The Chatbot That Foretold Why People Share Secrets With ChatGPT

In the 60 years that ELIZA has been influencing computation and culture, conventional accounts portray it as the earliest example of what we now call chatbots, one that could converse as an automated psychologist. The deceptively simple program is known for “fooling” even the secretary who watched MIT professor Joseph Weizenbaum create it. That’s how the story goes.

However, in all those accounts—even after all its adaptations across programming languages and research fields, in classrooms and popular culture—one essential piece of the story has been missing: the source code for the ELIZA program itself. Our new book, Inventing ELIZA, recovers this source code from the MIT Archives, offering for the first time a close reading and discussion of that code along with newly uncovered dialogs for ELIZA scripts beyond its popular “DOCTOR” persona.

This investigation revealed many ELIZAs: in its different program versions, designed to run a wide variety of scripts or personas, built using a series of technical innovations. Inventing ELIZA seeks to correct and to complicate ELIZA’s history and influence by exploring the misconceptions, multiple versions, and missing code of ELIZA. In this excerpt from the book, we examine one of ELIZA’s earliest interactions, how it laid the groundwork for human relationships with computers for decades to come, and how the complex program continues to speak to the unrestrained drive of today’s AI industry.

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

That dialog has been reprinted countless times and has inspired programmers and writers to dream up many of the chatbots that followed. Yet the closer one inspects that dialog, the more questions arise: Who was this young woman? Was she a real person, or is she the invention of ELIZA creator Joseph Weizenbaum? How exactly did the ELIZA system generate its responses, and how much were they edited? Why did the system work so well to draw people in?

ELIZA, and her “DOCTOR” persona, helped catalyze a mode of thought and an anxiety about people’s relationships with computers. Weizenbaum explored this in his 1976 book Computer Power and Human Reason, invoking philosophical, social, and political critiques. The unique machine interaction presented by his program revealed how new forms of human-computer relation would have profound effects that he attempted to explore and to contest. After seeing its public reception, Weizenbaum was startled by the quick and often emotional attachments people would form with ELIZA, which he saw 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.” The tendency to attribute empathy and invest private feelings into a computer puzzled Weizenbaum. He was concerned by the extent to which people associated rationality with computation, and ascribed understanding and intelligence to computer systems where none existed.

This tendency became known as the “ELIZA effect.” By 1991 the term was appearing in online forums, but its use predated that appearance by decades. 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.

To understand the power and provocation of ELIZA, we can look to the infamous challenge formulated by computer scientist Alan Turing in the essay “Computing Machinery and Intelligence,” in which Turing posed the question “Can Machines Think?” Turing premised his thought experiment on a parlor game—not about technology but about gender: A man and a woman are hidden in a separate room and an interrogator tries to identify who is which gender by asking a series of questions. The man tries to mislead the interrogator, pretending to be a woman, while the woman tries to convince the interrogator of the “correct” answer. That is, both of them claim they are the “real” woman, a challenge to essentialist notions of gender.