Trustworthy AI

a cooperative approach

Authors

DOI:

https://doi.org/10.26116/techreg.2023.006

Keywords:

Artificial Intelligence, Trustworthy AI, Artificial Intelligence Act, Automated Decision Making, Administrative Law

Abstract

The EU has proposed harmonized rules on artificial intelligence (AI Act) and a directive on adapting non-contractual civil liability rules to AI (AI liability directive) due to increased demand for trustworthy AI. However, the concept of trustworthy AI is unspecific, covering various desired characteristics such as safety, transparency, and accountability. Trustworthiness requires a specific contextual setting that involves human interaction with AI technology, and simply involving humans in decision processes does not guarantee trustworthy outcomes. In this paper, the authors argue for an informed notion of what is meant for a system to be trustworthy and examine the concept of trust, highlighting its reliance on a specific relationship between humans that cannot be strictly transmuted into a relationship between humans and machines. They outline a trust-based model for a cooperative approach to AI and provide an example of what that might look like.

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Author Biographies

  • Jacob Livingston Slosser, University of Copenhagen

    Assisstant Professor

    iCourts - Danish National Research Foundation’s Centre of Excellence for International Courts
    Faculty of Law

  • Birgit Aasa, University of Copenhagen

    Postdoctoral Researcher

    iCourts - Danish National Research Foundation’s Centre of Excellence for International Courts

    Faculty of Law

  • Henrik Palmer Olsen, University of Copenhagen

    Professor of Jurisprudence, University of Copenhagen, Faculty of Law, iCourts - the Danish National Research Foundation’s Centre of Excellence for International Courts; Research fellow 2023-2024 at IEA-Paris.

TechReg 2023.006 cover page

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Published

27-10-2023

Issue

Section

Articles

How to Cite

Trustworthy AI: a cooperative approach. (2023). Technology and Regulation, 2023, 58-68. https://doi.org/10.26116/techreg.2023.006