Relative Principals, Pluralistic Alignment, and the Structural Value Alignment Problem
The value alignment problem for artificial intelligence (AI) is often framed as a purely technical or normative challenge, sometimes focused on hypothetical future systems. I argue that the problem is better understood as a structural question about governance: not whether an AI system is aligned in the abstract, but whether it is aligned enough, for whom, and at what cost. Drawing on the principal-agent framework from economics, this paper reconceptualises misalignment as arising along three interacting axes: objectives, information, and principals. The three-axis framework provides a systematic way of diagnosing why misalignment arises in real-world systems and clarifies that alignment ...
| Authors | Travis LaCroix |
|---|---|
| Primary category | cs.CY |
| Published | 22 April 2026 |
| Last updated at source | 22 April 2026 |
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