for example by taking out a subscription to a service, and for that reason provides the opportunity for copyright holders to apply all sorts of commercial strategies to set the legal and technological parameters of access and potentially even circumvent the mandatory character of the provision. The paper concludes by drawing on insights from the recent European Commission study 'Improving access to and reuse of research results, publications and data for scientific purposes' that offer essential perspectives for the future of TDM, and by suggesting a number of paths forward that EU Member States can take already now in order to support a more predictable and reliable legal regime for scientific TDM and potentially code mining to foster innovation.

ai, CDSM Directive, Copyright, text and data mining

Bibtex