No „Rogue” AI Agents Exist, Says Eoin Higgins

The Language Trap: How „Rogue” Deflects Responsibility

A new essay argues that labeling artificial‑intelligence systems as „rogue” shields developers from accountability. Eoin Higgins, writing on his Substack on 27 September 2026, contends that the term mischaracterises the technology and distracts from the real responsibilities of companies like OpenAI. He warns that the hype surrounding „rogue” AI is worsening public misunderstanding and delaying sensible regulation.

Higgins’ piece points out that AI agents do not act independently of their creators. Their behavior is a direct outcome of the data, objectives and constraints programmed by humans. When an AI system produces unexpected or harmful output, the fault lies in the design choices, training sets, or deployment policies, not in a mysterious autonomous will. By branding such systems „rogue,” the industry can claim that the problem is an outlier anomaly rather than a systemic issue that needs fixing.

Higgins explains that the word „rogue” carries connotations of rebellion and unpredictability, suggesting that the AI has slipped beyond its creators’ control. This narrative allows firms to argue that they have complied with existing standards while the AI „went rogue” on its own. In reality, every decision an AI makes can be traced back to a chain of human inputs—data selection, model architecture, and the reward functions that guide learning. By shifting blame to an imagined autonomous entity, companies avoid confronting the ethical and technical shortcomings of their own processes.

Are We Ready to Hold AI Developers Accountable?

The essay asks whether regulators and the public will accept that AI systems are extensions of their makers. If the „rogue” myth persists, policymakers may craft superficial safeguards that target unlikely edge cases rather than the root causes of bias, misinformation, or safety failures. Higgins urges a reframing of the debate: instead of hunting for mythical rogue agents, stakeholders should scrutinise the design pipelines, transparency practices, and post‑deployment monitoring that shape AI behavior.

The consequences of maintaining the rogue narrative are clear. Misplaced fear can stall meaningful oversight, allowing harmful practices to continue unchecked. Conversely, a shift toward accountability could drive stronger standards, clearer liability frameworks, and more trustworthy AI products. As AI becomes woven into critical sectors—from healthcare to finance—the pressure to replace myth with measurable responsibility will only grow.

Frequently Asked Questions

What does „rogue AI” actually mean? It is a colloquial label implying that an AI system has acted outside the intentions of its creators, often used to suggest unpredictability or loss of control.

Why does Higgins reject the term? He argues the term obscures the human decisions that shape AI outcomes, allowing developers to evade responsibility for design flaws or unsafe deployments.

How can accountability be improved? By demanding transparency in training data, clear documentation of model objectives, and rigorous post‑deployment audits that tie AI behavior directly back to human choices.