Why we do not need to reinvent the wheel for an ethical approach to AI (IAPP.ORG)

While everyone is talking about AI Governance, my colleague D. Marty Esquibel and I propose that we do not need to reinvent the wheel. Let's draw inspiration from other industries! Consider what Tech can learn from health care research, Institutional Review Boards (IRBs), and Disclosure Review Boards (DRBs).

Check out a few snippets of the piece below or head over to IAPP.org to read the full piece.

The need for [AI] governance has slowly gained a foothold, and governments and other organizations are starting to create AI governance structures…the most compelling proposals for oversight are often simple. Author and computer scientist Ben Shneiderman suggests the "AI pragmatists" approach of finding oversight parallels in other industries and using them as blueprints to create AI governance. We tend to agree.

We propose that, in the context of AI-oversight, these blueprints can be found in health care research and data protection, specifically within an institutional review board and a disclosure review board…

The IRB/DRB model is a wonderful template for creating an AIRB — a distinct framework that satisfies the needs and requirements of robust AI oversight in both the private and public sectors, with only some necessary tweaks. Utilizing both for guidance allows AI governance to consider the possible human and technical harms respectively or combined.

The efforts behind AI governance should be viewed as evolutionary rather than revolutionary, fitting within the "pragmatist" approach. No novel overthinking is needed when proven solutions provide guidance. Taking the best from the IRB/DRB template and customizing it to fit AI provides a solution that can be implemented quickly, while improving on any historical weaknesses. 

AI governance can seem overwhelming, but it shares many of the issues associated with IRBs/DRBs and can use them as a way forward.