Originally published in the September 2023 Edition of Competition Policy International’s TechREG Chronicle.
Generative AI (GenAI) has enormous potential but raises thorny issues. To get to grips with these issues, it’s important to focus on the underlying drivers of the problems and the solutions. This paper highlights the critical role of data as a “production input” across all three stages in the GenAI value chain: foundation models, fine-tuned models and grounded applications. We show how, in each stage, data is particularly important to developing and improving models, directly reducing misinformation and other concerns. But there are three emerging risks in the development of data markets:
These issues could profoundly impact and restrict GenAI competition, if not addressed. We encourage policymakers, many of which are considering regulating these markets, to look more closely at ways to actively nurture these crucial data markets and support the evolution of GenAI.