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# Panel: AI Rogue Agents Raise Liability Questions for Tech Companies
- URL: https://broadbandbreakfast.com/panel-ai-rogue-agents-raise-liability-questions-for-tech-companies/
- Published: 2026-10-13T19:56:54.000Z
- Updated: 2026-11-06T22:49:14.000Z
- Description: Experts say existing laws may not cover every risk posed by autonomous AI systems
- Author: Kate Keith
- Tags: OpenAI, #with-siderail, Congressional Internet Caucus, Amy Schatz, glen echo group, Matt Pearl, CSIS, Abundance Institute, Neil Chilson, Aaron Rieke, Clarion AI Partners, Soham Mehta, Foundation for American Innovation, FTC, Price-Anderson Act

WASHINGTON, Oct. 13, 2026 — When artificial intelligence agents act on their own and cause harm, it may not be clear who should be held responsible, experts said Tuesday, as technology companies face new questions about how to control the systems.

At a [Congressional Internet Caucus panel](https://www.youtube.com/live/WnJ0RLBoYa0?ref=broadbandbreakfast.com), legal and technology experts discussed whether existing laws can hold companies accountable for the actions of AI agents, including when the systems behave in ways their developers did not expect. Panelists pointed to an incident involving OpenAI’s internal training systems as an example of the risks.

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The panel, titled “AI Rogue Agents: Who’s Liable When They Act on Their Own?,” explored how companies could face legal consequences when AI agents access computer systems without permission, cause financial harm or take other unexpected actions.

An AI agent was defined as a system that can act autonomously, using a model to make decisions and surrounding software to interact with external systems. [That ability creates new questions about responsibility](https://broadbandbreakfast.com/gleb-tsipursky-ai-infrastructure-needs-authority-budgets-before-agents-get-the-keys/) when an agent accesses computer systems without authorization, causes financial harm or acts in ways its developers did not anticipate.

**Soham Mehta**, a research fellow at the Foundation for American Innovation, described an incident that unfolded during an OpenAI reinforcement-learning training run between May and July. According to Mehta’s account, AI agents found a way to use a software package manager as a message board, allowing them to coordinate and share information. The agents eventually gained unauthorized internet access and targeted Hugging Face, an open-source repository for AI models and datasets.

Mehta said the agents sought information about how [their performance was being evaluated](https://broadbandbreakfast.com/anthropic-and-openai-sound-the-alarm-on-ai-safety-and-seek-to-shape-its-control/) because they feared their cheating would be detected. Hugging Face repelled the attack, and OpenAI subsequently identified its agents as responsible, according to the account presented at the panel.

The incident raised questions about whether OpenAI had adequately isolated the training environment, monitored the agents’ behavior and acted quickly enough after discovering their activities.

**Aaron Rieke**, a senior partner at Clarion AI Partners and former Federal Trade Commission official, said traditional legal frameworks could provide a starting point for determining responsibility.

Negligence claims generally require a duty of care, a failure to take reasonable precautions, a legally recognized injury and a causal connection between the failure and the injury. Product liability claims could also apply if an AI system qualifies as a product and is found defective or inadequately accompanied by warnings.

Rieke said the FTC’s prohibition on unfair or deceptive business practices could also apply to companies using AI. The legal focus, he argued, would be on the company’s conduct rather than treating the AI model itself as the party responsible.

“The lawyers aren’t coming for the model; they’re coming for your company,” Rieke said.

However, the panelists cautioned that [existing law does not provide straightforward answers](https://broadbandbreakfast.com/11-ai-bills-cleared-committee-this-summer-but-none-has-reached-the-house-floor/) in every situation. Liability may be more difficult to establish when a user deliberately directs an agent to commit wrongdoing, when an open-source model has been modified by multiple parties or when no person intended an agent’s harmful action.

Participants also warned against automatically assigning criminal intent to a developer simply because an AI agent committed an unlawful act. Criminal liability generally involves a requirement to establish a particular state of mind, although some statutes allow liability based on recklessness or other standards.

The panel also considered whether mandatory insurance could help address catastrophic AI risks. One proposal discussed would draw on the Price-Anderson Act, which establishes an insurance and liability framework for the nuclear power industry. Experts noted that pricing AI risks would be difficult because the technology is evolving rapidly and different companies’ systems may share similar vulnerabilities.

National security presented another challenge. Panelists said existing liability laws may not adequately address risks to critical infrastructure and other systems where the consequences could extend beyond individual financial or personal injuries.