From Eliza to ChatGPT: why people spent 60 years building chatbots

People have been trying to talk to computers for almost as long as they’ve been building computers. For decades, many in tech have been convinced that this was the trick: if we could figure out a way to talk to our computers the way we talk to other people, and for computers to talk back the same way, it would make those computers easier to understand and operate, more accessible to everyone, and just more fun to use.

ChatGPT and the current revolution in AI chatbots is really only the latest version of this trend, which extends all the way back to the 1960s. That’s when Joseph Weizenbaum, a professor at MIT, built a chatbot named Eliza. Weizenbaum wrote in an academic journal in 1966 that Eliza “makes certain kinds of natural language conversation between man and computer possible.” He set up the bot to act as a therapist, a vessel into which people could pour their problems and thoughts. 

The tech behind Eliza was incredibly primitive: users typed into a text field, and the bot selected from a bunch of predefined responses based on the keywords in your question. If it didn’t know what to say, it would just repeat your words back — you’d say “My father is the problem” and it would respond “Your father is the problem.” But it worked! Weizenbaum wrote in another paper a year later that it had been hard to convince people that there wasn’t a human on the other side of their conversation.

What Eliza showed, and what other developers and engineers have spent the next six decades working on, is that we treat our devices differently when we think of them as animate, human-like objects. And we are remarkably willing to treat our devices that way. (Have you ever felt bad for your robot vacuum as it bonks its way around your living room, or thanked Alexa for doing something for you?) It’s human nature to anthropomorphize objects, to imbue them with human qualities even when they don’t have any. And when we do that, we’re kinder to those objects; we’re more patient and collaborative with them; we enjoy using them more.

Examples of what this could look like are everywhere in pop culture. The Star Trek computer is a classic inspiration for Silicon Valley types — “Tea. Earl Grey. Hot.” — as is Scarlett Johansson’s ambient AI in Her. HAL 9000 in 2001: A Space Odyssey is both an inspiration and a cautionary tale, as is WOPR from WarGames. These are computers that think, that talk, that understand.

The only problem with all these human-like computers? They are remarkably hard to pull off. A bot like Eliza could generate somewhat convincing conversation, but that only gets you so far. Most of the time, your computer’s job is to do stuff, and these chatbots have never been very good at doing stuff. There have been people working on that, too: a group at Xerox PARC in the 1970s built a chatbot you could use to book plane tickets, but it was finicky and slow and wildly expensive to run. There have been countless attempts since to do the same thing.

Over the years, there have been many versions of these tools. There were other early chatbots, like Dr. Sbaitso, Parry, and Alice. In the early aughts, there was SmarterChild, the irreverent AIM bot that introduced so many teens and tweens to the idea that a computer could talk back. There was the voice-assistant era, in which everybody thought Siri, Alexa, Cortana, Bixby, and countless other tools would change the way we used our devices and got things done. With every generation, we got a little closer to a computer that could both talk the talk and walk the walk. But nothing ever got there. When was the last time you asked Google Assistant to book you a flight?

Now, we’re at the beginning of a new era in chatbots, one that many in the industry think might actually get the job done. Tools like ChatGPT and Google Gemini, and the underlying language models that power them, are far more capable of both understanding you and getting stuff done on your behalf. Microsoft is betting that Copilot will be your AI companion all day every day at work; Google’s putting Gemini in the same position. These tools aren’t perfect, or even close — they make things up, they misunderstand, they crash, they occasionally go completely haywire — but they’re the closest thing we’ve seen yet to a conversational computer. You talk to it like you’d talk to a person, and it talks back.

The rise of these powerful bots raises lots of questions. Is it cool to think that a computer can fit into your life the way an assistant or friend might, or is it horrifying? Is there something fundamentally wrong with the idea of having an AI companion like the ones from Meta, Replika, or Character.AI, or is there something beautiful about enabling that kind of relationship? How much better do these bots need to get before we can really, truly rely on them? Are they ever going to get that good?

But most of all, we get to finally answer the question we’ve been asking since the ‘60s: is this the way computers should work? Many people have believed so for years, many others have said they’re wrong and that training computers to work like humans would make them less efficient and more annoying. But we never got to find out, because the bots were never good enough to really pit against all the other ways we interact with our devices, our information, and each other. Now they’re close, or at least much closer. And so we get to find out for real whether Joseph Weizenbaum was right all those years ago — that conversation is the future of computation. The chatbot has been the future of computers for almost as long as there have been computers, and now its time has come.