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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.

his chapter explores aspects of the relationship between technology, transparency, and accountability in public decision-making. It addresses how technological advancements have increased accessibility and automation while complicating decision process reviewability. It explores transparency as a relational concept and focuses on legal obligations on documentation and records-keeping, such as in the EU General Data Protection Regulation and the upcoming EU Artificial Intelligence Act, as a means to bolster transparency and improve reviewability. In particular it also discusses the feasibility of gathering and analysing ‘paradata’—data pertaining to data processes—as a means to safeguard legality and transparency in automated decision-making, notably within the public sphere. 

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.

The primary objective of this special issue is to bring to light the role the social insurance system has as a cornerstone of the Swedish welfare state. The legal configuration of this system is consequently often significant for individuals in order for them to attain economic and social stability. Through its regulation of access to various benefits, including sickness allowances, pensions and non-monetary benefits such as rehabilitation services, social insurance can profoundly influence an individual’s capacity to navigate financial adversities across different life stages. Furthermore, it serves as a pivotal mechanism for social justice through its objective of equitably allocating resources and protection. Consequently, the configuration of social insurance benefits shapes not only individuals’ interaction with the welfare state but also their relationship with society at large.

This article explores the application of semi-automated decision support systems in the administration of social insurance, focusing on the Swedish Social Insurance Agency’s utilisation of an AI system called SAMU (structured analysis of medical records). SAMU employs cognitive analysis models to assist administrators in identifying pertinent information in medical certificates for evaluating eligibility for sickness or activity compensation. The article assesses the implementation of SAMU, examining its potential impact on a comprehensive evaluation of an individual’s work capacity, as well as its implications for legally correct and secure decision-making. The analysis adopts a sociotechnical perspective, considering the mutual influence between society and technology and the resulting framework that shapes the decisions of caseworkers in the realm of automation-related risks in case management.

This chapter examines the Swedish administrative model in the context of digitalisation and automation of tasks and decision-making, from a rule of law perspective. Against the background of ambitious national political ambitions to leverage technologies for enhancing the functions of public authorities, the chapter explores some distinctive aspects of the Swedish regulatory strategy toward digitalisation – emphasising its predominantly technology-neutral stance. This implies a somewhat restrained purpose-specific and direct regulatory impact on digitalisation initiatives and specific procedural safeguards for administrative matters influenced by digitisation or automation. However, the chapter also contends that there is a discernible shift towards an increased level of national regulatory initiatives and control, often aimed at reducing legal obstacles to digitalisation and automation. The chapter also highlights, as a second typical feature of the Swedish approach to public digitalisation, that the relatively strong independence of the government as well as municipal authorities in relation to central government has probable explanatory value for why national public digitisation initiatives are often initiated and prioritised at authority level rather than through political or regulatory governance. This independence is a probable factor contributing to cross-agency collaborations, which not only aim to facilitate implementation but also seek to clarify the boundaries of the governing regulatory frameworks. It concludes that the multifaceted challenges posed by technology to maintaining the rule of law in public administration require diligent oversight, collaborative initiatives, and the exchange of knowledge to effectively tackle common issues.

This contribution examines the relationship between automation, discretion, and proportionality. It argues that automation efforts in public administration need to be further discussed and analyzed in relation to requirements of proportionality flowing from both national and European law, as the principle carries important implications for both the implementation of automated systems and the responsibilities of decision-makers within those systems. The different facets of proportionality flowing from, inter alia, constitutional, and human rights law, administrative law, and data protection law are explored, with four distinct stages of proportionality analysis identified: legislative, system, decision, and ex post proportionality. These stages all carry different implications for discretion and the prospects of automation. Through the requirements in these different stages, the authors conclude that proportionality ought to act as another driver of keeping human oversight of automated systems. This human oversight will however, in relation to proportionality, require further contextual awareness and control of correct output proportionality, a role which may be significantly more demanding than a more limited oversight implied by current legal discussions on "humans in the loop".

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.

This article exploresthe growing role of automation in the administration of social security benefits, focusing on the reliance of automated processes not only on accurate data but also on well-structured data for computational utilisation. It examines the potential impact on claimants’ability to present their claims and identities, raising concerns about excessive standardisation that could compromise principles of good administration, including the right to be heard, a fair procedure, and the duty of care.Using Swedish examples, the article underscores the importance of balancing automated eligibility assessments with the need to allow claimants to present their cases in free text and to consider low-structured data within automated procedures. It argues for a continuous assessment of the consequences for claimants in developing digital services, emphasising the administration’s responsibility to align with underlying principles and intentions of applicable regulations. Failure to do so may lead to a dehumanised case administration lacking room for meaningful questioning or clarification.