Framework

Institutionalist approach to AI governance

The question it answers

When setting rules for its AI products, should an AI firm's leadership write its own standards or back binding public law that covers the whole sector?

Origin
Ferretti, 2022; Ferretti, 2024
Diagram type
Hub diagram
Level of analysis
Industry
Topics
AI for leadersEthics & corporate governance
Glass sphere with a glowing neural-network core, icon for AI for leaders

Diagram

Institutionalist approach to AI governance

Public regulation over self-regulation
Legitimacy: democratic process confers authority
Stability: binding law covers the whole sector; markets weaken self-regulation
Efficiency: central coordination, redistributing impacts
Exception: when government fails, firms' political duties widen
AI exposes existing institutional vulnerabilities

Sources

References

Listed A–Z by author surname, Harvard style. A source with a DOI links to https://doi.org/…; one without links to its page or says plainly that it has no DOI.

  1. Ferretti, T. (2022) ‘An institutionalist approach to AI ethics: justifying the priority of government regulation over self-regulation’, Moral Philosophy and Politics, 9(2), pp. 239–265.doi:10.1515/mopp-2020-0056Source page
  2. Ferretti, T. (2024) ‘Value alignment without institutional change cannot prevent the societal risks of artificial intelligence’, LSE Public Policy Review, 3(3), article 2.doi:10.31389/lseppr.113Source page