# Researchers link AI agent power to human Goal attainment in formal models

Digest AI · Research · published 2026-11-06T05:00:00Z

Canonical: https://digestai.news/story/researchers-link-ai-agent-power-to-human-goal-attainment-in-formal-mod

## Summary

A new paper on arXiv explores how power dynamics between AI agents and humans can be quantified in socio-technical systems. The authors propose two measures: *information-theoretic empowerment*—how much an agent’s actions influence future states—and *capability-based individual power*, which gauges a human’s ability to achieve goals based on probabilistic outcomes. They derive a mathematical relationship showing that empowerment sets an upper bound on *goal revelation*, the mutual information between a human’s latent goal and the realized trajectory, while a lower bound (*B(s)*) is derived from Fano’s inequality.

The work highlights critical failure modes: an AI maximizing empowerment might prioritize broad influence over irrelevant actions, while one maximizing revelation could mislabel goals without improving outcomes. The authors argue that only *satisfaction floors*—calculated from interaction logs—can reliably monitor human power retention. Simulations suggest the three metrics (empowerment, revelation, and satisfaction) correlate but are not interchangeable.

## Key points

- Two formal measures of AI-agent power defined: empowerment (action influence) and capability-based individual power (goal attainment)
- Goal revelation bounded by empowerment (upper limit) and a satisfaction floor (*B(s)*) derived from Fano’s inequality
- Failure modes identified: empowerment-maximizing agents may ignore goal relevance; revelation-maximizing agents may mislabel goals

## Why it matters

This bridges theoretical AI safety with practical human-AI interaction, offering tools to detect power imbalances in deployed systems.

## Sources

1. [Goal Revelation as a Bridge Between Information-Theoretic Empowerment and Capability-Based Human Power](https://arxiv.org/abs/2611.07247) (arXiv cs.AI, 2026-11-06, primary source)

## Cite

Digest AI, "Researchers link AI agent power to human Goal attainment in formal models", 6 November 2026, https://digestai.news/story/researchers-link-ai-agent-power-to-human-goal-attainment-in-formal-mod

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