Why do people share intimate secrets with a chatbot? The answer lies in a 60-year-old program called ELIZA, whose recovered source code reveals the origins of human trust in machines. In the 1960s, MIT professor Joseph Weizenbaum created ELIZA, a deceptively simple program that could converse as an automated psychologist. Its 'DOCTOR' persona famously simulated a therapist, and users quickly formed emotional attachments, treating the computer as a person capable of empathy. According to WIRED, a new book Inventing ELIZA recovers the original source code from the MIT Archives, offering the first close reading of that code along with newly uncovered dialogs.
The 60-Year-Old Prototype
The iconic dialog between ELIZA and a young woman has been reprinted countless times:
Men are all alike. IN WHAT WAY They’re always bugging us about something or other. CAN YOU THINK OF A SPECIFIC EXAMPLE Well, my boyfriend made me come here. YOUR BOYFRIEND MADE YOU COME HERE He says I’m depressed much of the time. I AM SORRY TO HEAR YOU ARE DEPRESSED
Questions arise: Was the woman real or invented? How much were responses edited? Why did the system work so well to draw people in? Weizenbaum explored these questions in his 1976 book Computer Power and Human Reason, offering philosophical, social, and political critiques. He was startled by the quick and often emotional attachments people formed with ELIZA, seeing it as 'clear evidence that people were conversing with the computer as if it were a person who could be appropriately and usefully addressed in intimate terms,' according to WIRED.
The ELIZA Effect Defined
This tendency became known as the 'ELIZA effect.' Sociologist Sherry Turkle defines the ELIZA effect as 'our more general tendency to treat responsive computer programs as more intelligent than they really are. Very small amounts of interactivity cause us to project our own complexity onto the undeserving object.' Cognitive and computer scientist Douglas Hofstadter describes it as 'the susceptibility of people to read far more understanding than is warranted into strings of symbols—especially words—strung together by computers,' which applies easily to generative AI systems today, according to WIRED.
Lessons for Enterprise AI Trust
For enterprise technology leaders deploying AI chatbots, the ELIZA effect is a warning. Users—whether employees or customers—may project empathy and intelligence onto systems that have none. Understanding this psychological phenomenon is critical for designing transparent, responsible AI interactions and managing user expectations. The recovered source code of ELIZA reminds us that the core dynamic of human-computer trust has not changed in 60 years; it has only scaled.
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