University of Oulu

Niels van Berkel, Benjamin Tag, Jorge Goncalves & Simo Hosio (2020) Human-centred artificial intelligence: a contextual morality perspective, Behaviour & Information Technology, DOI: 10.1080/0144929X.2020.1818828

Human-centred artificial intelligence : a contextual morality perspective

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Author: van Berkel, Niels1; Tag, Benjamin2; Goncalves, Jorge2;
Organizations: 1Aalborg University, Aalborg, Denmark
2The University of Melbourne, Melbourne, Australia
3University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202201031079
Language: English
Published: Informa, 2021
Publish Date: 2022-01-03
Description:

Abstract

The emergence of big data combined with the technical developments in Artificial Intelligence has enabled novel opportunities for autonomous and continuous decision support. While initial work has begun to explore how human morality can inform the decision making of future Artificial Intelligence applications, these approaches typically consider human morals as static and immutable. In this work, we present an initial exploration of the effect of context on human morality from a Utilitarian perspective. Through an online narrative transportation study, in which participants are primed with either a positive story, a negative story or a control condition (N = 82), we collect participants’ perceptions on technology that has to deal with moral judgment in changing contexts. Based on an in-depth qualitative analysis of participant responses, we contrast participant perceptions to related work on Fairness, Accountability and Transparency. Our work highlights the importance of contextual morality for Artificial Intelligence and identifies opportunities for future work through a FACT-based (Fairness, Accountability, Context and Transparency) perspective.

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Series: Behaviour & information technology
ISSN: 0144-929X
ISSN-E: 1362-3001
ISSN-L: 0144-929X
Volume: In press
DOI: 10.1080/0144929X.2020.1818828
OADOI: https://oadoi.org/10.1080/0144929X.2020.1818828
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Subjects:
Funding: This project was funded by GenZ, a strategic profiling project supported by the Academy of Finland (project number 318930) and the University of Oulu.
Academy of Finland Grant Number: 318930
Detailed Information: 318930 (Academy of Finland Funding decision)
Copyright information: © 2020 Informa UK Limited, trading as Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis in Behaviour & Information Technology on 11 Sep 2020, available online: https://doi.org/10.1080/0144929X.2020.1818828.