What Does It Take to Detect an AI Agent? Minimal Feature Sets for Behavioral Detection under Browser Automation
Bot detectors deployed at scale treat traffic as binary: human or bot. This assumption breaks when AI agents browse the web through browser automation, a traffic class that is neither and that binary classifiers structurally cannot represent. We present a three-class detection framework distinguishing humans, bots, and AI agents, and show that the binary-vs-agent confusion is architectural: a binary human-vs-bot detector misroutes agent sessions because its label space lacks an agent class. On o
Record details
Published: 29 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Jobs & economy · Agents & autonomy
Retrieved: 30 July 2026
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ethics.ai (29 July 2026), “What Does It Take to Detect an AI Agent? Minimal Feature Sets for Behavioral Detection under Browser Automation,” evidence record 14814, https://ethics.ai/record/14814 (originally published by arXiv cs.AI).
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