“Tear down this wall!”: Reducing entry barriers in the development and application of AI
In a new policy paper, R Street technology policy fellow Caleb Watney lays out a framework that can begin to address these various issues, provides an overview of the various inputs to the production function of AI and analyzes the policies that should be reconsidered or implemented to reduce these barriers.
The paper argues that reducing entry barriers in AI development and application can help address concerns both about the degree of industrial concentration and the slow speed of AI diffusion across the economy. By targeting bottlenecks in the supply of skilled AI analysts, the supply of data and access to specialized hardware, we can reduce these barriers, which have been inadvertently created by government policies. In addition, alternative policy frameworks like more stringent antitrust action are inherently higher-risk strategies when compared to reducing entry barriers.
The author adds, “[t]here are significant barriers to entry in AI development that have boosted the market power of incumbent firms. If new startups can successfully compete in the absence of these barriers, it will be a win for innovation, consumers and for the dynamism of the economy as a whole.
