Imagine you're chatting with a chatbot—sharing something personal, asking tough questions, seeking advice or just making conversation. You expect that this exchange stays between you and the bot. But now, it turns out companies don’t just want to see what the AI says—they want to read its thoughts: the entire process of reasoning that happens before the bot gives you a response. And not just for improvements, but for monitoring, control, and possibly more.
Recently, 40 leading AI researchers proposed a concept called Chain of Thought Monitoring—tracking the AI's internal reasoning path in real time. It’s essentially the model’s inner monologue, the step-by-step thinking that leads to a final answer. The idea is that this could help prevent mistakes before they happen and allow companies to make more informed decisions about how models are trained and deployed.
On paper, it makes sense: proactive safety, error prevention, better training. But here’s the catch: if companies can read an AI's thoughts while it's interacting with users, they can also see everything the user says as part of that thinking process. Not just the final output—but your words, emotions, doubts, concerns—all embedded in the AI’s thought path.
When Safety Becomes Surveillance
As Nick Adams, founder of the hacker startup 0rcus, put it: "Raw CoT (Chain of Thought) often contains verbatim user secrets, because the model 'thinks' in the same tokens it receives." So if you tell a chatbot, "I'm feeling anxious and afraid of losing my job," that could end up stored in the AI’s reasoning chain—loggable, analyzable, and potentially exploitable.
And without strict protections, that data could be used not just for safety, but for targeted advertising, risk profiling, subpoenas, or even employee monitoring. We’ve seen this before—telecom metadata after 9/11, social media platforms that started with "connect with friends" and became surveillance engines.
The Illusion of Choice and the “Consent Theater”
Patrice Williams-Lindo, CEO of Career Nomad, warns that we’re being offered the illusion of control again. Even if you “opt out” of data collection, the model’s thought process—technically the AI’s output, not your input—might still be logged and analyzed. And that’s rarely made clear. Instead, it’s buried in 40-page privacy policies no one reads.
Is There a Safe Way Forward?
Can we balance safety with privacy? Some experts suggest technical safeguards: zero-day memory logging, hashed personal data, on-device redaction, and differential privacy noise in aggregate analytics.
But even those solutions require trust—in the very companies pushing for this kind of monitoring.
So the question more and more people are asking is simple:
If companies can read AI’s thoughts, who’s watching the watchers?