Difference between revisions of "Knowledge"

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==Full Title or Meme==
 
==Full Title or Meme==
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Facts, information, and skills acquired by a person through experience and education; the theoretical or practical understanding of a subject.
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Facts, information, and skills acquired by a person through experience and education; the theoretical or practical [[Understanding]] of a subject.
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the ladder from knowledge to wisdom.
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* [[Data Category|Data]] → raw facts, unprocessed.
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* [[Information]] → data organized into patterns.
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* [[Knowledge]] → information understood and applied.
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* [[Wisdom]] → knowledge tempered by judgment, ethics, and lived perspective.
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This is sometimes called the DIKW hierarchy (Data–Information–Knowledge–Wisdom). But it’s not a simple progression — each step after the first exhibits a [[Dialectic Harmony]]. Each step contains tensions that must be resolved to move upward.
  
 
==Context==
 
==Context==
 
A significant number of philosophers have convinced themselves that there is no way that a computer could ever be said to have human [[Knowledge]] of any subject.
 
A significant number of philosophers have convinced themselves that there is no way that a computer could ever be said to have human [[Knowledge]] of any subject.
  
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*Searle: The '''Chinese room argument''' holds that a program is no different from a room full of Chinese scholars who cannot understand English, but can translate it to English using rules in books, and so cannot give a computer a "[[mind]]", "[[intentionality|understanding]]" or "[[consciousness]]" regardless of how intelligently or human-like the program may make the computer behave.<ref>John Searle, "Minds, Brains, and Programs", (1980) Behavioral and Brain Sciences </ref>  Searle argues that, without "understanding" (or "[[intentionality]]"), we cannot describe what the machine is doing as "thinking" and, since it does not think, it does not have a "mind" in anything like the normal sense of the word. Therefore, he concludes that "strong AI" is false. Most of the discussion consists of attempts to refute it. The sheer volume of the literature that has grown up around it inspired [[Patrick J. Hayes|Pat Hayes]] to comment that the field of [[cognitive science]] ought to be redefined as "the ongoing research program of showing Searle's Chinese Room Argument to be false".Searle's argument has become "something of a classic in cognitive science,". Varol Akman agrees, and has described the original paper as "an exemplar of philosophical clarity and purity".<ref>In [[Varol Akman|Akman]]'s [http://www.google.com/search?client=safari&rls=en&q=cogprints.org/539/0/md2.ps&ie=UTF-8&oe=UTF-8 review of ''Mind Design II'']</ref> But all liturature boils down to a silly veralism, an argument about the meaning of words, which is why this wiki seeks to define the words that it depends on. In this wiki words mean exactly what we want them to mean, no more and no less.
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*Alan Turing: The "standard interpretation" of the [[Turing Test]], in which player C, the interrogator, is given the task of trying to determine which of two players: A or B on the other end of teletypewriter links is a computer and which is a human. The interrogator is limited to using the responses to typed in questions to make the determination. The Turing test which was introduced in 1950 to help answer the question "can machines think?" In the standard version, a human judge engages in a natural language conversation with a human and a machine designed to generate performance indistinguishable from that of a human being. All participants are separated from one another. If the judge cannot reliably tell the machine from the human, the machine is said to have passed the test. Turing then considered each possible objection to the proposal "machines can think", and found that there are simple, obvious answers if the question is de-mystified in this way. He did not, however, intend for the test to measure for the presence of "[[Consciousness]]" or "understanding". He did not believe this was relevant to the issues that he was addressing. He wrote: "I do not wish to give the impression that I think there is no mystery about consciousness. There is, for instance, something of a paradox connected with any attempt to localise it. But I do not think these mysteries necessarily need to be solved before we can answer the question with which we are concerned in this paper." Turing anticipated Searle's Chinese room argument (which he called "The Argument from Consciousness") in 1950 by noting that people never consider the problem of other minds when dealing with each other. He writes that "instead of arguing continually over this point it is usual to have the polite convention that everyone thinks." The [[Turing Test]] simply extends this "polite convention" to machines.
  
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===Consciousness===
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*Newell and Simon had conjectured that a physical symbol system (such as a digital computer) had all the necessary machinery for "general intelligent action", or, as it is known today, [[Artificial Intelligence|artificial general intelligence]]. They framed this as a philosophical position, the hypothesis: "A physical symbol system has the necessary and sufficient means for general intelligent action." The Chinese room argument does not refute this, because it is framed in terms of "intelligent action", i.e. the external behavior of the machine, rather than the presence or absence of understanding, consciousness and mind.
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Searle's original presentation emphasized "understanding"—that is, mental states with what philosophers call "[[intentionality]]"—and did not directly address other closely related ideas such as "consciousness". However, in more recent presentations Searle has included consciousness as the real target of the argument.{{sfn|Searle|1992|p=44}}
 
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{{quote|Computational models of consciousness are not sufficient by themselves for consciousness. The computational model for consciousness stands to consciousness in the same way the computational model of anything stands to the domain being modelled. Nobody supposes that the computational model of rainstorms in London will leave us all wet. But they make the mistake of supposing that the computational model of consciousness is somehow conscious. It is the same mistake in both cases.{{sfn|Searle|2002}}|John R. Searle| Consciousness and Language, p. 16}}
 
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[[David Chalmers]] writes "it is fairly clear that consciousness is at the root of the matter" of the Chinese room.{{sfn|Chalmers|1996|p=322}}
 
  
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[[Colin McGinn]] argues that the Chinese room provides strong evidence that the [[hard problem of consciousness]] is fundamentally insoluble. The argument, to be clear, is not about whether a machine can be conscious, but about whether it (or anything else for that matter) can be shown to be conscious. It is plain that any other method of probing the occupant of a Chinese room has the same difficulties in principle as exchanging questions and answers in Chinese. It is simply not possible to divine whether a conscious agency or some clever simulation inhabits the room.{{sfn|McGinn|2000}}
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*Haldane: was skeptical of Materialist views and said in 1932: "If my options are the result of chemical processes going on in my brain, they are determined by the laws of chemistry, not the laws of logic".<ref>J.B.S Haldane, ''Some Consequences of Materialism'' in ''The Inequality of Man.'' PENGUIN (PELICAN) (1932)</ref>
  
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Searle argues that this is only true for an observer ''outside'' of the room. The whole point of the thought experiment is to put someone ''inside'' the room, where they can directly observe the operations of consciousness. Searle claims that from his vantage point within the room there is nothing he can see that could imaginably give rise to consciousness, other than himself, and clearly he does not have a mind that can speak Chinese.
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*Searle: The '''Chinese room argument''' implements a version of the [[Turing Test]] where a program in the computer is held to be no different from a room full of Chinese scholars who cannot understand English, but can translate English to Chinese using rules in books and cards. Searle asserts that this [[Symbol Manipulation]] cannot result in a computer having a "mind", "[[intentionality|understanding]]" or "consciousness" regardless of how intelligently or human-like the program may make the computer behave.<ref>John Searle, "Minds, Brains, and Programs", (1980) Behavioral and Brain Sciences </ref>  Searle argues that, without "understanding" (or "[[intentionality]]"), we cannot describe what the machine is doing as "thinking" and, since it does not think, it does not have a "mind" in anything like the normal sense of the word. Therefore, he concludes that "strong AI" is false. Most of the commentary about [[Knowledge]] seems to be an attempt to refute Searle's argument, which has become "something of a classic in cognitive science,". Varol Akman agrees, and has described the original paper as "an exemplar of philosophical clarity and purity".<ref>Varol Akman review of ''Mind Design II'' http://www.google.com/search?client=safari&rls=en&q=cogprints.org/539/0/md2.ps&ie=UTF-8&oe=UTF-8 </ref>. To any of other suggestions, Searle's response is always the same: no matter how much [[Knowledge]] is written into the program and no matter how the program is connected to the world, he is still in the room manipulating symbols according to rules. His actions are [[syntax|syntactic]] and this can never explain to him what the symbols stand for. Searle writes "syntax is insufficient for semantics." The Chinese room is designed to show that the [[Turing Test]] is insufficient to detect the presence of consciousness, even if the room can behave or function as a conscious mind would.
  
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===Applied Ethics===
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*Dennett looks at all of [[Artificial Intelligence]], and most particularly Deep Learning as "parasitic: deep learning (so far) discriminates but doesn't notice, That is the flood of data a system takes in does not have relevance for the system except a more 'food' to 'digest'" and further that "deep-learning machines are dependent on human understanding."<ref> Daniel C. Dennett, ''From Bacteria to Bach and Back: The Evolution of Minds.'' (2017-02-17) ISBN 978-0393242072</ref> He seems to be unaware of the symbiotic relationship between humans and Wikipedia or the possibility of interaction between humans and [[Identity Management]] systems as further explicated on the page [[Bayesian Identity Proofing]]. But most damning of Dennett, and in fact all of these philosophers, is that they think of human [[Knowledge]] as a high point to be reached for and emulated, rather than as the distillation of the rantings and ravings of a self-absorbed bunch of apes.
  
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[[File:USS Vincennes (CG-49) Aegis large screen displays.jpg|thumb|right|Sitting in the [[Operations room|Combat Information Center]] aboard [[USS Vincennes (CG-49)|a warship]] - proposed as a real-life analog to the Chinese Room]]
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But all this discussion by philosophers boils down to a silly verbalism, an argument about the meaning of words, which is why this wiki seeks to define the words that are used here. In this wiki words mean exactly what we want them to mean, no more and no less. Or, in other words, we chose words and their definitions as is demanded by Popper<ref>Karl Popper ''The Open Society and Its Enemies'' (original 1945) Routledge ISBN 978-0415610216</ref>.
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Patrick Hew used the Chinese Room argument to deduce requirements from military [[command and control]] systems if they are to preserve a commander's [[moral agency]]. He drew an analogy between a commander in their [[Operations room|command center]] and the person in the Chinese Room, and analyzed it under a reading of [[Nicomachean Ethics|Aristotle’s notions of 'compulsory' and 'ignorance']]. Information could be 'down converted' from meaning to symbols, and manipulated symbolically, but moral agency could be undermined if there was inadequate 'up conversion' into meaning. Hew cited examples from the [[Iran Air Flight 655|USS ''Vincennes'' incident]].<ref>{{cite journal|last1=Hew|first1=Patrick Chisan|title=Preserving a combat commander’s moral agency: The Vincennes Incident as a Chinese Room|journal=Ethics and Information Technology|date=September 2016|volume=18|issue=3|pages=227–235|doi=10.1007/s10676-016-9408-y}}</ref>
 
  
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===Strong AI vs. AI research===
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==Problem==
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Searle's arguments are not usually considered an issue for AI research. [[Stuart J. Russell|Stuart Russell]] and [[Peter Norvig]] observe that most AI researchers "don't care about the strong AI hypothesis—as long as the program works, they don't care whether you call it a simulation of intelligence or real intelligence."{{sfn|Russell|Norvig|2003|p=947}} The primary mission of [[artificial intelligence]] research is only to create useful systems that ''act'' intelligently, and it does not matter if the intelligence is "merely" a simulation.
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*As the process of collecting a [[User]]'s [[Identifier]]s, [[Attribute]]s etc. (aka [[Claim]]s) from a [[Distributed Identity]] hosted across the cloud in unrelated databases and block-chains, the challenge of turning this data into an [[Authorization]] decision becomes quite complex. This is a problem that once was decided by the [[Knowledge]] of an expert and the [[Understanding]] of the context, for example large bank loans needed to be approved by a vice president and large corporate checks need to be signed by the comptroller of the company.
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*Human [[Knowledge]] is, after all, "Human, all to Human"<ref>Friedrich Nietzsche, ''Human, All Too Human''. (original 1878) ISBN 9780140446173</ref>. Which means it cannot escape the limitations and prejudices of actual people going about their daily business.
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===Writing===
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A famous myth recounted in Plato’s Phaedrus is one of the earliest critiques of technological mediation: Thoth presented writing to King Thamus, who questioned its value. Thamus argued that writing would lead to forgetfulness, as people would rely on written records instead of their memory. This story highlights the dual nature of writing as both a tool for knowledge and a potential crutch for memory.  
  
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Searle does not disagree that AI research can create machines that are capable of highly intelligent behavior. The Chinese room argument leaves open the possibility that a digital machine could be built that ''acts'' more intelligently than a person, but does not have a [[mind]] or [[intentionality]] in the same way that [[Human brain|brains]] do. Indeed, Searle writes that "the Chinese room argument ... assumes complete success on the part of artificial intelligence in simulating human cognition."{{sfn|Searle|2004|p=63}}
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Conclusion:
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<!-- Going to add this when I get sources; out of time today
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Thoth's legacy as the inventor of writing has had a lasting impact on human communication and record-keeping, making him a central figure in the history of literacy and knowledge in ancient Egypt.
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Marvin Minsky goes so far as to say that the argument "should be ignored",{{Minsky|WHAT}} and [[Alan Turing]] writes (on the general subject of "consciousness") yadda yadda. -->
 
  
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Searle's "strong AI" should not be confused with "[[artificial general intelligence|strong AI]]" as defined by [[Ray Kurzweil]] and other futurists,{{sfn|Kurzweil|2005|p=260}} who use the term to describe machine intelligence that rivals or exceeds human intelligence. Kurzweil is concerned primarily with the ''amount'' of intelligence displayed by the machine, whereas Searle's argument sets no limit on this. Searle argues that even a super-intelligent machine would not necessarily have a mind and consciousness.
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==Solution==
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<!-- Going to add this as well.
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[[Knowledge]] comes in two forms (which are not completely distinct):
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There are a few researchers{{Who|date=February 2012}} who argue that (contrary to Russell, Norvig, Turing and Minsky) consciousness would be required by a machine to pass the Turing test.{{Citation needed|date=February 2012}}-->
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#Active knowledge that is accessible to a [[Mind]] in a form that can be (nearly) immediately accessed and used.
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#Passive knowledge that is coded in some form that can be absorbed by a [[Mind]] and (hopefully) turned into active knowledge. (This process is also called learning.)
  
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===Turing test===
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Arthur Shopenhauer described the two forms of knowledge thus:<ref>Arthur Shopenhauer, Essays and Aphorisms. trans. R.J. Holllingdale, (1970) Penguin p. 89 ISBN 978-0140442274 </ref>
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{{main article|Turing test}}
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<blockquote>As the biggest library, if it is in disorder, is not as useful as a small but well-arranged one; so you may accumulate a vast amount of knowledge but it will be of far less value than a much smaller amount if you have not thought it over for yourself, because only through ordering what you know by comparing every truth with every other truth can you take complete possession of your knowledge and get it into your power. You can think about only what you know, so you ought to learn something, on the other hand, you can know only what you have thought about.</blockquote>
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[[File:Turing Test version 3.png|thumb|The "standard interpretation" of the Turing Test, in which player C, the interrogator, is given the task of trying to determine which player – A or B – is a computer and which is a human. The interrogator is limited to using the responses to written questions to make the determination. Image adapted from Saygin, 2000.{{sfn|Saygin|2000}}]]
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===Knowledge in Identity Management===
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The Chinese room implements a version of the [[Turing test]].{{sfn|Turing|1950}} [[Alan Turing]] introduced the test in 1950 to help answer the question "can machines think?" In the standard version, a human judge engages in a natural language conversation with a human and a machine designed to generate performance indistinguishable from that of a human being. All participants are separated from one another. If the judge cannot reliably tell the machine from the human, the machine is said to have passed the test.
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The working solution for [[Authentication]] and [[Authorization]] can be viewed as an extension of an existing process in ecommerce where the [[Relying Party]] collects the claims about the user and the context of the request (which will likely include user behavior and value of the transaction) into a [[Trust Vector]] for processing by a [[Fraud Detection]] Service. The result will be used to make the [[Authorization]] decision, or (if insufficient) it might initiate a continued collection of user claims for a retry.
  
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Turing then considered each possible objection to the proposal "machines can think", and found that there are simple, obvious answers if the question is de-mystified in this way. He did not, however, intend for the test to measure for the presence of "consciousness" or "understanding". He did not believe this was relevant to the issues that he was addressing. He wrote:
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In other words, with a [[Distributed Identity]] system, the [[Relying Party]] needs to be self-aware to the extent that it can determine what [[Knowledge]] it has about a [[User]] so that if that knowledge is insufficient to [[Authorization|Authorize]] access, that the [[Relying Party]] has [[Knowledge]] to seek out the additional claims it needs to grant access. The current state-of-the-art is for [[Understanding]] of the context to be built into the algorithm that collects context, but that is starting to change with the inclusion of [[Artificial Intelligence]] into the [[Fraud Detection]] systems.
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{{quote|I do not wish to give the impression that I think there is no mystery about consciousness. There is, for instance, something of a paradox connected with any attempt to localise it. But I do not think these mysteries necessarily need to be solved before we can answer the question with which we are concerned in this paper.{{sfn|Turing|1950}}}}
 
  
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To Searle, as a philosopher investigating in the nature of [[philosophy of mind|mind]] and [[consciousness]], these are the relevant mysteries. The Chinese room is designed to show that the Turing test is insufficient to detect the presence of consciousness, even if the room can [[behaviourism|behave]] or [[functionalism (philosophy)|function]] as a conscious mind would.
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==References==
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<references />
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Newell and Simon had conjectured that a physical symbol system (such as a digital computer) had all the necessary machinery for "general intelligent action", or, as it is known today, [[artificial general intelligence]]. They framed this as a philosophical position, the [[physical symbol system|physical symbol system hypothesis]]: "A physical symbol system has the [[sufficient|necessary and sufficient means]] for general intelligent action."{{sfn|Newell|Simon|1976|p=116}}{{sfn|Russell|Norvig|2003|p=18}} The Chinese room argument does not refute this, because it is framed in terms of "intelligent action", i.e. the external behavior of the machine, rather than the presence or absence of understanding, consciousness and mind.
 
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===Robot and semantics replies: finding the meaning===
 
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As far as the person in the room is concerned, the symbols are just meaningless "squiggles." But if the Chinese room really "understands" what it is saying, then the symbols must get their meaning from somewhere. These arguments attempt to connect the symbols to the things they symbolize. These replies address Searle's concerns about [[intentionality]], [[symbol grounding]] and [[syntax]] vs. [[semantic]]s.
 
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;Robot reply:Suppose that instead of a room, the program was placed into a robot that could wander around and interact with its environment. This would allow a "[[causality|causal]] connection" between the symbols and things they represent.<ref>{{Harvnb|Searle|1980|p=7}}; {{Harvnb|Cole|2004|pp=9–11}}; {{Harvnb|Hauser|2006|p=3}}; {{Harvnb|Fearn|2007|p=44}}.</ref>{{efn|This position is held by [[Margaret Boden]], [[Tim Crane]], [[Daniel Dennett]], [[Jerry Fodor]], [[Stevan Harnad]], [[Hans Moravec]], and [[Georges Rey]], among others.{{sfn|Cole|2004|p=9}}}} [[Hans Moravec]] comments: "If we could graft a robot to a reasoning program, we wouldn't need a person to provide the meaning anymore: it would come from the physical world."<ref>Quoted in {{Harvnb|Crevier|1993|p=272}}</ref>{{efn| David Cole calls this the "externalist" account of meaning.{{sfn|Cole|2004|p=18}}}}
 
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:Searle's reply is to suppose that, unbeknownst to the individual in the Chinese room, some of the inputs came directly from a camera mounted on a robot, and some of the outputs were used to manipulate the arms and legs of the robot. Nevertheless, the person in the room is still just following the rules, and ''does not know what the symbols mean.'' Searle writes "he doesn't ''see'' what comes into the robot's eyes."{{sfn|Searle|1980|p=7}} (See [[Mary's room]] for a similar thought experiment.)
 
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;Derived meaning: Some respond that the room, as Searle describes it, ''is'' connected to the world: through the Chinese speakers that it is "talking" to and through the programmers who designed the [[knowledge base]] in his file cabinet. The symbols Searle manipulates ''are already meaningful'', they're just not meaningful to ''him''.<ref>{{Harvnb|Hauser|2006|p=11}}; {{Harvnb|Cole|2004|p=19}}.</ref>{{efn|The derived meaning reply is associated with [[Daniel Dennett]] and others.}}
 
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:Searle says that the symbols only have a "derived" meaning, like the meaning of words in books. The meaning of the symbols depends on the conscious understanding of the Chinese speakers and the programmers outside the room. The room, according to Searle, has no understanding of its own.{{efn|Searle distinguishes between "intrinsic" intentionality and "derived" intentionality. "Intrinsic" intentionality is the kind that involves "conscious understanding" like you would have in a human mind. [[Daniel Dennett]] doesn't agree that there is a distinction. David Cole writes "derived intentionality is all there is, according to Dennett."{{sfn|Cole|2004|p=19}}}}
 
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;Commonsense knowledge / contextualist reply:Some have argued that the meanings of the symbols would come from a vast "background" of [[commonsense knowledge]] encoded in the program and the filing cabinets. This would provide a "[[contextualism|context]]" that would give the symbols their meaning.{{sfn|Cole|2004|p=18}}{{efn|David Cole describes this as the "internalist" approach to meaning.{{sfn|Cole|2004|p=18}} Proponents of this position include [[Roger Schank]], [[Doug Lenat]], [[Marvin Minsky]] and (with reservations) [[Daniel Dennett]], who writes "The fact is that any program [that passed a Turing test] would have to be an extraordinarily supple, sophisticated, and multilayered system, brimming with 'world knowledge' and meta-knowledge and meta-meta-knowledge." {{sfn|Dennett|1991|p=438}}}}
 
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:Searle agrees that this background exists, but he does not agree that it can be built into programs. [[Hubert Dreyfus]] has also criticized the idea that the "background" can be represented symbolically.{{sfn|Dreyfus|1979|loc="The [[epistemological]] assumption"}}
 
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To each of these suggestions, Searle's response is the same: no matter how much knowledge is written into the program and no matter how the program is connected to the world, he is still in the room manipulating symbols according to rules. His actions are [[syntax|syntactic]] and this can never explain to him what the symbols stand for. Searle writes "syntax is insufficient for semantics."{{sfn|Searle|1984}}{{efn|Searle also writes "Formal symbols by themselves can never be enough for mental contents, because the symbols, by definition, have no meaning (or [[Interpretation (logic)|interpretation]], or semantics) except insofar as someone outside the system gives it to them."{{sfn|Motzkin|Searle|1989|p=45}}}}
 
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However, for those who accept that Searle's actions simulate a mind, separate from his own, the important question is not what the symbols mean ''to Searle'', what is important is what they mean ''to the virtual mind.'' While Searle is trapped in the room, the virtual mind is not: it is connected to the outside world through the Chinese speakers it speaks to, through the programmers who gave it world knowledge, and through the cameras and other sensors that [[roboticist]]s can supply.
 
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===Speed and complexity: appeals to intuition===
 
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The following arguments (and the intuitive interpretations of the arguments above) do not directly explain how a Chinese speaking mind could exist in Searle's room, or how the symbols he manipulates could become meaningful. However, by raising doubts about Searle's intuitions they support other positions, such as the system and robot replies. These arguments, if accepted, prevent Searle from claiming that his conclusion is obvious by undermining the intuitions that his certainty requires.
 
  
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Several critics believe that Searle's argument relies entirely on intuitions. [[Ned Block]] writes "Searle's argument depends for its force on intuitions that certain entities do not think."<ref>Quoted in {{Harvnb|Cole|2004|p=13}}.</ref> [[Daniel Dennett]] describes the Chinese room argument as a misleading "[[intuition pump]]"{{sfn|Dennett|1991|pp=437–440}} and writes "Searle's thought experiment depends, illicitly, on your imagining too simple a case, an irrelevant case, and drawing the 'obvious' conclusion from it."{{sfn|Dennett|1991|pp=437–440}}
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===Other Material===
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* See also wiki [[Emergent Behavior]]
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* and wiki [[Wisdom]]
  
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Some of the arguments above also function as appeals to intuition, especially those that are intended to make it seem more plausible that the Chinese room contains a mind, which can include the robot, commonsense knowledge, brain simulation and connectionist replies. Several of the replies above also address the specific issue of complexity. The connectionist reply emphasizes that a working artificial intelligence system would have to be as complex and as interconnected as the human brain. The commonsense knowledge reply emphasizes that any program that passed a Turing test would have to be "an extraordinarily supple, sophisticated, and multilayered system, brimming with 'world knowledge' and meta-knowledge and meta-meta-knowledge", as [[Daniel Dennett]] explains.{{sfn|Dennett|1991|p=438}}
 
  
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;Speed and complexity replies:The speed at which human brains process information is (by some estimates) 100 billion operations per second.{{sfn|Crevier|1993|p=269}} Several critics point out that the man in the room would probably take millions of years to respond to a simple question, and would require "filing cabinets" of astronomical proportions. This brings the clarity of Searle's intuition into doubt.<ref>{{Harvnb|Cole|2004|pp=14–15}}; {{Harvnb|Crevier|1993|pp=269–270}}; {{Harvnb|Pinker|1997|p=95}}.</ref>{{efn|Speed and complexity replies are made by [[Daniel Dennett]], [[Tim Maudlin]], [[David Chalmers]], [[Steven Pinker]], [[Paul Churchland]], [[Patricia Churchland]] and others.{{sfn|Cole|2004|p=14}} Daniel Dennett points out the complexity of world knowledge.{{sfn|Dennett|1991|p=438}}}}
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[[Category: Glossary]]
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[[Category: Philosophy]]
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[[Category: Artificial Intelligence]]
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[[Stevan Harnad]] is critical of speed and complexity replies when they stray beyond addressing our intuitions. He writes "Some have made a cult of speed and timing, holding that, when accelerated to the right speed, the computational may make a [[phase transition]] into the mental. It should be clear that is not a counterargument but merely an ''[[ad hoc]]'' speculation (as is the view that it is all just a matter of ratcheting up to the right degree of 'complexity.')"{{sfn|Harnad|2001|p=7}}{{efn|Critics of the "phase transition" form of this argument include Stevan Harnad, [[Tim Maudlin]], [[Daniel Dennett]] and David Cole.{{sfn|Cole|2004|p=14}} This "phase transition" idea is a version of [[strong emergentism]] (what [[Daniel Dennett]] derides as "Woo woo West Coast emergence"{{sfn|Crevier|1993|p=275}}). Harnad accuses [[Paul Churchland|Churchland]] and [[Patricia Churchland]] of espousing strong emergentism. Ray Kurzweil also holds a form of strong emergentism.{{sfn|Kurzweil|2005}}}}
 
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;Other minds reply:This reply points out that Searle's argument is a version of the [[problem of other minds]], applied to machines. There is no way we can determine if other people's subjective experience is the same as our own. We can only study their behavior (i.e., by giving them our own [[Turing test]]). Critics of Searle argue that he is holding the Chinese room to a higher standard than we would hold an ordinary person.
 
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[[Alan Turing]] anticipated Searle's line of argument (which he called "The Argument from Consciousness") in 1950 and makes the other minds reply.{{sfn|Turing|1950|pp=11–12}} He noted that people never consider the problem of other minds when dealing with each other. He writes that "instead of arguing continually over this point it is usual to have the polite convention that everyone thinks."{{sfn|Turing|1950|p=11}} The [[Turing test]] simply extends this "polite convention" to machines. He doesn't intend to solve the problem of other minds (for machines or people) and he do
 
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==Problem==
 
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As the process of collecting a [[User]]'s [[Identifier]]s, [[Attribute]]s etc. (which we can call claims) from a [[Distributed Identity]] resident across the cloud in unrelated databases and block-chains, the challenge of turning this data into an [[Authorization]] decision becomes quite complex. This is a problem that once was decided by the [[Knowledge]] of an expert, for example large bank loans needed to be approved by a vice president and large corporate checks need to be signed by the comptroller of the company.
 
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==Solution==
 
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The working solution can be viewed as an extension of an existing process in ecommerce where the [[Relying Party]] collects the claims about the user and the context of the request (which will likely include user behavior and value of the transaction) into a [[Trust Vector]] for processing by a [[Fraud Detection]] Service. The result will be used to make the [[Authorization]] decision, or it might initiate a continued collection of user claims for a retry.
 
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==References==
 
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See also [[Emergent behavior]]
 

Latest revision as of 15:53, 10 October 2025

Full Title or Meme

Facts, information, and skills acquired by a person through experience and education; the theoretical or practical Understanding of a subject.

the ladder from knowledge to wisdom.

  • Data → raw facts, unprocessed.
  • Information → data organized into patterns.
  • Knowledge → information understood and applied.
  • Wisdom → knowledge tempered by judgment, ethics, and lived perspective.

This is sometimes called the DIKW hierarchy (Data–Information–Knowledge–Wisdom). But it’s not a simple progression — each step after the first exhibits a Dialectic Harmony. Each step contains tensions that must be resolved to move upward.

Context

A significant number of philosophers have convinced themselves that there is no way that a computer could ever be said to have human Knowledge of any subject.

  • Alan Turing: The "standard interpretation" of the Turing Test, in which player C, the interrogator, is given the task of trying to determine which of two players: A or B on the other end of teletypewriter links is a computer and which is a human. The interrogator is limited to using the responses to typed in questions to make the determination. The Turing test which was introduced in 1950 to help answer the question "can machines think?" In the standard version, a human judge engages in a natural language conversation with a human and a machine designed to generate performance indistinguishable from that of a human being. All participants are separated from one another. If the judge cannot reliably tell the machine from the human, the machine is said to have passed the test. Turing then considered each possible objection to the proposal "machines can think", and found that there are simple, obvious answers if the question is de-mystified in this way. He did not, however, intend for the test to measure for the presence of "Consciousness" or "understanding". He did not believe this was relevant to the issues that he was addressing. He wrote: "I do not wish to give the impression that I think there is no mystery about consciousness. There is, for instance, something of a paradox connected with any attempt to localise it. But I do not think these mysteries necessarily need to be solved before we can answer the question with which we are concerned in this paper." Turing anticipated Searle's Chinese room argument (which he called "The Argument from Consciousness") in 1950 by noting that people never consider the problem of other minds when dealing with each other. He writes that "instead of arguing continually over this point it is usual to have the polite convention that everyone thinks." The Turing Test simply extends this "polite convention" to machines.
  • Newell and Simon had conjectured that a physical symbol system (such as a digital computer) had all the necessary machinery for "general intelligent action", or, as it is known today, artificial general intelligence. They framed this as a philosophical position, the hypothesis: "A physical symbol system has the necessary and sufficient means for general intelligent action." The Chinese room argument does not refute this, because it is framed in terms of "intelligent action", i.e. the external behavior of the machine, rather than the presence or absence of understanding, consciousness and mind.
  • Haldane: was skeptical of Materialist views and said in 1932: "If my options are the result of chemical processes going on in my brain, they are determined by the laws of chemistry, not the laws of logic".[1]
  • Searle: The Chinese room argument implements a version of the Turing Test where a program in the computer is held to be no different from a room full of Chinese scholars who cannot understand English, but can translate English to Chinese using rules in books and cards. Searle asserts that this Symbol Manipulation cannot result in a computer having a "mind", "understanding" or "consciousness" regardless of how intelligently or human-like the program may make the computer behave.[2] Searle argues that, without "understanding" (or "intentionality"), we cannot describe what the machine is doing as "thinking" and, since it does not think, it does not have a "mind" in anything like the normal sense of the word. Therefore, he concludes that "strong AI" is false. Most of the commentary about Knowledge seems to be an attempt to refute Searle's argument, which has become "something of a classic in cognitive science,". Varol Akman agrees, and has described the original paper as "an exemplar of philosophical clarity and purity".[3]. To any of other suggestions, Searle's response is always the same: no matter how much Knowledge is written into the program and no matter how the program is connected to the world, he is still in the room manipulating symbols according to rules. His actions are syntactic and this can never explain to him what the symbols stand for. Searle writes "syntax is insufficient for semantics." The Chinese room is designed to show that the Turing Test is insufficient to detect the presence of consciousness, even if the room can behave or function as a conscious mind would.
  • Dennett looks at all of Artificial Intelligence, and most particularly Deep Learning as "parasitic: deep learning (so far) discriminates but doesn't notice, That is the flood of data a system takes in does not have relevance for the system except a more 'food' to 'digest'" and further that "deep-learning machines are dependent on human understanding."[4] He seems to be unaware of the symbiotic relationship between humans and Wikipedia or the possibility of interaction between humans and Identity Management systems as further explicated on the page Bayesian Identity Proofing. But most damning of Dennett, and in fact all of these philosophers, is that they think of human Knowledge as a high point to be reached for and emulated, rather than as the distillation of the rantings and ravings of a self-absorbed bunch of apes.

But all this discussion by philosophers boils down to a silly verbalism, an argument about the meaning of words, which is why this wiki seeks to define the words that are used here. In this wiki words mean exactly what we want them to mean, no more and no less. Or, in other words, we chose words and their definitions as is demanded by Popper[5].

Problem

  • As the process of collecting a User's Identifiers, Attributes etc. (aka Claims) from a Distributed Identity hosted across the cloud in unrelated databases and block-chains, the challenge of turning this data into an Authorization decision becomes quite complex. This is a problem that once was decided by the Knowledge of an expert and the Understanding of the context, for example large bank loans needed to be approved by a vice president and large corporate checks need to be signed by the comptroller of the company.
  • Human Knowledge is, after all, "Human, all to Human"[6]. Which means it cannot escape the limitations and prejudices of actual people going about their daily business.

Writing

A famous myth recounted in Plato’s Phaedrus is one of the earliest critiques of technological mediation: Thoth presented writing to King Thamus, who questioned its value. Thamus argued that writing would lead to forgetfulness, as people would rely on written records instead of their memory. This story highlights the dual nature of writing as both a tool for knowledge and a potential crutch for memory.

Conclusion: Thoth's legacy as the inventor of writing has had a lasting impact on human communication and record-keeping, making him a central figure in the history of literacy and knowledge in ancient Egypt.

Solution

Knowledge comes in two forms (which are not completely distinct):

  1. Active knowledge that is accessible to a Mind in a form that can be (nearly) immediately accessed and used.
  2. Passive knowledge that is coded in some form that can be absorbed by a Mind and (hopefully) turned into active knowledge. (This process is also called learning.)

Arthur Shopenhauer described the two forms of knowledge thus:[7]

As the biggest library, if it is in disorder, is not as useful as a small but well-arranged one; so you may accumulate a vast amount of knowledge but it will be of far less value than a much smaller amount if you have not thought it over for yourself, because only through ordering what you know by comparing every truth with every other truth can you take complete possession of your knowledge and get it into your power. You can think about only what you know, so you ought to learn something, on the other hand, you can know only what you have thought about.

Knowledge in Identity Management

The working solution for Authentication and Authorization can be viewed as an extension of an existing process in ecommerce where the Relying Party collects the claims about the user and the context of the request (which will likely include user behavior and value of the transaction) into a Trust Vector for processing by a Fraud Detection Service. The result will be used to make the Authorization decision, or (if insufficient) it might initiate a continued collection of user claims for a retry.

In other words, with a Distributed Identity system, the Relying Party needs to be self-aware to the extent that it can determine what Knowledge it has about a User so that if that knowledge is insufficient to Authorize access, that the Relying Party has Knowledge to seek out the additional claims it needs to grant access. The current state-of-the-art is for Understanding of the context to be built into the algorithm that collects context, but that is starting to change with the inclusion of Artificial Intelligence into the Fraud Detection systems.

References

  1. ↑ J.B.S Haldane, Some Consequences of Materialism in The Inequality of Man. PENGUIN (PELICAN) (1932)
  2. ↑ John Searle, "Minds, Brains, and Programs", (1980) Behavioral and Brain Sciences
  3. ↑ Varol Akman review of Mind Design II http://www.google.com/search?client=safari&rls=en&q=cogprints.org/539/0/md2.ps&ie=UTF-8&oe=UTF-8
  4. ↑ Daniel C. Dennett, From Bacteria to Bach and Back: The Evolution of Minds. (2017-02-17) ISBN 978-0393242072
  5. ↑ Karl Popper The Open Society and Its Enemies (original 1945) Routledge ISBN 978-0415610216
  6. ↑ Friedrich Nietzsche, Human, All Too Human. (original 1878) ISBN 9780140446173
  7. ↑ Arthur Shopenhauer, Essays and Aphorisms. trans. R.J. Holllingdale, (1970) Penguin p. 89 ISBN 978-0140442274

Other Material

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