Fausto Gernone

In The You On AI Field Guide

Gernone's work with Mazzucato applied the creation-extraction framework to dimensions of the AI economy that had received less analytical attention — particularly the relationship between generative AI and creative labor. Their argument that generative AI models are trained on publicly accessible creative content yet offer little to the artists, journalists, coders, and others who produce it named a specific structural injustice with policy implications.

The July 2025 analysis proposed that a levy on AI firm revenues fund creative production — treating creative knowledge explicitly as a public good that requires collective funding, and recognizing that extraction, if unchecked, destroys the base on which future value creation rests. The levy proposal became part of the broader windfall taxation framework Mazzucato has advanced for the AI economy.

Gernone's contribution to the collaboration has been the policy-specification dimension — translating Mazzucato's analytical framework into concrete policy mechanisms that governments could implement. This work sits at the interface between academic analysis and operational policy design, a boundary IIPP was explicitly founded to bridge.

Origin

Gernone's academic training and policy career have centered on applied innovation economics and the political economy of technological change. His collaboration with Mazzucato began through IIPP and has focused primarily on the AI-specific applications of her framework that intensified in 2024–2025.

Key Ideas

Creative labor extraction. The specific application of the creation-extraction framework to the relationship between AI and human creative work.

Policy specification. Translating analytical frameworks into operational policy mechanisms.

Levy on AI revenues. The specific policy instrument proposed for funding creative production sustained by AI training data.

Incentive alignment. The argument that current AI incentives are aligned for rent extraction rather than value creation.