Life on the Screen: Identity in the Age of the Internet | Study Guide

Sherry Turkle

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Life on the Screen: Identity in the Age of the Internet | Part 2, Chapter 5 : Of Dreams and Beasts (The Quality of Emergence) | Summary


Key Takeaways

  • Turkle's goal in this chapter is to define and then to elaborate on the concept of "emergence" in computer culture. She begins by observing that the field of artificial intelligence (AI) is complex. One of the field's founders, the American cognitive scientist Marvin Minsky, is quoted as saying that AI is "trying to get computers to do things that would be considered intelligent if done by people." Once again, the boundaries between humans and machines are called into question. Turkle observes that a pattern of both "disavowal" and "appropriation" may be discerned in the development of AI from the 1960s to the 1980s.
  • An "emergent" model of AI is associated with learning from experience. Turkle argues that emergent AI has recently promoted the idea of "a fundamental kinship between human and machine minds."
  • According to Turkle, early AI researchers were divided into two groups. One group considered intelligence wholly formal and logical. This group believed that detailed rules should be provided to computers. The second group, however, believed that the underlying mathematical structure of machines would allow them to learn from experience. Such "emergent" models, though, were largely brushed off by the end of the 1960s. Later on, they roared back. Turkle places special emphasis on the "Chinese room thought experiment" devised in 1980 by John Searle. Searle asserted that, even though a computer might be able to manipulate the complex characters of the Chinese language, the machine could not really be held to understand Chinese.
  • The rebound of emergent AI was indebted to the development of the "perceptron," a computer program made up of smaller programs called "agents." Turkle offers the analogy of a weather-prediction system made up of a thousand meteorologists of limited ability.
  • The group of emergent AI partisans that most seriously challenged the dominant information-processing approach in the 1980s was known as the "connectionists." These researchers believed in making connections from the bottom up. By the 1990s emergent AI had not only rebounded, but had become the mainstream in AI research. Connectionism suggested that "mystery" and "unpredictability" resided within machines.
  • Connectionism placed a new emphasis on experience as the foundation for learning. It began to present the computer "as though it were an evolving biological organism." Connectionism used a biological template and placed computers within the grand scheme of nature. This approach challenged traditional distinctions between the natural and the artificial.
  • In the 1980s Marvin Minsky, who had long been associated with traditional information-processing approaches, became more sympathetic to emergent AI. In his book, The Society of Mind (1985), Minsky described an emergent system of "agents." Once again, emergent AI had the effect of softening the boundaries between machines and people.
  • Turkle presents illuminating analogies between emergent AI and the structure of ant colonies, the human immune system, the pile-up of cars in a traffic jam, and the motion of a flock of birds. Mitchel Resnick, an American MIT Media Lab researcher, has generalized these patterns using the phrase "the decentralized mindset."
  • Turkle points out a striking parallel between the development of psychoanalysis and that of AI. Both evolved from a centralized to a decentralized model of mind. American psychoanalyst David Olds has stressed this parallel.
  • An important landmark in the "rebirth" of connectionism of emergent AI was the publication in 1986 of a two-volume work titled Parallel Distributed Processing.
  • At the conclusion of this chapter, Turkle notes that some controversial theories, such as those of Sigmund Freud, require a "Trojan horse," by which they can be smuggled into unfriendly terrain. When AI was seen as pure information processing, for example, it was regarded by humanists as objectionable. This attitude has changed now that AI is associated with the language of biology and neurology.
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