Is Generative AI an Existential Threat to Human Creatives? Insights from Financial Economics
This addresses fears about job displacement for human creatives, offering a theoretical counterargument, but it is incremental as it applies an existing economic insight to a new domain.
The paper tackles the concern that generative AI might replace human creatives by arguing it is impossible, drawing an analogy to financial economics to show a paradox where AI would rely on stale information if humans stopped creating new content.
With the phenomenal rise of generative AI models (e.g., large language models such as GPT or large image models such as Diffusion), there are increasing concerns about human creatives' futures. Specifically, as generative models' power further increases, will they eventually replace all human creatives' jobs? We argue that the answer is "no," even if existing generative AI models' capabilities reach their theoretical limit. Our theory has a close analogy to a familiar insight in financial economics on the impossibility of an informationally efficient market [Grossman and Stiglitz (1980)]: If generative AI models can provide all the content humans need at low variable costs, then there is no incentive for humans to spend costly resources on content creation as they cannot profit from it. But if no human creates new content, then generative AI can only learn from stale information and be unable to generate up-to-date content that reflects new happenings in the physical world. This creates a paradox.