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User-Centric Democratization towards Social Value Aligned Medical AI Services

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Published
Publication date19/08/2023
Host publicationProceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
EditorsEdith Elkind
PublisherInternational Joint Conferences on Artificial Intelligence
Pages6326-6334
Number of pages9
ISBN (electronic)9781956792034
<mark>Original language</mark>English
Event32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 - Macao, China
Duration: 19/08/202325/08/2023

Conference

Conference32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
Country/TerritoryChina
CityMacao
Period19/08/2325/08/23

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
Volume2023-August
ISSN (Print)1045-0823

Conference

Conference32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
Country/TerritoryChina
CityMacao
Period19/08/2325/08/23

Abstract

Democratic AI, aiming at developing AI systems aligned with human values, holds promise for making AI services accessible to people. However, concerns have been raised regarding the participation of non-technical individuals, potentially undermining the carefully designed values of AI systems by experts. In this paper, we investigate Democratic AI, define it mathematically, and propose a user-centric evolutionary democratic AI (u-DemAI) framework. This framework maximizes the social values of cloud-based AI services by incorporating user feedback and emulating human behavior in a community via a user-in-the-loop iteration. We apply our framework to a medical AI service for brain age estimation and demonstrate that non-expert users can consistently contribute to improving AI systems through a natural democratic process. The u-DemAI framework presents a mathematical interpretation of Democracy for AI, conceptualizing it as a natural computing process. Our experiments successfully show that involving non-tech individuals can help improve performance and simultaneously mitigate bias in AI models developed by AI experts, showcasing the potential for Democratic AI to benefit end users and regain control over AI services that shape various aspects of our lives, including our health.

Bibliographic note

Funding Information: This work was supported in part by the U.K. EPSRC under Grant EP/P009727/1 and Grant EP/T518037/1, and in part by the Leverhulme Trust under Grant RF-2019-492. Publisher Copyright: © 2023 International Joint Conferences on Artificial Intelligence. All rights reserved.