We study the impact of Moore’s law on productivity growth and changes in the labor share. Motivated by the fact that the ratio of computation to labor in production is rising, while both the labor and computational shares are declining, we develop a novel production function with both labor- and computation-augmenting productivity terms. Using this setup, we estimate a production function in order to quantify the effects of computation and other IT inputs on productivity growth and the fall in the labor share.
New technologies with military applications may demand new modes of governance. In this article, we develop a taxonomy of technology governance forms, outline their strengths, and red-team their weaknesses. In particular, we consider the challenges and opportunities posed by advancing artificial intelligence, which is likely to have substantial dual-use properties. We conclude that it is too soon to tell whether a non-proliferation regime, a verification-based regime, or an International Monopoly is most feasible for governing AI. Nonetheless, a variety of policies would yield a high return across all three scenarios, and we conclude by identifying some of these steps that could be taken today.
We assess the impact of deep learning on the economy by estimating the idea production function for AI in two computer vision tasks that are considered key test-beds for deep learning and show that AI idea production is notably more capital-intensive than traditional R&D and suggests that AI-augmented R&D has the potential to speed up technological change and economic growth.
A formal model reveals how the information environment affects international races to implement a powerful, dangerous new military technology, which may cause a ''disaster'' affecting all states. States implementing the technology face a tradeoff between the safety of the technology and performance in the race. We study the role of information and uncertainty on the probability of a disaster.