Pournaras, E (2020) Collective Learning: A 10-Year Odyssey to Human-centered Distributed Intelligence. In: 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS). 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), 17-21 Aug 2020, Washington, DC, USA. IEEE , pp. 205-214. ISBN 978-1-7281-7277-4
Abstract
This paper illustrates a 10-year research endeavor on collective learning, a paradigm for tackling tragedy of the commons problems in socio-technical systems using human-centered distributed intelligence. In contrast to mainstream centralized artificial intelligence (AI) allowing algorithmic discrimination and manipulative nudging, the decentralized approach of collective learning is by-design participatory and value-sensitive: it aligns with privacy, autonomy, fairness and democratic values. Engineering such values in a socio-technical system results in computational constraints that turn collective decision-making into complex combinatorial NP-hard problems. These are the problems that collective learning and the EPOS research project tackles. Collective learning finds striking applicability in energy, traffic, supply-chain and the self-management of sharing economies. This grand applicability and the social impact are demonstrated in this paper along with a future perspective of the collective learning paradigm.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | collective learning , artificial intelligence , human-centered AI , multi-agent system , combinatorial optimization , distributed computing , EPOS |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Apr 2021 14:08 |
Last Modified: | 13 Apr 2021 13:48 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/acsos49614.2020.00043 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:172733 |