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  [83]Artificial Intelligence[84]Topic[85]Type[86]Article

Why People Demanded Privacy to Confide in the World's First Chatbot

In 1966, the Eliza program couldn't say much--but it was enough

  [87]Oscar Schwartz
  18 Nov 2019
  4 min read
  Computer scientist Joseph Weizenbaum with his chatbot Eliza, running on
  an IBM 36-bit IBM 7094 mainframe computer.
  Computer scientist Joseph Weizenbaum with his chatbot Eliza, running on
  a 36-bit IBM 7094 mainframe computer.
  Photo-illustration: Gluekit

  [88]machine learning[89]software[90]history of natural language
  processing[91]NLP[92]natural language
  processing[93]chatbots[94]AI[95]history

  This is part four of a six-part series on the [96]history of natural
  language processing.

  Between 1964 and 1966, [97]Joseph Weizenbaum, a German American
  computer scientist at MIT's [98]artificial intelligence lab, developed
  [99]the first-ever chatbot [PDF].

  While there were already some rudimentary digital language generators
  in existence--programs that could spit out somewhat coherent lines of
  text--Weizenbaum's program was the first designed explicitly for
  interactions with humans. The user could type in some statement or set
  of statements in their normal language, press enter, and receive a
  response from the machine. As Weizenbaum explained, his program made
  "certain kinds of natural-language conversation between man and
  computer possible."

  He named the program [100]Eliza after Eliza Doolittle, the
  working-class hero of George Bernard Shaw's [101]Pygmalion who learns
  how to talk with an upper-class accent. The new Eliza was written for
  the 36-bit [102]IBM 7094, an early transistorized mainframe computer,
  in a programming language that Weizenbaum developed called MAD-SLIP.

  Because computer time was a valuable resource, Eliza could only be run
  via a time-sharing system; the user interacted with the program
  remotely via an electric typewriter and printer. When the user typed in
  a sentence and pressed enter, a message was sent to the mainframe
  computer. Eliza scanned the message for the presence of a keyword and
  used it in a new sentence to form a response that was sent back,
  printed out, and read by the user.

  To encourage ongoing dialogue, Weizenbaum designed Eliza to simulate
  the type of conversational style used by a [103]Rogerian psychoanalyst.
  The program would take something the user said and reflect it back with
  a question, as can be seen in the example below. (Notice how the
  program takes keywords like "boyfriend" and "depressed" and re-uses
  them.)

  Human: Men are all alike.

  Computer: IN WHAT WAY?

  Human: They're always bugging us about something or other.

  Computer: CAN YOU THINK OF A SPECIFIC EXAMPLE?

  Human: Well, my boyfriend made me come here.

  Computer: YOUR BOYFRIEND MADE YOU COME HERE

  Human: He says I'm depressed much of the time.

  Computer: I AM SORRY TO HEAR YOU ARE DEPRESSED

  Human: It's true. I am unhappy.

  Weizenbaum chose this mode of dialogue for Eliza because it gave the
  impression that the computer understood what was being said without
  having to offer anything new to the conversation. It created the
  illusion of comprehension and engagement in a mere 200 lines of code.

  To test Eliza's capacity to engage an interlocutor, Weizenbaum invited
  students and colleagues into his office and let them chat with the
  machine while he looked on. He noticed, with some concern, that during
  their brief interactions with Eliza, many users began forming emotional
  attachments to the algorithm. They would open up to the machine and
  confess problems they were facing in their lives and relationships.
  During their brief interactions with Eliza, many users began forming
  emotional attachments to the algorithm.

  Even more surprising was that this sense of intimacy persisted even
  after Weizenbaum described how the machine worked and explained that it
  didn't really understand anything that was being said. Weizenbaum was
  most troubled when his secretary, who had watched him build the program
  from scratch over many months, insisted that he leave the room so she
  could talk to Eliza in private.

  For Weizenbaum, this experiment with Eliza made him question an idea
  that [104]Alan Turing had proposed in 1950 about machine intelligence.
  In his paper, entitled "[105]Computing Machinery and Intelligence,"
  Turing suggested that if a computer could conduct a convincingly human
  conversation in text, one could assume it was intelligent--an idea that
  became the basis of the famous [106]Turing Test.

  But Eliza demonstrated that convincing communication between a human
  and a machine could take place even if comprehension only flowed from
  one side: The simulation of intelligence, rather than intelligence
  itself, was enough to fool people. Weizenbaum called this the Eliza
  effect, and believed it was a type of "delusional thinking" that
  humanity would collectively suffer from in the digital age. This
  insight was a profound shock for Weizenbaum, and one that came to
  define his intellectual trajectory over the next decade.
  The simulation of intelligence, rather than intelligence itself, was
  enough to fool people.

  In 1976, he published [107]Computing Power and Human Reason: From
  Judgment to Calculation [PDF], which offered a long meditation on why
  people are willing to believe that a simple machine might be able to
  understand their complex human emotions.

  In this book, he argues that the Eliza effect signifies a broader
  pathology afflicting "modern man." In a world conquered by science,
  technology, and capitalism, people had grown accustomed to viewing
  themselves as isolated cogs in a large and uncaring machine. In such a
  diminished social world, Weizenbaum reasoned, people had grown so
  desperate for connection that they put aside their reason and judgment
  in order to believe that a program could care about their problems.

  Weizenbaum spent the rest of his life [108]developing this humanistic
  critique of artificial intelligence and digital technology. His mission
  was to remind people that their machines were not as smart as they were
  often said to be. And that even though it sometimes appeared as though
  they could talk, they were never really listening.

  This is the fourth installment of a six-part series on the [109]history
  of natural language processing. Last week's post described [110]Andrey
  Markov and Claude Shannon's painstaking efforts to create statistical
  models of language for text generation. Come back next Monday for part
  five, which describes the [111]Microsoft's disastrous 2016 experiment
  with a chatbot that learned the subtleties of language from Twitter.

  You can also check out our prior series on the [112]untold history of
  AI.
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  [114]machine learning[115]software[116]history of natural language
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  [122]Oscar Schwartz
  The Conversation (0)

  [123]A woman smiling at the camera while sitting at her desk in front
  of a computer
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