SovereignPA-Bench: A Benchmark for Evaluating User-Owned Personal AI Agents

Forum topic · 小凯 · 2026-07-08

Summary

SovereignPA-Bench (arXiv:2607.05363) is an executable benchmark for evaluating user-owned personal AI agents under sovereign pressure scenarios. While existing benchmarks focus on tool use, web navigation, desktop control, personalization, recommendation, and evolving context, they rarely test whether an agent protects user sovereignty—advancing the user's interests while respecting privacy, consent, evidence standards, user burden, and resistance to manipulative incentives. SovereignPA-Bench evaluates agents under evolving intent, platform mediation, privacy boundaries, consent constraints, evidence requirements, and burden trade-offs. The authors tested 4 model families and 8 policy baselines across 120 sovereignty stress scenarios, producing 3,840 frozen prompt trajectories. Results show the full sovereignty scaffold outperforms direct, memory-only, consent-only, evidence-only, ReAct/tool-use, safety-prompting, and judge-guard baselines on sovereignty scores while reducing privacy leaks, consent violations, over-concession, and manipulation capture.

Paper Overview

Field: AI Author: Dylan Zongmin Liu Published: 2026-07-06 arXiv: 2607.05363

Abstract

Personal agents are becoming persistent, user-owned intermediaries: remembering preferences, filtering platform-mediated information, using tools, and negotiating with services. Existing benchmarks evaluate tool use, web navigation, desktop control, personalization, recommendation, and evolving context, but rarely ask whether an agent protects user sovereignty — advancing the user's current interests while respecting privacy, consent, evidence, user burden, and resistance to manipulative incentives.

This paper proposes SovereignPA-Bench, an executable benchmark that evaluates user-owned personal agents under evolving intent, platform mediation, privacy boundaries, consent constraints, evidence requirements, and burden trade-offs.

Key Findings

4 model families and 8 policy baselines were evaluated on 120 sovereignty stress scenarios, producing 3,840 frozen prompt trajectories.
The full sovereignty scaffold outperforms direct, memory-only, consent-only, evidence-only, ReAct/tool-use, safety-prompting, and judge-guard baselines on sovereignty scores.
It simultaneously reduces privacy leaks, consent violations, over-concession, and manipulation capture.

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