Supporting Trustworthy AI Through Machine Unlearning.

Journal: Science and engineering ethics
Published Date: Sep 11, 2024

Abstract

Machine unlearning (MU) is often analyzed in terms of how it can facilitate the "right to be forgotten." In this commentary, we show that MU can support the OECD's five principles for trustworthy AI, which are influencing AI development and regulation worldwide. This makes it a promising tool to translate AI principles into practice. We also argue that the implementation of MU is not without ethical risks. To address these concerns and amplify the positive impact of MU, we offer policy recommendations across six categories to encourage the research and uptake of this potentially highly influential new technology.

Authors

  • Emmie Hine
    Oxford Internet Institute, University of Oxford, 1 St Giles', Oxford, OX1 3JS, UK.
  • Claudio Novelli
    Department of Legal Studies, University of Bologna, Via Zamboni, 27/29, 40121, Bologna, Italy.
  • Mariarosaria Taddeo
    Oxford Internet Institute, University of Oxford, 1 St Giles, Oxford, OX1 3JS, UK.
  • Luciano Floridi
    Oxford Internet Institute, University of Oxford, Oxford, United Kingdom.

Keywords

External Resources

Popular Topics
Recent Journals