‘A certain danger lurks there’: how the inventor of the first chatbot turned against AI

From The Guardian:

In 1966, an MIT professor named Joseph Weizenbaum created the first chatbot. He cast it in the role of a psychotherapist. A user would type a message on an electric typewriter connected to a mainframe. After a moment, the “psychotherapist” would reply.

User: Men are all alike.
Chatbot: IN WHAT WAY
User: They’re always bugging us about something or other.
User: Well, my boyfriend made me come here.
User: He says I’m depressed much of the time.

Weizenbaum published this sample exchange in a journal article that explained how the chatbot worked. The software was relatively simple. It looked at the user input and applied a set of rules to generate a plausible response. He called the program Eliza, after Eliza Doolittle in Pygmalion. The cockney flower girl in George Bernard Shaw’s play uses language to produce an illusion: she elevates her elocution to the point where she can pass for a duchess. Similarly, Eliza would speak in such a way as to produce the illusion that it understood the person sitting at the typewriter.

“Some subjects have been very hard to convince that Eliza (with its present script) is not human,” Weizenbaum wrote. In a follow-up article that appeared the next year, he was more specific: one day, he said, his secretary requested some time with Eliza. After a few moments, she asked Weizenbaum to leave the room. “I believe this anecdote testifies to the success with which the program maintains the illusion of understanding,” he noted.

Eliza isn’t exactly obscure. It caused a stir at the time – the Boston Globe sent a reporter to go and sit at the typewriter and ran an excerpt of the conversation – and remains one of the best known developments in the history of computing. More recently, the release of ChatGPT has renewed interest in it. In the last year, Eliza has been invoked in the Guardian, the New York Times, the Atlantic and elsewhere. The reason that people are still thinking about a piece of software that is nearly 60 years old has nothing to do with its technical aspects, which weren’t terribly sophisticated even by the standards of its time. Rather, Eliza illuminated a mechanism of the human mind that strongly affects how we relate to computers.

Early in his career, Sigmund Freud noticed that his patients kept falling in love with him. It wasn’t because he was exceptionally charming or good-looking, he concluded. Instead, something more interesting was going on: transference. Briefly, transference refers to our tendency to project feelings about someone from our past on to someone in our present. While it is amplified by being in psychoanalysis, it is a feature of all relationships. When we interact with other people, we always bring a group of ghosts to the encounter. The residue of our earlier life, and above all our childhood, is the screen through which we see one another.

This concept helps make sense of people’s reactions to Eliza. Weizenbaum had stumbled across the computerised version of transference, with people attributing understanding, empathy and other human characteristics to software. While he never used the term himself, he had a long history with psychoanalysis that clearly informed how he interpreted what would come to be called the “Eliza effect”.

As computers have become more capable, the Eliza effect has only grown stronger. Take the way many people relate to ChatGPT. Inside the chatbot is a “large language model”, a mathematical system that is trained to predict the next string of characters, words, or sentences in a sequence. What distinguishes ChatGPT is not only the complexity of the large language model that underlies it, but its eerily conversational voice. As Colin Fraser, a data scientist at Meta, has put it, the application is “designed to trick you, to make you think you’re talking to someone who’s not actually there”.

But the Eliza effect is far from the only reason to return to Weizenbaum. His experience with the software was the beginning of a remarkable journey. As an MIT professor with a prestigious career, he was, in his words, a “high priest, if not a bishop, in the cathedral to modern science”. But by the 1970s, Joseph Weizenbaum had become a heretic, publishing articles and books that condemned the worldview of his colleagues and warned of the dangers posed by their work. Artificial intelligence, he came to believe, was an “index of the insanity of our world.”

Today, the view that artificial intelligence poses some kind of threat is no longer a minority position among those working on it. There are different opinions on which risks we should be most worried about, but many prominent researchers, from Timnit Gebru to Geoffrey Hinton – both ex-Google computer scientists – share the basic view that the technology can be toxic. Weizenbaum’s pessimism made him a lonely figure among computer scientists during the last three decades of his life; he would be less lonely in 2023.

There is so much in Weizenbaum’s thinking that is urgently relevant now. Perhaps his most fundamental heresy was the belief that the computer revolution, which Weizenbaum not only lived through but centrally participated in, was actually a counter-revolution. It strengthened repressive power structures instead of upending them. It constricted rather than enlarged our humanity, prompting people to think of themselves as little more than machines. By ceding so many decisions to computers, he thought, we had created a world that was more unequal and less rational, in which the richness of human reason had been flattened into the senseless routines of code.

Weizenbaum liked to say that every person is the product of a particular history. His ideas bear the imprint of his own particular history, which was shaped above all by the atrocities of the 20th century and the demands of his personal demons. Computers came naturally to him. The hard part, he said, was life.

. . . .

What it means to be human – and how a human is different from a computer – was something Weizenbaum spent a lot of time thinking about. So it’s fitting that his own humanity was up for debate from the start. His mother had a difficult labour, and felt some disappointment at the result. “When she was finally shown me, she thought I was a bloody mess and hardly looked human,” Weizenbaum later recalled. “She couldn’t believe this was supposed to be her child.”

He was born in 1923, the youngest son of an assimilated, upper-middle class Jewish family in Berlin. His father, Jechiel, who had emigrated to Germany from Galicia, which spanned what is now south-eastern Poland and western Ukraine, at the age of 12, was an accomplished furrier who had acquired a comfortable foothold in society, a nice apartment, and a much younger Viennese wife (Weizenbaum’s mother). From the start, Jechiel treated his son with a contempt that would haunt Weizenbaum for the rest of his life. “My father was absolutely convinced that I was a worthless moron, a complete fool, that I would never become anything,” Weizenbaum later told the documentary film-makers Peter Haas and Silvia Holzinger.

By the time he was old enough to make memories, the Nazis were everywhere. His family lived near a bar frequented by Hitler’s paramilitaries, the SA, and sometimes he would see people getting dragged inside to be beaten up in the backroom. Once, while he was out with his nanny, columns of armed communists and Nazis lined up and started shooting at each other. The nanny pushed him under a parked car until the bullets stopped flying.

Shortly after Hitler became chancellor in 1933, the government passed a law that severely restricted the number of Jews in public schools. Weizenbaum had to transfer to a Jewish boys’ school. It was here that he first came into contact with the Ostjuden: Jews from eastern Europe, poor, dressed in rags, speaking Yiddish. To Weizenbaum, they may as well have come from Mars. Nevertheless, the time he spent with them gave him what he later described as “a new feeling of camaraderie”, as well as a “sensitivity for oppression”. He became deeply attached to one of his classmates in particular. “If fate had been different, I would have developed a homosexual love for this boy,” he later said. The boy “led me into his world”, the world of the Jewish ghetto around Berlin’s Grenadierstrasse. “They had nothing, owned nothing, but somehow supported each other,” he recalled.

One day, he brought the boy back to his family’s apartment. His father, himself once a poor Jewish boy from eastern Europe, was disgusted and furious. Jechiel was very proud, Weizenbaum remembered – and he had reason to be, given the literal and figurative distances he had travelled from the shtetl. Now his son was bringing the shtetl back into his home.

Alienated from his parents, richer than his classmates, and a Jew in Nazi Germany: Weizenbaum felt comfortable nowhere. His instinct, he said, was always to “bite the hand that fed me”, to provoke the paternal figure, to be a pain in the backside. And this instinct presumably proceeded from the lesson he learned from his father’s hostility toward him and bigotry toward the boy he loved: that danger could lie within one’s home, people, tribe.

. . . .

In Weizenbaum’s 1967 follow-up to his first article about Eliza, he argued that no computer could ever fully understand a human being. Then he went one step further: no human being could ever fully understand another human being. Everyone is formed by a unique collection of life experiences that we carry around with us, he argued, and this inheritance places limits on our ability to comprehend one another. We can use language to communicate, but the same words conjure different associations for different people – and some things can’t be communicated at all. “There is an ultimate privacy about each of us that absolutely precludes full communication of any of our ideas to the universe outside ourselves,” Weizenbaum wrote.

This was a very different perspective than that of Minsky or McCarthy. It clearly bore the influence of psychoanalysis. Here was the mind not as a meat machine but as a psyche – something with depth and strangeness. If we are often opaque to one another and even to ourselves, what hope is there for a computer to know us?

Yet, as Eliza illustrated, it was surprisingly easy to trick people into feeling that a computer did know them – and into seeing that computer as human. Even in his original 1966 article, Weizenbaum had worried about the consequences of this phenomenon, warning that it might lead people to regard computers as possessing powers of “judgment” that are “deserving of credibility”. “A certain danger lurks there,” he wrote.

In the mid-1960s, this was as far as he was willing to go. He pointed to a danger, but didn’t dwell on it. He was, after all, a depressed kid who had escaped the Holocaust, who always felt like an impostor, but who had found prestige and self-worth in the high temple of technology. It can be hard to admit that something you are good at, something you enjoy, is bad for the world – and even harder to act on that knowledge. For Weizenbaum, it would take a war to know what to do next.

. . . .

In 1976, Weizenbaum published his magnum opus: Computer Power and Human Reason: From Judgment to Calculation. “The book has overwhelmed me, like being crashed over by the sea,” read a blurb from the libertarian activist Karl Hess. The book is indeed overwhelming. It is a chaotic barrage of often brilliant thoughts about computers. A glimpse at the index reveals the range of Weizenbaum’s interlocutors: not only colleagues like Minsky and McCarthy but the political philosopher Hannah Arendt, the critical theorist Max Horkheimer, and the experimental playwright Eugène Ionesco. He had begun work on the book after completing a fellowship at Stanford University, in California, where he enjoyed no responsibilities, a big office and lots of stimulating discussions with literary critics, philosophers and psychiatrists. With Computer Power and Human Reason, he wasn’t so much renouncing computer science as trying to break it open and let alternative traditions come pouring in.

The book has two major arguments. First: there is a difference between man and machine. Second: there are certain tasks which computers ought not be made to do, independent of whether computers can be made to do them. The book’s subtitle – From Judgment to Calculation – offers a clue as to how these two statements fit together.

For Weizenbaum, judgment involves choices that are guided by values. These values are acquired through the course of our life experience and are necessarily qualitative: they cannot be captured in code. Calculation, by contrast, is quantitative. It uses a technical calculus to arrive at a decision. Computers are only capable of calculation, not judgment. This is because they are not human, which is to say, they do not have a human history – they were not born to mothers, they did not have a childhood, they do not inhabit human bodies or possess a human psyche with a human unconscious – and so do not have the basis from which to form values.

And that would be fine, if we confined computers to tasks that only required calculation. But thanks in large part to a successful ideological campaign waged by what he called the “artificial intelligentsia”, people increasingly saw humans and computers as interchangeable. As a result, computers had been given authority over matters in which they had no competence. (It would be a “monstrous obscenity”, Weizenbaum wrote, to let a computer perform the functions of a judge in a legal setting or a psychiatrist in a clinical one.) Seeing humans and computers as interchangeable also meant that humans had begun to conceive of themselves as computers, and so to act like them. They mechanised their rational faculties by abandoning judgment for calculation, mirroring the machine in whose reflection they saw themselves.

This had especially destructive policy consequences. Powerful figures in government and business could outsource decisions to computer systems as a way to perpetuate certain practices while absolving themselves of responsibility. Just as the bomber pilot “is not responsible for burned children because he never sees their village”, Weizenbaum wrote, software afforded generals and executives a comparable degree of psychological distance from the suffering they caused.

Letting computers make more decisions also shrank the range of possible decisions that could be made. Bound by an algorithmic logic, software lacked the flexibility and the freedom of human judgment. This helps explain the conservative impulse at the heart of computation. Historically, the computer arrived “just in time”, Weizenbaum wrote. But in time for what? “In time to save – and save very nearly intact, indeed, to entrench and stabilise – social and political structures that otherwise might have been either radically renovated or allowed to totter under the demands that were sure to be made on them.”

Link to the rest at The Guardian

5 thoughts on “‘A certain danger lurks there’: how the inventor of the first chatbot turned against AI”

  1. There have been programs for a while that respond to telemarketers and keep them on the phone as long as possible. I recently read of an AI that does the same, but with much more success. Who says AI is a danger?

  2. Now you’re talking. “Transference”

    Thanks for the link.

    People bring their own sentience to the conversation.

    – “When we interact with other people, we always bring a group of ghosts to
    the encounter.”

    That’s my WIP in a nutshell.

    This movie speaks to the same thing.

    THE ARTIFICE GIRL Official Trailer 2 (2023)

    BTW, The Chatbots are about to eat their own tail.

    Model Collapses and UFO Narratives

    But I digress.

  3. Computer Power and Human Reason is a masterpiece. It has informed my thinking on this subject now for over forty years – and nothing has happened yet to falsify Dr. Weizenbaum’s thesis.

  4. As is typical in the world of computing, the problem isn’t the software per se, but the expectations and uses people project onto it. It is no different than how, in the early PC days, people would try to do word processing in LOTUS 1-2-3 and spreadsheeting in WORD PERFECT. They expected too much and got too little.

    There is a lot of handwringing over how “AI” software “hallucinates” answers and some think it is intrinsic to the software:


    …when the reality is the problem is intrinsic to the user.
    All software is useful within its design parameters as long as the inputs are within expected bounds. Go beyond either and you get failure: blue screen of death, lockups, restarts, and yes, nonsense answers. GIGO rules.

    As one of the talking heads quoted in the Fox piece says, people are using narrow focus software for uses beyond its ken. And since people want the black box software to sound human it replies like humans would: by faking it. 😉

    As the saying goes, if all you have is a hammer, everything gets treated like a nail.

    The software is inmensely powerful when used within its “sphere of competence”–sifting data, infering relationships, sophisticated interpolation–and presenting it in an easily “digestible” form for humans. And if you look at how it is being deployed in the corporate world, that is exactly how it is being used: to process limited sets of (internal, proprietary) data for very narrow, specific uses.

    Very different from what the media world thinks.

    “AI” is not about building a magical oracle that can correctly answer any query, do anything. Even Asimov’s MULTIVAC had limits. “AI” software is about building tools that do specific tasks, typically with natural language interfaces. Which means it’ll suffer the same imprecisions and ambiguities of natural language. And software is never good with ambiguity and imprecision. This type of interface is meant for things like parsing an input and assembling an output based on its internal model and the data available to it. If you ask, say Bingchat, to search the internet for a known answer it will find it and present it as best it can. Usually with high reliability if it is a mainstream subject or well documented. Ask it about an obscure subject or when with multiple contradictory answers and it will likely go off the rails. GIGO.

    MULTIVAC knew how to say INSUFICIENT DATA AVAILABLE. Today’s chatbots don’t always know that. It’s early days. Give it time. Just don’t expect too much right away. After all it is created by fallible humans who can’t think of every use and every *misuse* right away.

    Blame the humans, not the tool.

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