Conference Paper/Proceeding/Abstract 113 views 5 downloads
Enhancing Fairness, Justice and Accuracy of Hybrid Human-AI Decisions by Shifting Epistemological Stances
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Alan Dix
Communications in Computer and Information Science, Volume: 1, Pages: 323 - 331
Swansea University Authors:
Peter Daish, Matt Roach , Alan Dix
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DOI (Published version): 10.1007/978-3-031-74627-7_25
Abstract
From applications in automating credit to aiding judges in presiding over cases of recidivism, deep-learning powered AI systems are becoming embedded in high-stakes decision-making processes as either primary decision-makers or supportive assistants to humans in a hybrid decision-making context, wit...
| Published in: | Communications in Computer and Information Science |
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| ISBN: | 9783031746260 9783031746277 |
| ISSN: | 1865-0929 1865-0937 |
| Published: |
Cham
Springer Nature Switzerland
2025
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa68367 |
| Abstract: |
From applications in automating credit to aiding judges in presiding over cases of recidivism, deep-learning powered AI systems are becoming embedded in high-stakes decision-making processes as either primary decision-makers or supportive assistants to humans in a hybrid decision-making context, with the aim of improving the quality of decisions. However, the criteria currently used to assess a system’s ability to improve hybrid decisions is driven by a utilitarian desire to optimise accuracy through a phenomenon known as ‘complementary performance’. This desire puts the design of hybrid decision-making at odds with critical subjective concepts that affect the perception and acceptance of decisions, such as fairness. Fairness as a subjective notion often has a competitive relationship with accuracy and as such, driving complementary behaviour with a utilitarian belief risks driving unfairness in decisions. It is our position that shifting epistemological stances taken in the research and design of human-AI environments is necessary to incorporate the relationship between fairness and accuracy into the notion of ‘complementary behaviour’, in order to observe ‘enhanced’ hybrid human-AI decisions. |
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| College: |
Faculty of Science and Engineering |
| Start Page: |
323 |
| End Page: |
331 |