arXiv AI

Co-constructing sociotechnical AI governance: participatory system mapping using algorithm registers

arXiv:2608. 12166v1 Announce Type: cross Abstract: Algorithm registers have been championed as a means of providing transparency on the use of algorithms in public services.

arXiv AI
Jul 22

Governing Well in the Algorithmic Age: The Foundations of Digital Statecraft

arXiv:2607. 18483v1 Announce Type: cross Abstract: The digital substrate of states -- data, algorithms, infrastructure, platforms, applications -- is being governed without adequate conceptual foundations.

By Zeynep Engin, Tim Gordon, Viviana Bastidas, Tom Crick, Jon Crowcroft, Jean-Martin Denis, David J. Hand, Lauren Maffeo, Jakob M\"okander, Irene Ng, Anastasija Nikiforova, Giulio Quaggiotto, David Uriel Socol de la Osa, Rhonda Syler, Philip Treleaven, Stefaan Verhulst
arXiv AI
Jun 12

Fault Lines: Navigating Ethics and Responsible AI Where National Policy Meets Local Practice in Public Sector Transformation

arXiv:2606. 13039v1 Announce Type: cross Abstract: The UK government has adopted a pro-AI stance to help transform public service delivery in the face of severe financial pressures, but the path to translate this vision into responsible AI practice remains ill-defined.

By Sitong Lyu, Shabnam Taghiyeva, Mohit Kukadia, Denis Newman-Griffis
arXiv AI
Jun 12

Algorithmic Constitutionalism

arXiv:2606. 12437v1 Announce Type: cross Abstract: The increasing encroachment of artificial intelligence (AI) on social life raises significant risks for society, particularly within the infospheres created and controlled by companies such as Google, Facebook, Apple, and Amazon.

By Oren Perez, Nurit Wimer
arXiv AI
Jul 1

A Technical Typology of AI Systems in Public Administration

arXiv:2606. 31755v1 Announce Type: cross Abstract: Research on artificial intelligence (AI) in the public sector often treats "AI" as a single category, neglecting technical distinctions between different AI systems.

By Jonathan Rystr{\o}m, Chris Schmitz, Nathan Davies, Gerhard Hammerschmid, Albert Meijer, Chris Russell
arXiv AI
Jul 15

Vertical Standardisation for High-Risk AI Systems under the EU AI Act: A Domain-Specific Framework for Algorithmic Hiring

arXiv:2607. 12588v1 Announce Type: new Abstract: According to the recent European legislation, high-risk AI systems will have to adapt in order to comply with requirements related to specific areas, like risk management, data quality and governance, logging and traceability, technical documentation, transparency, human oversight, and accuracy, as outlined in the European Artificial Intelligence (AI) Act.

By Anna Gatzioura, Vrettos Moulos, Nina Baranowska