Confessions to a data lake
visual interfaces of our tools should faithfully represent the way the underlying technology works: if a chat interface shows a private conversation between two people, it should actually be a private conversation between two people, rather than a “group chat” with unknown parties underneath the interface.
We are using LLMs for the kind of unfiltered thinking that we might do in a private journal – except this journal is an API endpoint. An API endpoint to a data lake specifically designed for extracting meaning and context. We are shown a conversational interface with an assistant, but if it were an honest representation, it would be a group chat with all the OpenAI executives and employees, their business partners / service providers, the hackers who will compromise that plaintext data, the future advertisers who will almost certainly emerge, and the lawyers and governments who will subpoena access.
When you work through a problem with an AI assistant, you’re not just revealing information - you’re revealing how you think. Your reasoning patterns. Your uncertainties. The things you’re curious about but don’t know. The gaps in your knowledge. The shape of your mental model.
When advertising comes to AI assistants, they will slowly become oriented around convincing us of something (to buy something, to join something, to identify with something), but they will be armed with total knowledge of your context, your concerns, your hesitations. It will be as if a third party pays your therapist to convince you of something.
