Researcher and software engineer interested in applying economics to AI safety
The core focus of my research is using agent-based modelling to understand real-world complex-adaptive systems which are composed of interacting autonomous agents. The key research question that I am interested in is how, and if, these systems maintain macroscopic homeostatic behaviour despite the fact that their constituent agents often face an incentive to disrupt the rest of the system for their own gain. This question pervades the biological and social sciences, as well as many areas of engineering and computing. Accordingly, I work with a diverse range of collaborators in different disciplines. I am particularly interested in whether models of learning and cooperation can be validated against empirical studies, and I have had the opportunity to apply many different modelling techniques to a diverse range of data.
https://sphelps.net/
https://sphelps.substack.com/
https://github.com/phelps-sg
This problem has been studied extensively by economists within the field of organizational economics, and is called the principal-agent problem (Jensen and Meckling, 1976). In a principal-agent problem a principal (e.g. firm) hires an agent to perform some task. Both the principal and the agent are assumed to be rational expected utility maximisers, but the utility function of the agent and that of the principal are not necessarily aligned, and there is an asymmetry in the information available to each party. This situation can lead the agent into taking actions that are not in the principal’s interests.
(image by Zirguezi)As the OP suggests, incentive schemes, such as performance-conditional payments, can be used to bring the interests of the principal and the agent into alignment, as can reducing information asymmetry by introducing regulations enforcing transparency.
The principal-agent problem has also been discussed in the context of AI alignment. I have recently written a working-paper on principal-agent problems that occur with AI agents instantiated using large-language models; see arXiv:2307.11137.
References
Jensen and W. H. Meckling, “Theory of the firm: Managerial behavior, agency costs and ownership
structure,” Journal of Financial Economics 3 no. 4, (1976) 305–360
S. Phelps and R. Ranson, “Of Models and Tin Men—a behavioural economics study of principal-agent problems in AI alignment using large-language models”, arXiv:2307.11137, 2023.