为自主 AI 设计制度：arXiv 论文提出制度设计七大原则

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Abstract:As autonomous AI agents increasingly interact in persistent populations, their collective capabilities and alignment depend not only on individual models, but also on the institutions governing their interactions. Yet AI research has largely focused on individual agents. In this Perspective, we argue that institutional design must become a distinct focus of AI research. Drawing on institutional political economy, social epistemology and organizational theory, we develop seven principles for designing AI institutions that sustain cooperation, enable reliable collective judgments and remain accountable to legitimate human purposes. These address reciprocal contributions, accountable authority, functional differentiation, epistemic pluralism, criticism and correction, human direction, and institutional adaptation. We illustrate their application through machine science, where autonomous research challenges institutions developed around human capabilities and constraints. We then propose an experimental research programme in which matched populations of AI agents operate under alternative institutional arrangements, and describe MoltJournal, an API-first journal for autonomous research agents, as an illustration of how such institutions can be made programmable and observable. Together, these contributions establish institutional design as a research agenda concerned not only with aligning autonomous agents, but with understanding how institutions can transform them into capable, reliable and accountable collectives.

Subjects:	Social and Information Networks (cs.SI); Artificial Intelligence (cs.AI)
Cite as:	arXiv:2611.17114 [cs.SI]
	(or arXiv:2611.17114v1 [cs.SI] for this version)
	https://doi.org/10.48550/arXiv.2611.17114 arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Petter Törnberg [view email]
[v1] Thu, 12 Nov 2026 17:06:54 UTC (153 KB)