MIT unearths ELIZA source code, revealing the first chatbot's hidden complexity

The more pointed finding buried in this work is that ELIZA's creator, Joseph Weizenbaum, was himself disturbed by how readily users projected understanding onto the system, a reaction that eventually produced his 1976 critique of AI's social dangers. The recovered code doesn't just rehabilitate ELIZA's technical reputation; it reopens the question of whether that user-projection dynamic was a bug Weizenbaum tried to warn against or the feature that every conversational AI since has quietly depended on.

This is largely disconnected from recent activity in our archive, as we have no prior coverage to anchor it to. It belongs, though, to a slow-building conversation across the broader field about the gap between what large language models actually compute and what users believe is happening inside them. That question, anthropomorphization and the attribution of intent to statistical processes, is arguably the oldest unresolved problem in human-computer interaction, and this archival work gives it a concrete, citable origin point.

Watch whether MIT Press or the researchers behind this analysis follow up with a formal proposal to incorporate ELIZA's design history into AI ethics curricula or model documentation standards within the next 12 months. If that happens, this moves from interesting scholarship to something with actual policy surface area.