Read our comprehensive reports, analyses and working papers on the impact and ethical questions of algorithmic decision-making, written in collaboration with our network of researchers and civil society experts.
It remains unclear how the largest platforms and search engines should go about identifying “systemic risks” to comply with the DSA. AlgorithmWatch outlines a methodology that will serve as a benchmark for how we, as a civil society watchdog, will judge the risk assessments that are being conducting at this very moment.
Workers are increasingly being digitally surveilled, datafied and algorithmically managed in Italy, Poland, Sweden and the United Kingdom, a qualitative analysis by AlgorithmWatch shows.
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Employees must be included in the implementation process, if so-called Artificial Intelligence (AI) systems are introduced to their workplace. Such systems are used by many companies for automated decision-making (ADM) already. They are often based on Machine Learning (ML) algorithms. The European Union’s Artificial Intelligence Act (AI Act) draft is designed to safeguard workers’ rights, but such legislative measures won’t be enough. An AlgorithmWatch study funded by the Hans Böckler Foundation explains how workers’ co-determination can be practically achieved in this regard.
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In the second issue of our SustAIn Magazine, we show what prevents AI systems from being sustainable and how to find better solutions.
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Our report shows that trade unions are now called upon to focus on practical advice and guidance to empower union representatives and negotiators to deal with the challenges that automation puts onto workers.
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Understanding causes, recognizing cases, supporting those affected: documents for implementing a workshop.
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The environmental, social and economic sustainability costs of AI urgently need to be addressed by academia, industry, civil society and policy makers – based on evidence. With the first edition of our SustAIn magazine, we hope to fuel this debate.
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We are faced with automated decision-making systems almost every day and they might be discriminating, without us even knowing about it. A new guidebook helps to better recognize such cases and support those affected.
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In a new AlgorithmWatch discussion paper, data regulation expert Winfried Veil argues that the Data Governance Act is not only annoyingly bureaucratic, but a missed opportunity to breathe life into the “Data for Good” idea.
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