Incomplete Contracting and AI Alignment

TL;DR

This paper proposes using incomplete contracting theory from law and economics to better understand and address the AI alignment problem, emphasizing the role of external structures like institutions in human contracts.

Contribution

It introduces a novel framework linking incomplete contracting insights to AI alignment, focusing on replicating human cognitive processes supported by external structures.

Findings

Economic analysis of incomplete contracts offers insights for AI alignment.

External structures like law and culture support human contracts and can inform AI design.

A research agenda is proposed to develop AI systems that emulate human reliance on external structures.

Abstract

We suggest that the analysis of incomplete contracting developed by law and economics researchers can provide a useful framework for understanding the AI alignment problem and help to generate a systematic approach to finding solutions. We first provide an overview of the incomplete contracting literature and explore parallels between this work and the problem of AI alignment. As we emphasize, misalignment between principal and agent is a core focus of economic analysis. We highlight some technical results from the economics literature on incomplete contracts that may provide insights for AI alignment researchers. Our core contribution, however, is to bring to bear an insight that economists have been urged to absorb from legal scholars and other behavioral scientists: the fact that human contracting is supported by substantial amounts of external structure, such as generally available institutions (culture, law) that can supply implied terms to fill the gaps in incomplete contracts. We propose a research agenda for AI alignment work that focuses on the problem of how to build AI that can replicate the human cognitive processes that connect individual incomplete contracts with this supporting external structure.