Essays on the Economics of Artificial Intelligence and Innovation

With the field of AI evolving at an unprecedented pace, many countries are attempting to acquire and diffuse new knowledge. In many areas, AI systems have become essential elements of sector-specific innovation, such as in the medicine, automotive, chemistry, and biotechnology sectors, and many more. Despite these efforts, the implications of this technological success story are poorly understood.

The first essay of the dissertation seeks to contribute to explaining the development and emergence of AI research and innovation across regions worldwide, focusing on three important elements: scientific paradigms, enabling technologies, and diffusion processes.

Scientific paradigms refer to the presence of multiple schools of thought. Enabling technologies play a critical role in the development of AI by providing the necessary hardware and software infrastructure to run and scale AI algorithms and models. In particular, Graphics Processing Units (GPUs) have played a major role in the development of deep learning. Diffusion processes set in once an attractive new technology has been found and demonstrated to work well. To understand the diffusion of knowledge in the field of AI, it is necessary to consider the interplay between regional specialization towards different paradigms, the command of enabling technologies, and the regional endowment with critical human capital.