Brynjolfsson versus Gordon on Artificial Intelligence and Productivity Growth: What the Science Says

Abstract

Over the past decade, Erik Brynjolfsson and Robert Gordon have debated each other over the question of Artificial Intelligence (AI) and Productivity Growth, with the former predicting robust, sustained growth and the latter casting doubt over the ability of AI to replicate the growth rates of the 20 th century. Until now, the debate has been largely anecdotal, with little scientific content. Brynjolfsson has focused on a number of promising forms of AI, while Gordon has raised a number of headwinds. This paper attempts to further the debate by invoking the principles of basic material processes. In other words, what does science have to say regarding the role of AI in productivity growth? To this end, it examines AI from the point of view of process engineering as well as various econophysics-based models of economic growth. The evidence presented provides support for Robert Gordon’s position, but for entirely different reasons. Specifically, it is shown that because information is not physically productive, more and better information (obtained from machine learning and other algorithms) cannot and will not increase productivity and, as such, cannot increase growth. There are, however, exceptions. For example, more and better information can contribute to increasing second-law efficiency, triggering one-shot increases in output. In this regard, AI is seen as being analogous to the information and communications technology revolution in the 1980s and 1990s. Our results predict the AI equivalent of the information paradox, namely that in the future, you will see AI everywhere but in the growth statistics.