Successful AI Ethics & Governance at Scale: Bridging The Organizational and Implementation Gaps

The road from ethics to executives winds through lawyers and LLMs

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When it comes to AI governance, what do the world’s largest AI companies, the world’s smartest AI academics, and the world’s most famous consulting firms have in common?

None of them are responsible for actually making it work in your company.

This is part 2 of a series on successful implementing AI ethics and governance in large organizations. Part 1 talks about the challenge of interpretation: how specialist talent is needed to bridge the gap between high level policies and unique AI use cases.

In this article we talk about the next two gaps: the organizational gap looking at the challenge of AI ethics and governance ownership spread across different departments, and the implementation gap of reluctance to implement scaled AI ethics and governance measures under pressure to adopt AI.

The focus is on AI ethics and governance at scale — in a way that is embedded in the core processes and decisions of the company. Starting on AI ethics is easy — the problem is they often end with the 3 Ps of principles, pilots and PR (public relations). Munn (2022)’s provocative paper ‘The…