Achi news desk-
The Massachusetts Institute of Technology (MIT) Distinguished Collections archive is quiet while a blizzard rages outside. Silence seems to build with the falling snow. I am the only researcher in the archive, but there is a voice that I strain to hear.
I’m looking for someone – let’s call her the missing secretary. She played a crucial role in the history of computing, but has never been named. I’m at MIT as part of my research into the history of talking machines. You may know them as “chatbots” – computer programs and interfaces that use dialogue as the primary form of human-machine interaction. You may have spoken to Alexa, Siri or ChatGPT.
Despite the hype surrounding generative artificial intelligence (AI) today, talking machines have a long history. In 1950, computer pioneer Alan Turing proposed a test of machine intelligence. The test asks if a human could distinguish between a computer and a person through conversation. The Turing test sparked research in AI and the nascent field of computing. We now live in that future he imagined: we talk to machines.
I am interested in why early computer pioneers dreamed of talking to computers, and what was at stake in that idea. What does it mean for the way we understand computer technology and human-machine interaction today? I find myself at MIT, in the middle of this blizzard, because this is the birthplace of the mother of all bots – Eliza.
Eliza’s speech
Eliza was a computer program developed by mustachioed MIT electrical engineering professor Joseph Weizenbaum in the 1960s. Through Eliza, his aim was to make conversation between human and computer possible.
Eliza took messages typed by the user, parsed them for keyword triggers and used transformation rules (where the meaning of a statement can be inferred from one or more other statements) to generate a response. In his most famous version, Eliza claimed to be a psychotherapist, a specialist who responds to the needs of the user. “Tell me your problem” was the opening prompt. Not only could Eliza receive input in the form of natural language, she gave the “illusion of understanding”.
Photo Christoph Keller/Alamy Stock
The name of the program was a nod to the main character of George Bernard Shaw’s play Pygmalion (1912) where a Cockney florist is taught to speak “like a woman”. Like the Audrey Hepburn musical in 1964, this Eliza took the world by storm. Newspapers and magazines were the fruit of Turing’s dream.
Even Playboy played with it. Eliza’s legacy is significant. Siri and Alexa are the direct descendants of this program.
Eliza’s accounts tend to focus on a Frankensteinian story of the inventor rejecting his own creation. Weizenbaum was alarmed that users could be “fooled” by a simple piece of software. He renounced Eliza and all the “Artificial Intelligentsia” in the next decades – to the chagrin of his colleagues.
But I am not in the archive to hear Eliza’s voice, or Weizenbaum’s voice. In all these stories about Eliza, one woman comes up again and again – our missing secretary.
The lost secretary
In his accounts of Eliza, Weizenbaum repeatedly worries about a particular user:
My secretary watched me work on this program over a long period of time. One day he asked permission to speak to the system. Of course, she knew she was talking to a machine. And yet, after I watched her type in a few sentences she turned to me and said: ‘Would you mind leaving the room, please?’
Weizenbaum saw her response as troubling evidence: “Extremely brief exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people.” Her response sowed the seeds for his later distaste for his creation.
But who was this “quite normal” person? And what did she think of Eliza? If the missing secretary played such an important role, then why don’t we hear from her? In this chapter of talking machine history, we only have one side of the conversation.
Back in the archive, I want to see if I can recover the scribe’s voice, to understand what we could learn from Eliza’s user. I’m working my way through Weizenbaum’s yellow papers. Surely there will be evidence among the transcripts, code printouts, letters and notebooks? There are some clues, a reference to a secretary in letters to and from Weizenbaum. But no name.
I expand my hunt to administrative records. I look in the departmental papers and collections of Weizenbaum’s workplace, Project MAC – the hallowed center of computer science innovation at MIT. No luck. I contact the HR office and the MIT alumni group. I extend the patience of the ever generous archivists. As my last day approaches, all I hear is silence.
Listening to silence
But the hunt has revealed some things. So few organizations historically have taken care of the people who produced, organized and saved so much of their knowledge, for one.
In the history of institutions like MIT and computing more generally, the writers of those records—often low-status, low-wage women—are largely written out. Our silent scribe is the nameless, nameless transcriber of the documents on which history is built.
The contributions of talking machine users – their labour, their expertise, their views, their creativity – are all too often overlooked. When the model is “talking”, it’s easy to think those contributions are effortless or insignificant. But downplaying these contributions has real consequences, not only for the talking machine technology we design, but also for the ways we value human input in those systems.
With generative Artificial Intelligence we are talking about user input in terms of “conversation” and “stimuli”. But what kind of legal status can “speak” claim? Should we, for example, be able to claim copyright over those comments? What about the work those systems are trained on? How do we recognize those contributions?
A blizzard is getting worse. The announcement states that the campus closes early due to the weather. The voice of the missing secretary still eludes me. For now, the history of talking machines remains one-sided. It’s a silence that haunts me as I trudge home through the confused, snow-covered streets.
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