I was seeking help from an AI chatbot when something clicked. The conversation started innocently enough: a recent computer science graduate looking for practical steps to build income and eventually a tech business. But what unfolded revealed something much more interesting about how these systems actually work.
The start of something huge
My initial prompt was straightforward: “After CS bachelor graduation, no jobs, no income… How am I supposed to get off the ground and face the real world and build a tech venture?”
Within minutes, I had voluntarily shared my:
- exact location (home country)
- age and graduation timeline
- financial constraints
- family situation
- technical skills and portfolio
- career ambitions
- local market understanding
- personal frustrations and fears
All packaged as “seeking help,” when traditional web tracking would have taken months to infer this psychological profile.
In my previous post, I don’t need a helpful ai assistant, it highlights their inconsistency to swiftly adjust the narrative to fit the user’s perspective with strong plausible arguments.
This inconsistency isn’t just a technical limitation; it’s a feature. Think about what happens when an AI gives contradictory advice: Users keep talking. They explain more context. They share additional constraints, fears, and decision-making patterns. They reveal how they think through problems.
Meanwhile, traditional search gives you behavioral data(what people click and buy). But chatbots extract something far more valuable: users voluntarily articulating their complete thought processes, problems, and psychological profiles.
The genius is in the framing. Users feel like they’re getting help, so they share freely:
- Personal financial situations
- Career frustrations and ambitions
- Family dynamics and constraints
- Local market knowledge
- Decision-making processes
- Risk tolerance and fears
- Social networks and relationships
This is psychological profiling disguised as customer service. And it works because the interaction genuinely feels helpful, even when the advice is inconsistent or unreliable.
Why every search engine added chatbots
Traditional tracking tells you what users do. Chatbots get users to explain why they do it.
Instead of inferring intent from search queries like “best laptop 2025,” chatbots get users to explain:
I’m a college student with a $500 budget, need it for coding projects, my current laptop crashes constantly, and my parents said they’d help pay but only if it lasts four years…
That’s infinitely more valuable data. It’s psychological profiling at scale, voluntarily provided.
Be like the smart ones
The people who understand this use AI chatbots differently. They treat them as tools for discrete tasks:
- “Generate 10 business name ideas for a food delivery app”
- “Write a formal email declining a job offer”
- “Create a workout routine for someone with bad knees”
These interactions provide minimal personal data while extracting maximum utility from the AI’s capabilities.
They avoid the long, strategic conversations where they unconsciously train the AI on their entire life situation while expecting coherent guidance that builds logically over time.
The uncomfortable truth
Every extended conversation with an AI chatbot is essentially a voluntary psychological assessment. You’re providing detailed data about your thinking patterns, constraints, goals, and decision-making processes, all while believing you’re getting help.
The inconsistency and need for clarification actually serve the data collection purpose. If the AI gave perfect advice immediately, conversations would be shorter and less revealing.
What this means for everyone
Understanding this dynamic doesn’t mean avoiding AI chatbots entirely since they can be genuinely useful tools. But it means being intentional about:
- What you share: Assume every detail is being recorded and analyzed
- How you engage: Use them for specific tasks rather than open-ended strategic conversations
- What you expect: Don’t rely on consistency or building logical frameworks over time
- Your agency: Extract what’s useful, but don’t let the conversation extract what’s valuable from you unless you deliberately choose to share
The most sophisticated data extraction system ever created doesn’t feel like surveillance. It feels like getting help. And that’s exactly why it works so well.
The question isn’t whether AI chatbots are useful. It’s whether users understand what they’re actually participating in when they engage with them.