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Reasoned Use of Expertise in Argumentation
Reasoned Use of Expertise in Argumentation

... guarding against. But does this suggest that all appeals to expert authority in argument are fallacious? It should not. For taking into account the intelligent and informed opinion of a legitimate expert on a question that one needs to act upon may be reasonable in argument, if no better or more dir ...
How We`re Predicting AI—or Failing To
How We`re Predicting AI—or Failing To

... is Thomas Nagel’s “What is it like to be a bat” (Nagel 1974). In this paper, Nagel argues that bats must have mental states, but that we humans can never understand what it is like to have these mental states. This feels purely philosophical, but does lead to empirical predictions: that if the bat’s ...
Reply to Touretzky and Pomerleau
Reply to Touretzky and Pomerleau

... We can begin with snowflakes, and proceed through the whole vast collection of nondenotative patterns exhibited by natural (and artificial) systems: The wind ripples on lakes, the shapes of birds, the masses of clouds, crystals, the grain in wood, a Jackson Pollock painting, the performance of a Moz ...
In Honor of Marvin Minsky`s Contributions on his 80th Birthday
In Honor of Marvin Minsky`s Contributions on his 80th Birthday

... phenomena. We shouldn’t rush to define them. Minsky says “words are designed to keep you from thinking.” (3) If we can’t find an elegant solution to an artificial intelligence problem, we shouldn’t give up. An elegant solution is unlikely given what we know about the brain and the fact that it is a ...
Symbol Grounding and its Implications for Artificial
Symbol Grounding and its Implications for Artificial

... symbols and their categories are grouped into taskspecific sets. Task-specific means that the symbols are formed in order to solve specific problems in particular domains. By having a specific task to perform, a bias is provided for the problem of searching for the best categorisation of sensory dat ...
Meaning in Artificial Agents: The Symbol Grounding Problem
Meaning in Artificial Agents: The Symbol Grounding Problem

... context of the prevailing theories in the cognitive sciences at the time, namely the symbolic model of the mind, which holds that ‘‘the mind is a symbol system and cognition is symbol manipulation’’ (Harnad 1999). Strictly speaking, the SGP can be seen as the problem of endowing Artificial Agents wi ...
Reconstructing  Physical Symbol Systems
Reconstructing Physical Symbol Systems

... Why should the shapes of symbols be arbitrary? So that symbols can designate anything at all: A symbol may be used to designate any expression whatsoever. That is, given a symbol, it is not precribed a priori what expressions it can designate. This arbitrariness pertains only to symbols; the symbol ...
(1927–2016) Scientist and inventor was a visionary founder of AI
(1927–2016) Scientist and inventor was a visionary founder of AI

... synergistically bringing together Minsky’s computational ideas with Papert’s understanding of developmental psychology to develop theories of intelligence and radical approaches to early education. In the mid 1970s, Minsky introduced Frames, a way of representing entities and situations as sets of s ...
Reconstructing Physical Symbol Systems
Reconstructing Physical Symbol Systems

... as symbolic. In describing Brooks’ creatures, they say that “sensory information is converted to symbols, which are then processed and evaluated in order to determine the appropriate motor symbols that lead to behavior” (p. 34). Yet elsewhere they confer symbolic status on retinal images themselves, ...
The errors, insights and lessons of famous AI predictions
The errors, insights and lessons of famous AI predictions

... predictions are all over the map, with no pattern of convergence, and no visible difference between expert and non-expert predictions. These results were detailed in a previous paper [AS12], and are summarised here. The key part of the paper is a series of case studies on five of the most famous AI ...
Why Heideggerian AI Failed and how Fixing it would Require
Why Heideggerian AI Failed and how Fixing it would Require

... understand intelligence. We in the AI Lab. have taken over and are succeeding where you philosophers have failed. We are now programming computers to exhibit human intelligence: to solve problems, to understand natural language, to perceive, and to learn.”1 In 1968 Marvin Minsky, head of the AI lab, ...
Artificial intelligence
Artificial intelligence

... "A physical symbol system has the necessary and sufficient means of general intelligent action." This statement claims that the essence of intelligence is symbol manipulation.[45] Hubert Dreyfus argued that, on the contrary, human expertise depends on unconscious instinct rather than conscious symbo ...
ttay8_ppt_15b
ttay8_ppt_15b

... a 1950 paper called “Computing Machinery and Intelligence.” In 1952 he was professionally and socially devastated when he was arrested and injected with hormones for violation of British antihomosexuality laws. The 41-year-old genius apparently committed suicide in 1954, years before the government ...
Expert Systems - Department of Computer Science
Expert Systems - Department of Computer Science

... Dreyfus: points out ways in which AI theorists have overclaimed about what they can do. e.g. Feigenbaum claims that ‘DENDRAL has been in use for many years at university and industrial chemical labs around the world’. But ‘..when we called several university and industrial sites that do mass spectro ...
NETWORK   AESTHETICS Warren Sack Abstract Film & Digital Media Department
NETWORK AESTHETICS Warren Sack Abstract Film & Digital Media Department

... A. Common sense is knowing maybe 30 or 50 million things about the world and having them represented so that when something happens, you can make analogies with others. If you have common sense, you don't classify the things literally; you store them by what they are useful for or what they remind u ...
Network Aesthetics - social computing lab
Network Aesthetics - social computing lab

... A. Common sense is knowing maybe 30 or 50 million things about the world and having them represented so that when something happens, you can make analogies with others. If you have common sense, you don't classify the things literally; you store them by what they are useful for or what they remind u ...
Future Progress in Artificial Intelligence: A Survey of
Future Progress in Artificial Intelligence: A Survey of

... intelligence’ (HLMI) as one that can carry out most human professions at least as well as a typical human.” (We still had one expert writing back to us that they could not say what a ‘typical human’ is – though they could be convinced to respond, after all.) In hindsight, it may have been preferable ...
Papert (1988)
Papert (1988)

... -6is hardly viable as a cognitive architecture. No rule-based system has survived more than a few thousand rules, and the problems of maintaining such large rule-bases are unsolved. And qualitative reasoning in the domain of naive physics, which seems to have dominated much of the mainstream public ...
TOK essay preparation (Steve Reynolds 2011) - DPC
TOK essay preparation (Steve Reynolds 2011) - DPC

... intelligence’ (e.g. empathy)? How can we ever know if AI feels unless we are also AI? Claim: Newell & Simon’s, ‘Physical symbol system hypothesis’ states that all knowledge exists through symbols and therefore AI has sufficiency to ‘know’. Counter claim: Dreyfus argues humans depend on unconscious i ...
Jurek Gryz The frame problem in artificial intelligence and
Jurek Gryz The frame problem in artificial intelligence and

... any one time as many as 30 people were simultaneously entering data. They analyzed newspaper articles, encyclopedia entries, advertisements, etc. sentence by sentence. The idea was not to create yet another encyclopedia, but to encode the knowledge anyone needs to have before he can understand an en ...
Is it possible to create a computer that mimics human
Is it possible to create a computer that mimics human

... impulses define specific behaviors of the nervous system (Von Neumann 70). Likewise, computer programmers input rules as sequences of computer codes to make the machine respond to different activities. Many neuroscientists believe that the brain depends on “neural codes”, or algorithms, to transform ...
Dialogue systems: simulations or interfaces?
Dialogue systems: simulations or interfaces?

... based on formal representations is questionable – Instead, formal dialogue research can be regarded as the creation of systematic domains that can be used in the engineering of flexible human-computer ...
Solving Mathematical Puzzles: a Deep Reasoning Challenge
Solving Mathematical Puzzles: a Deep Reasoning Challenge

... driven. The fact that a bank teller is confused, the name of Ms Smith and the newspaper bought do not help the solution process and should be discarded. The fact that we are talking about the two inhabitants, Jacob and Frank, does not play any important role in the problem solving activity. They cou ...
Artificial Human Nature Warren Sack
Artificial Human Nature Warren Sack

... about the same subject. For example, the philosophy of rationalism has been cited in critiques of “reasoning” in AI, phenomenology in critiques of AI’s conceptions of “perception” and “the body,” and romanticism has been named in defense of “human emotion” over machines’ supposed inability to experi ...
A Symbol Is Not A Symbol
A Symbol Is Not A Symbol

... two interrelated questions emerge: What would a cognitive theory that could accomodate these seemingly contradictory positions look like, and what could such a theory say — or at least indicate — about what computers can do? My aim with the present paper is to show how the two positions of 'mainstre ...
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Hubert Dreyfus's views on artificial intelligence

Hubert Dreyfus has been a critic of artificial intelligence research since the 1960s. In a series of papers and books, including Alchemy and AI (1965), What Computers Can't Do (1972; 1979; 1992) and Mind over Machine (1986), he presented a pessimistic assessment of AI's progress and a critique of the philosophical foundations of the field. Dreyfus' objections are discussed in most introductions to the philosophy of artificial intelligence, including Russell & Norvig (2003), the standard AI textbook, and in Fearn (2007), a survey of contemporary philosophy.Dreyfus argued that human intelligence and expertise depend primarily on unconscious instincts rather than conscious symbolic manipulation, and that these unconscious skills could never be captured in formal rules. His critique was based on the insights of modern continental philosophers such as Merleau-Ponty and Heidegger, and was directed at the first wave of AI research which used high level formal symbols to represent reality and tried to reduce intelligence to symbol manipulation.When Dreyfus' ideas were first introduced in the mid-1960s, they were met with ridicule and outright hostility. By the 1980s, however, many of his perspectives were rediscovered by researchers working in robotics and the new field of connectionism—approaches now called ""sub-symbolic"" because they eschew early AI research's emphasis on high level symbols. Historian and AI researcher Daniel Crevier writes: ""time has proven the accuracy and perceptiveness of some of Dreyfus's comments."" Dreyfus said in 2007 ""I figure I won and it's over—they've given up.""
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