The GM AI Foundry: A Model for Upskilling SME's in Responsible AI

Lawton, Roxy; Boswell, Sara; Smiee, Keeley Crockett

Abstract

Building responsible and trustworthy AI solutions is now the norm, yet the challenge of bridging the ethical AI principles to practice gap especially for small to medium businesses is significant with the forthcoming European Union AI ACT (2023) becoming a major disrupter for global businesses. AI Adoption by SMEs is growing but there are many barriers including limited AI skills, complexity of projects, lack of understanding of what is trustworthy and responsible AI and the tools needed to consequence scan the wider impact on stakeholders of innovative products and services prior to market. This paper presents a case study of the Greater Manchester AI Foundry (GMAIF)-a consortium model for University-SME collaboration designed to foster ethical and responsible AI design and development practices into SMEs and new start-ups. The GMAIF model supports the creation of proof-of-concept demonstrator projects, forming a number of tangible products or services, that demonstrate how AI can be used to enhance or provide new products and services. Whilst the model is demonstrated within the UK, its concepts are generalizable and applicable globally. GMAIF has impacted 186 SMEs in the UK, with 67 new AI products being developed by SMEs and an additional 80 innovative products to market.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2023 IEEE Symposium Series on Computational Intelligence (SSCI)
• Acceptance Date: Sep 30, 2023
• Publication Date: Jan 1, 2024
• Deposit Date: Jan 17, 2024
• Publicly Available Date: Feb 14, 2024
• Journal: 2023 IEEE Symposium Series on Computational Intelligence (SSCI)
• Electronic ISSN: 2472-8322
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1109/ssci52147.2023.10371988
• Keywords: ethics artificial intelligence; toolkits; responsible technology; industry; SME