This paper surveys the relevant existing literature that can help researchers and policy makers understand the drivers of competition in markets that constitute the provision of artificial intelligence products. The focus is on three broad markets: training data, input data, and AI predictions....

This paper investigates the alignment of existing securities regulations with the emerging landscape of crypto-tokens and blockchain technology. By examining the features of these digital assets, including decentralization, consensus mechanisms, and programmability, we analyze how they interact...

This paper examines recent proposals and research suggesting that AI adoption should be delayed until its potential harms are properly understood. It is shown that conclusions regarding the social optimality of delayed AI adoption are sensitive to assumptions regarding the process by which...

New generative artificial intelligence (AI) models, including large language models and image generators, have created new challenges for copyright policy as such models may be trained on data that includes copy-protected content. This paper examines this issue from an economics perspective and...

This paper robustly concludes that it cannot. A model is constructed under idealised conditions that presume the risks associated with artificial general intelligence (AGI) are real, that safe AGI products are possible, and that there exist socially-minded funders who are interested in funding...

Mobile app commissions paid by app developers to a monopolist device maker/app store operator are examined. Three results are demonstrated. First, unregulated app commissions are set at a level that maximises consumer surplus. Second, eliminating app commissions will lead to higher device...

This paper examines the impact of Generative AI (GAI) on communication through the lens of salience and signalling models. It explores how GAI affects both senders' ability to create salient messages and receivers' costs of absorbing them. The analysis reveals that while GAI can increase...

This paper examines the regulation of technological innovation direction under uncertainty about potential harms. We develop a model with two competing technological paths and analyze various regulatory interventions. Our findings show that market forces tend to inefficiently concentrate...

When AI prediction substantially resolves trial uncertainty, a party purchasing AI prediction will disclose it if it is in their favour and not otherwise, signalling the outcome to the other party. Thus, the trial outcome becomes common knowledge. However, this implies that the parties will...

This paper examines and finds that the answer is likely to be no. The environment examined starts with users who contribute based on their motives to create a public good. Their own actions determine the quality of that public good but also embed a free-rider problem. When AI is trained on that...