From ethical Artificial Intelligence principles to practice: a case study of university-industry collaboration

Crockett, Keeley ORCID: https://orcid.org/0000-0003-1941-6201, Brophy, Sean ORCID: https://orcid.org/0000-0001-9940-4192, Attwood, Samuel ORCID: https://orcid.org/0000-0001-8140-6157, Monks, Peter and Webb, David (2022) From ethical Artificial Intelligence principles to practice: a case study of university-industry collaboration. In: IEEE World Congress on Computational Intelligence 2022 - IEEE IJCNN, 18 July 2022 - 23 July 2022, Italy.

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Official URL: https://ieeexplore.ieee.org/document/9892760

Abstract

The ethical artificial intelligence principal to practice gap is a significant challenge for micro and small medium businesses (SME). The policy and legal landscape is very dynamic and whilst there are limited toolkits, designed to help such businesses to embed the ethical design of responsible technology, there is generally a lack of skills, knowledge and resources on how to apply them within individual businesses. In this paper we present a small case study of practical examples that has led to the introduction of ethical AI practices into SMEs. Through a European funded university-industry collaboration, to date 102 SMEs within Greater Manchester, UK have been exposed to data and ethical AI workshops, with a subset of these choosing to deeper dive and apply tools such as consequence scanning and harms modelling within their business with support from university technical analysts and academics. The case study presents initial evaluations on embedding ethical principles, challenges faced by the SMEs and the reflections of technical analysts.

Item Type:	Conference or Workshop Item (Paper)
Published Proceedings:	2022 International Joint Conference on Neural Networks (IJCNN)
Peer-reviewed:	Yes
Date Deposited:	12 May 2022 10:31
Publisher:	IEEE
Additional Information:	© 2022 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.
Divisions:	Faculties > Business and Law Faculties > Science and Engineering Research Centres > Centre for Advanced Computational Science Research Centres > Decent Work and Productivity
Subject terms:	Artificial Intelligence, Business, Ethics, GM AI Foundry
URI:	https://mmu-uat.leaf.cosector.com/id/eprint/629693
DOI:	https://doi.org/10.1109/IJCNN55064.2022.9892760
ISSN	2161-4393
e-ISSN	2161-4407

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