When the Watcher Became the Confidant
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When the Watcher Became the Confidant<br>How AI Befriends, Predicts, and Pre-empts Our Children
Jorge Pereira Campos, PhD<br>Jun 12, 2026
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For the better part of the past 70 years, the machines that profile us and the machines we confide in ran on separate tracks. The result of this merger talks to our children every day, and this month, the companies behind it filed to go public.
Photo by Enchanted Tools on Unsplash
Not too long ago, a fifteen-year-old I work with turned her phone around to show me she had screenshotted a message from a boy she liked, pasted it into ChatGPT, and asked what she should say back. Then she read me the reply. How did it feel showing the message and asking for the opinion of a machine instead of that of a person, a close friend, or a parent? She immediately said that she would never show something like that to a parent, maybe a friend, but then again, a friend would be “judgy”. They would remember the interaction, the (potential) rejection.<br>I believe she was wrong about the second part.<br>I am a researcher running an education practice, which means I spend my working days in conversation with teenagers, mostly preparing for university. Over the past five years, I have had more than two hundred conversations with them in which AI came up, more often at their initiative than mine. Somewhere in 2023, the register changed from being homework tools that the students mentioned (e.g., Grammarly or Wolfram) to being ‘things’ that they described the way you and I might describe a person. These ‘new humans’ do not get tired of them; they remember what they said last month and are awake when their best friend and therapist are asleep (“how can those bastards dare to sleep when I need to vent?”). In all fairness, none of my students actually thinks ChatGPT or any other LLM are alive (at least I hope). They simply find that it occupies the role of a confidant or a friend, and they talk to it accordingly, at length, late, about the things they will not say anywhere else.<br>This month, some of the biggest AI companies filed to go public. The filings are confidential for now, so the details are scarce. A listing, though, is not speculative. A private company can, at least in principle, let an engagement number fall for the sake of its youngest users and answer to a manageable room; a listed one is expected to show quarterly market growth, and the market is not famous for its patience. I am aware that the funding rounds were never charity, but a listing formalises it. Whatever the prospectuses turn out to say, the systems my students confide in at three in the morning will be owned by shareholders who are driven, mostly, by profit.
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To see why this combination unsettles me more than a decade of screen-time argument has, you need a piece of history:<br>The first story is about our weakness for machines that listen. In 1956, sociologists Donald Horton and Richard Wohl described what they called intimacy at a distance: the one-sided bonds that television viewers formed with broadcasters who did not know they existed. A decade later, at MIT, Joseph Weizenbaum built ELIZA, the original chatbot. Weizenbaum was quite shocked when people confided in the thing. His own secretary, who had watched him build it and knew exactly what it was, asked him to leave the room so she could talk to it in private. He spent much of his later career warning, to little effect, that the willingness to be heard by a machine ran far deeper than anyone in his field wanted to believe. By 1996, Byron Reeves and Clifford Nass had shown experimentally what Weizenbaum had stumbled into: we automatically and unconsciously extend social rules to machines, and resisting the habit takes deliberate effort.<br>Without wanting to make this too long that it risks taking the TikTok Generation five working days to get through, let me quickly discuss the story of the profile: the credit score, the recommendation engine, the advertising model, and the accretion of inferences about what a person will click on, buy, and eventually want. Its emblem is the American retailer whose statisticians had worked out, by 2012, that they could spot a pregnancy from changes in a shopping basket; in the famous telling, before the girl’s father knew. That story is well into its second decade. Inference about us, conducted at scale and at a distance, is not new.<br>What is new is the merger. Companion apps were selling machine intimacy with memory by 2017; Microsoft had already run an engagement-tuned social chatbot (Zo) at an enormous scale. With the advent of the systems of the past three years came general fluency, homework, mainstream adoption by the hundred million, and, from 2024, memory as a default feature. The once disjointed pieces are now one product. The thing that listens, like ELIZA, profiles like the retailer, and the profile shapes its reply. Effectively, the watcher became the...