SovereignNegotiation-Bench: Evaluating User-Owned Personal Agents In Delegated Bargaining Under Privacy, Consent, Evidence, And Institutional Pressure
arXiv:2607.02814v1 Announce Type: cross Abstract: Personal agents will increasingly negotiate on behalf of users: splitting costs with other personal agents, appealing platform decisions, escalating support disputes, requesting refunds, changing subscriptions, and negotiating deadlines or reimbursements. Existing negotiation benchmarks emphasize agreement, surplus, or strategic competence, but a user-owned agent can reach an agreement while harming the user through privacy leakage, consent violation, unsupported advocacy, over-concession, failed escalation, or poor auditability. We introduce S
The proliferation of advanced AI models necessitates a rigorous framework to evaluate their autonomous negotiation capabilities, especially as they move into user-owned contexts and handle sensitive operations.
Evaluating user-owned personal agents under real-world constraints like privacy and institutional pressure is crucial for their safe and effective deployment, preventing harm to users even when agreements are reached.
The focus for AI agent development shifts beyond mere agreement or surplus to include critical evaluation of user protection, auditability, and adherence to ethical boundaries during autonomous negotiations.
- · AI ethicists
- · Compliance software providers
- · Users of personal AI agents
- · Developers of robust, secure AI agents
- · Developers of unconstrained AI agents
- · Platforms with opaque decision-making
- · Users of poorly designed personal AI agents
This benchmark will drive the development of more sophisticated and trustworthy personal AI agents.
Increased trust in AI agents will accelerate their adoption across various consumer and enterprise interactions.
The legal and regulatory frameworks for autonomous agents will likely evolve rapidly to address issues surfaced by such evaluation benchmarks.
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