Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward

Lo Piano, S. ORCID: https://orcid.org/0000-0002-2625-483X (2020) Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward. Palgrave Communications, 7 (9). ISSN 2055-1045 doi: 10.1057/s41599-020-0501-9

Abstract/Summary

Decision-making on numerous aspects of our daily lives is being outsourced to machine-learning algorithms and artificial intelligence (AI), motivated by speed and efficiency in the decision process. Machine learning (ML) approaches - one of the typologies of algorithms underpinning artificial intelligence - are typically developed as black boxes. The implication is that ML code scripts are rarely scrutinised; interpretability is usually sacrificed in favour of usability and effectiveness. Room for improvement in practices associated with programme development have also been flagged along other dimensions, including inter alia fairness, accuracy, accountability, and transparency. In this contribution, the production of guidelines and dedicated documents around these themes is discussed. The following applications of AI-driven decision making are outlined: a) Risk assessment in the criminal justice system, and b) autonomous vehicles, highlighting points of friction across ethical principles. Possible ways forward towards the implementation of governance on AI are finally examined.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/90710
Item Type	Article
Refereed	Yes
Divisions	Interdisciplinary centres and themes > Centre for Technologies for Sustainable Built Environments (TSBE) Science > School of the Built Environment > Energy and Environmental Engineering group
Publisher	Nature
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