The first chatbot was a joke. Only the oligarchs are laughing now

Read the original at The Sydney Morning Herald ↗
The Sydney Morning Herald · collected 2026-09-17 · by Tom Holloway

Quick Summary

The article discusses Joseph Weizenbaum, who developed Eliza, the world’s first chatbot, in the mid-1960s while working at MIT's Project MAC. Despite creating Eliza as a joke to highlight the limitations of AI, it was celebrated by therapists and even used privately by his secretary. The unintended success of Eliza led Weizenbaum to face the realization that government agencies like the Pentagon were major funders of his work, leading him into disillusionment about AI's implications.
Written locally by qwen2.5:14b on 2026-09-17, using this article's own text rather than the other coverage of the same event (that is the story summary below).

AI analysis runs on qwen2.5:14b, locally

Story summary

In the mid-1960s, Joseph Weizenbaum, a researcher at the Massachusetts Institute of Technology (MIT) on a temporary contract for Project MAC, created the world’s first chatbot named Eliza. This pioneering project aimed to make computers more accessible but was also meant as a critique of artificial intelligence. Eliza mimicked basic conversational skills by recognizing certain keywords like “mother” or “father,” and could switch "I's" to "you's." However, when it couldn't understand input sentences, Eliza employed vague responses typical of Rogerian psychotherapy, such as asking patients to elaborate. Weizenbaum developed Eliza not just to demonstrate the capabilities of early AI but also to highlight its limitations and ethical concerns surrounding machine-human interactions.

Written for “Chatbot Oligarch Laughter” on 2026-09-18, grounded in this article and the 0 other(s) covering the same event.
Why this leaning score
The article's own words the score was based on. Each is quoted verbatim and was checked against the article text before being stored, so you can find it in the original.
Score -0.35 Confidence medium
Leaning score -0.35 for article 16827 (medium confidence, 2 verified quotes) · logged 2026-09-17

Signals How these are calculated →

Claims extracted
49
claim-shaped sentences
Uncertain
18%
9 of 49 hedged
Leaning
Leans left
of the writing, not the subject
Correction & hedging signals
96.6
corrections and hedging in what we collected; not a measure of accuracy
Outlets on this story
1
Technology
Narrative spread
1
articles carrying this framing
Analyzed 2026-09-17 · how these are computed

Story

📰 Chatbot Oligarch Laughter
Technology · 1 article(s) covering the same event.

How this is being covered How these are calculated →

Article leaning vs. publisher reliability
Source leaning vs. consistency

Compared with similar articles

This article reads leans left and hedges 18% of its claims. Each row says how that neighbour differs.
NBC News
⚖️ leaning not scored 🔴 21% hedged 5 of 24 📰 publisher trust 95
“Article A discusses a public agreement by AI CEOs to slow AI development, while Article B is a historical piece about the creation of the first chatbot.”
September 13, 2026 different event · 98%
Letters from an American
⚖️ Leans left 🔴 15% hedged 10 of 65
“Article A describes a specific essay published on September 12 by Dario Amodei, while Article B discusses the history of the first chatbot developed by Joseph Weizenbaum in the mid-1960s.”
Fox News
⚖️ Leans strongly right further right than this 🔴 11% hedged 4 of 38 📰 publisher trust 95
“The articles discuss different topics related to AI but do not describe the same specific incident.”
New York Post
⚖️ Leans left 🔴 9% hedged 4 of 43 📰 publisher trust 59
“The articles discuss different aspects of AI chatbots without referring to the same specific incident.”
New York Post
⚖️ leaning not scored 🔴 28% hedged 7 of 25 📰 publisher trust 59
“The articles discuss different topics related to AI but describe distinct events and timeframes.”
Artificial audacity different event · 90%
Dawn
⚖️ leaning not scored 🔴 19% hedged 5 of 27 📰 publisher trust 95
“The articles discuss different topics related to AI, with Article A focusing on a statement by Donald Trump regarding AI regulation and Article B discussing historical context about the first chatbot.”
NPR
⚖️ leaning not scored 🔴 18% hedged 10 of 57 📰 publisher trust 60
“The articles discuss different topics: one focuses on ChatGPT's crisis feature and suicide prevention, while the other is about the history of the first chatbot.”

Publisher

The Sydney Morning Herald · 402 article(s) · 0 correction(s) detected
No corrections detected for this publisher. That may mean careful reporting, or simply that nothing has been checked.

Who wrote this

Tom Holloway
1 article(s) here · 1 carrying a prediction
🔮 Eliza could recognise words such as “mother” or “father”, change “I’s” to “you’s” and very, very basically, ask input sentences back as questions.
The only article under this byline in the corpus.

Topics

American Germany Nazi Project MAC the Massachusetts Institute of Technology

Subjects

Weizenbaum PERSON · 9× Eliza PERSON · 4× MIT ORG · 3× Jewish NORP · 2× Carl Rogers PERSON · 1× Eliza Doolittle PERSON · 1× George Bernard Shaw’s PERSON · 1× Joseph Weizenbaum PERSON · 1× Project MAC ORG · 1× the Massachusetts Institute of Technology ORG · 1×

Narrative

I went to Weizenbaum, his secretary and their invention, and it was all there: all the contemporary worries about people falling in love with chatbots, about privacy, about environmental damage and, perhaps worst of all, all the legitimate fear about who is behind it and what their intentions are.
framing: assertive · carried by 1 article(s) · first seen 2026-09-17
🔮 Eliza could recognise words such as “mother” or “father”, change “I’s” to “you’s” and very, very basically, ask input sentences back as questions.
2026-09-17 · The Sydney Morning Herald
The first chatbot was a joke. Only the oligarchs are laughing now · assertive framing

Claims (49 extracted, 9 hedged)

I don’t know when I first heard the story of Joseph Weizenbaum, but it was a long time before our screens and news and thoughts and dreams and nightmares were so full of artificial intelligence. asserted
screens → know → intelligence
He was on a temporary contract at the Massachusetts Institute of Technology in the mid-1960s, working for Project MAC, which had the aim of making computers more widely accessible. asserted
computers → work → aim
Seemingly to help achieve this aim, Weizenbaum developed the world’s first chatbot, on a computer the size of a room, that heated an entire building, and had just 150 kilobytes of memory. asserted
that → help → memory
Named after Eliza Doolittle from George Bernard Shaw’s Pygmalion, Weizenbaum’s creation was a play on Rogerian psychotherapy, a non-directive type of talk therapy created by Carl Rogers in the 1940s. asserted
creation → name → 1940s
Eliza could recognise words such as “mother” or “father”, change “I’s” to “you’s” and very, very basically, ask input sentences back as questions. uncertain
you → recognise → questions
If it couldn’t compute how to do this, it would use the disguise of Rogerian therapy to say things like, “please go on” or “I’m not sure I understand you fully.” asserted
I → compute → you
Weizenbaum actually had ulterior motives. asserted
Weizenbaum → have → motives
He was already sceptical of the concept of AI, and saw Eliza as the chance to remind the world how farcical the concept of intelligent machines was. asserted
concept → see → machines
He wrote a paper about the program, publishing sections of its basic code, to say, “Look! This is so simple and yet it can appear intelligent!” asserted
it → write → code
Because, for him, appearance was as close as a computer could ever get to human intelligence. uncertain
computer → get → intelligence
He was sure his paper and this apparent joke would show the world how right he was. asserted
he → show → world
But the world didn’t take it the way he intended. asserted
he → take → it
Eliza was celebrated. asserted
Eliza → celebrate → ?
Prominent voices in the American therapeutic world thought it could be rolled out across the country to help with the therapy shortage. uncertain
it → think → shortage
Then he discovered his own staff, the people who had helped create it, were sneaking in and using it without his knowledge and refusing to hand over their transcripts, calling them “private” conversations between “me and her”. asserted
who → discover → me
Most famously of all, his secretary asked him to leave the room when she was “talking to Eliza”. asserted
she → ask → Eliza
It has even come out that, in the very same building, under a disguise, was a government agency that also claimed the word “intelligence”; Weizenbaum, who had fled a growing Nazi Germany in 1936, was eventually forced to confront the fact the Pentagon was a major funder of his work. asserted
Pentagon → come → work
His invention (or joke) had been received in exactly the opposite way he had intended. asserted
he → receive → way
He received tenure at MIT on the back of this misunderstanding and nothing he could do seemed to sway people’s views of his creation. uncertain
he → receive → creation
I guess that’s the risk you take when you create and put something out into the world. asserted
you → guess → world
So, as the world was heating up over AI, and I wondered how I could creatively respond to all this, the first thought I had was to look back in order to understand something that seems to be so much about the future. uncertain
that → heat → future
I went to Weizenbaum, his secretary and their invention, and it was all there: all the contemporary worries about people falling in love with chatbots, about privacy, about environmental damage and, perhaps worst of all, all the legitimate fear about who is behind it and what their intentions are. asserted
intentions → go → it
My play is set in 1966, as Weizenbaum releases his creation and finds himself in a maelstrom of delusion. asserted
Weizenbaum → set → delusion
To write it, I did something very un-AI: I talked to people. asserted
I → write → people
I talked to Jewish consultants about the early post-World War II Jewish experience, to computer engineers at MIT during the ’60s, to the people who rediscovered Weizenbaum’s files he had hidden in the MIT archives. asserted
he → talk → archives
I talked to friends and family and anyone and everyone to hear about their dreams and fears for this technology. asserted
I → talk → technology
I also talked to a friend and collaborator of Weizenbaum about the mythical secretary who was never named, and then I got to share this name with an academic researching the lost women of computing history. asserted
I → talk → history
Wonderfully, the academic and the secretary shared a name: Becky! asserted
academic → share → name
I also talked to Eliza; the program is freely available online thanks to members of the team who rediscovered the story. asserted
who → talk → story
I even talked to ChatGPT and Claude and any other sentence-generating software to see how they would respond to prompts about Eliza and Weizenbaum. asserted
they → talk → Eliza
One of them tried to set the whole play in a jazz bar, with Weizenbaum wearing a beret. asserted
Weizenbaum → try → beret
What are we, as creatives, meant to think about this software? asserted
we → mean → software
Is it just the latest in the long line of technology that has disrupted and brought fear to the arts, only to be used to create new, incredible work? asserted
that → disrupt → work
Is it Baudelaire against the camera, or Bob Dylan coming out with an electric guitar? asserted
Dylan → come → guitar
They steal our IP, churn through our water, tear apart our privacy, line their pockets in ways the Rockefellers could never have dreamed of, and threaten the structures of democracy. uncertain
Rockefellers → steal → democracy
As a citizen, all this enrages me. asserted
this → enrage → me
I dream of setting fire to military contracts, pumping polluted water into data centres and toppling space rockets as if they were statues of dictators. asserted
they → dream → dictators
How dare these tech feudalist elites think they can steal everything we have ever created and earn a country’s GDP from the theft! asserted
we → think → theft
But there are rumblings of a different way: voices as diverse as Bernie Sanders and Steve Bannon have called for at least partial nationalisation. asserted
voices → be → nationalisation
Cory Doctorow, coiner of the glorious term “enshittification” – an idea no AI could ever come up with – believes that when the financial bubble finally bursts, the hardware behind these models could be bought for pennies in the dollar and whatever is created from it can become open-sourced, as I believe it should have been in the first place. uncertain
it → come → place
…and 9 more, not listed.
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