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Whereas hackathons are widespread within and outside academia and have been argued to be a valid pedagogical method for teaching interdisciplinarity, no detailed frameworks or methods are available for conceptualizing and organizing educational hackathons, i.e., hackathons dedicated to best achieving pedagogic objectives. This paper is dedicated to introducing EDUCational Hackathons for learning how to solve Interdisciplinary Challenges (EDUCHIC) through: (1) defining the fundamental principles for framing an activity as an EDUCHIC, integrating principles from pedagogical methods, hackathon organization, and interdisciplinarity processes; (2) describing general properties that EDUCHIC possess as a consequence of the interaction of the fundamental principles; (3) developing operational guidelines for streamlining the practical organization of EDUCHIC, including an exhaustive end‐to‐end process covering all the steps for organizing EDUCHIC and practical frames for carrying the key decisions to be made in this process; and (4) a demonstration of these guidelines through illustrating their application for organizing a concrete EDUCHIC. [ABSTRACT FROM AUTHOR]

This article focuses on the legal implications of the growing reliance on automated systems in public administrations, using the example of social security benefits administration. It specifically addresses the deployment of automated systems for decisions on benefits eligibility within the frameworks of the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (AIA). It compares how these two legal frameworks, each targeting different regulatory objects (personal data versus AI systems) and employing different protective measures, apply for two common system types: rule-based systems utilised for making fully automated decisions on eligibility, and machine learning AI systems utilised for assisting case administrators in their decision-making. It concludes on the combined impact that the GDPR and the AIA will have on each of these types of systems, as well as on differences in how these instruments determines the basic legality of utilising such systems within social security administration. [ABSTRACT FROM AUTHOR]

Human oversight has been much stressed and discussed as a safeguarding measure to ensure human centrism in AI deployment. Through its proposal of a new EU Artificial Intelligence Act, the Commission is breaking new ground by promoting the introduction of the first general and sharp worded human oversight requirement over AI systems in European law. This Article discusses the content, limitations and implications of this oversight requirement. It does this by addressing the questions of what the Regulation prescribes on 'what' is to be overviewed, 'when' the overview is to be exercised and 'by whom'. The article points to some of the AIA's unclarities and gaps, and to the implications of vesting too much trust in providers to secure the oversight infrastructure of high-risk AI systems. [ABSTRACT FROM AUTHOR]

Public and private organizations are increasingly implementing various algorithmic decision-making systems. Through legal and practical incentives, humans will often need to be kept in the loop of such decision-making to maintain human agency and accountability, provide legal safeguards, or perform quality control. Introducing such human oversight results in various forms of semi-automated, or hybrid decision-making – where algorithmic and human agents interact. Building on previous research we illustrate the legal dependencies forming an impetus for hybrid decision-making in the policing, social welfare, and online moderation contexts. We highlight the further need to situate hybrid decision-making in a wider legal environment of data protection, constitutional and administrative legal principles, as well as the need for contextual analysis of such principles. Finally, we outline a research agenda to capture contextual legal dependencies of hybrid decision-making, pointing to the need to go beyond legal doctrinal studies by adopting socio-technical perspectives and empirical studies. [ABSTRACT FROM AUTHOR]