Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle

Borsci, Simone; Lehtola, Ville V.; Nex, Francesco; Yang, Michael Ying; Augustijn, Ellen-Wien; Bagheriye, Leila; Brune, Christoph; Kounadi, Ourania; Li, Jamy; Moreira, Joao; Van Der Nagel, Joanne; Veldkamp, Bernard; Le, Duc V.; Wang, Mingshu; Wijnhoven, Fons; Wolterink, Jelmer M.; Zurita-Milla, Raul

Abstract

The European Union (EU) Commission’s whitepaper on Artificial Intelligence (AI) proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: (i) the lack of a coherent EU vision to drive future decision-making processes at state and local levels and (ii) the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society.

• Journal Article Type: Article
• Acceptance Date: Dec 21, 2021
• Online Publication Date: Jan 22, 2022
• Publication Date: 2023-08
• Deposit Date: May 7, 2024
• Journal: AI & SOCIETY
• Print ISSN: 0951-5666
• Electronic ISSN: 1435-5655
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 38
• Pages: 1465-1484
• DOI: https://doi.org/10.1007/s00146-021-01383-x
• Keywords: Artificial intelligence, Human artificial intelligence interaction, AI Policies, Symbiosis of AI and Humans, Societal impact, Trust