Mind over Machine.

In Mind Over Machine (1986), written during the heyday of expert systems, Dreyfus analyzed the difference between human expertise and the programs that claimed to capture it.

This expanded on ideas from What Computers Can’t Do, where he had made a similar argument criticizing the “cognitive simulation” school of AI research practiced by Allen Newell and Herbert A. Simon in the 1960s. Dreyfus argued that human problem solving and expertise depend on our background sense of the context, of what is important and interesting given the situation, rather than on the process of searching through combinations of possibilities to find what we need. Dreyfus would describe it in 1986 as the difference between “knowing-that” and “knowing-how”, based on Heidegger’s distinction of present-at-hand and ready-to-hand. Knowing-that is our conscious, step-by-step problem solving abilities. We use these skills when we encounter a difficult problem that requires us to stop, step back and search through ideas one at time. At moments like this, the ideas become very precise and simple: they become context free symbols, which we manipulate using logic and language. These are the skills that Newell and Simon had demonstrated with both psychological experiments and computer programs. Dreyfus agreed that their programs adequately imitated the skills he calls “knowing-that.” Knowing-how, on the other hand, is the way we deal with things normally. We take actions without using conscious symbolic reasoning at all, as when we recognize a face, drive ourselves to work or find the right thing to say. We seem to simply jump to the appropriate response, without considering any alternatives. This is the essence of expertise, Dreyfus argued: when our intuitions have been trained to the point that we forget the rules and simply “size up the situation” and react. Our sense of the situation is based, Dreyfus argues, on our goals, our bodies and our culture—all of our unconscious intuitions, attitudes and knowledge about the world. This “context” or “background” (related to Heidegger’s Dasein) is a form of knowledge that is not stored in our brains symbolically, but intuitively in some way. It affects what we notice and what we don’t notice, what we expect and what possibilities we don’t consider: we discriminate between what is essential and inessential. The things that are inessential are relegated to our “fringe consciousness” (borrowing a phrase from William James): the millions of things we’re aware of, but we’re not really thinking about right now. Dreyfus claimed that he could see no way that AI programs, as they were implemented in the 70s and 80s, could capture this background or do the kind of fast problem solving that it allows. He argued that our unconscious knowledge could never be captured symbolically. If AI could not find a way to address these issues, then it was doomed to failure, an exercise in “tree climbing with one’s eyes on the moon.” Dreyfus began to formulate his critique in the early 1960s while he was a professor at MIT, then a hotbed of artificial intelligence research. His first publication on the subject is a half-page objection to a talk given by Herbert A. Simon in the spring of 1961. Dreyfus was especially bothered, as a philosopher, that AI researchers seemed to believe they were on the verge of solving many long standing philosophical problems within a few years, using computers. In 1965, Dreyfus was hired (with his brother Stuart Dreyfus’ help) by Paul Armer to spend the summer at RAND Corporation’s Santa Monica facility, where he would write Alchemy and AI, the first salvo of his attack. Armer had thought he was hiring an impartial critic and was surprised when Dreyfus produced a scathing paper intended to demolish the foundations of the field. (Armer stated he was unaware of Dreyfus’ previous publication.) Armer delayed publishing it, but ultimately realized that “just because it came to a conclusion you didn’t like was no reason not to publish it.” It finally came out as RAND Memo and soon became a best seller. The paper flatly ridiculed AI research, comparing it to alchemy: a misguided attempt to change metals to gold based on a theoretical foundation that was no more than mythology and wishful thinking. It ridiculed the grandiose predictions of leading AI researchers, predicting that there were limits beyond which AI would not progress and intimating that those limits would be reached soon.

About the Authors

Stuart Dreyfus,a native of Terre Haute, Indiana, earned a Ph.D. in applied mathematics and is a professor of industrial engineering and operations research at the University of California, Berkeley and Operations Research Department. While at the Rand Corporation he was a programmer of the JOHNNIAC computer. While at Rand he was coauthor, with Richard Bellman, of Applied Dynamic Programming. Following that work, he was encouraged to pursue a Ph.D. which he completed in applied mathematics at Harvard University in 1964, on the calculus of variations. He coauthored Mind Over Machine with his brother Hubert Dreyfus in 1986

Hubert Lederer Dreyfus (born October 15, 1929) is an American philosopher. He is a professor of philosophy at the University of California, Berkeley. His main interests include phenomenology, existentialism and the philosophy of both psychology and literature, as well as the philosophical implications of artificial intelligence. Dreyfus is known for his exegesis of Martin Heidegger, which critics labeled “Dreydegger”. Many of his students have gone to do work on themes related to Heidegger and phenomenology, including Charles Guignon, Mark Wrathall, Sean Kelly, John Haugeland, and John Richardson. Born in Terre Haute, Indiana to Stanley S. and Irene Lederer Dreyfus, Dreyfus was educated at Harvard University, earning three degrees there, with a BA in 1951, an MA in 1952, and a PhD in 1964, under the supervision of Dagfinn Føllesdal. He is considered a leading interpreter of the work of Edmund Husserl, Michel Foucault, and Maurice Merleau-Ponty, but especially of Martin Heidegger. His Being-in-the-World: A Commentary on Heidegger’s “Being and Time,” Division 1, is thought by many who have attempted to teach Heidegger to undergraduates to be the authoritative text on Heidegger’s most significant contribution to philosophy. He also co-authored Michel Foucault: Beyond Structuralism and Hermeneutics, translated Merleau-Ponty’s Sense and Non-Sense, and authored the controversial 1972 book What Computers Can’t Do, revised first in 1979, and then again in 1992 with a new introduction as What Computers Still Can’t Do. While spending most of his teaching career at Berkeley, Professor Dreyfus has also taught at Brandeis University (1957 to 1959), the Massachusetts Institute of Technology (from 1960 to 1968), the University of Frankfurt, and Hamilton College. His philosophical work has influenced Richard Rorty, Charles Taylor, John Searle, and his former student John Haugeland, among others. His critical comments on the existential phenomenology and subsequent dialectical philosophy of Jean-Paul Sartre may well have played a significant role in the demise of Sartre’s influence on recent thought. In 1965, while teaching at Massachusetts Institute of Technology, Dreyfus published “Alchemy and Artificial Intelligence”, an attack on the work of Allen Newell and Herbert A. Simon, two of the leading researchers in the field of Artificial Intelligence. Dreyfus not only questioned the results they had so far obtained, but he also criticized their basic presupposition (that intelligence consists of the manipulation of physical symbols according to formal rules), and argued that the AI research program was doomed to failure. In 1965, he spent time at the Rand Corporation, while work on artificial intelligence was in progress there. In addition to criticizing artificial intelligence, Dreyfus is well known for making the work of continental philosophers, especially Martin Heidegger, Maurice Merleau-Ponty, and Michel Foucault, intelligible to analytically trained philosophers.


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2 respuestas a MoM.

  1. dcruz dijo:

    I think we´ll reach “know-how” in about 20 years. Increasing calculation capacity whit Quantum Computing, it´s almost Sci-Fi jajaja. I don´t understand so well the conflict of the scientists. ¿Why you don´t upload the PDF!!!!!!

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