EPISTEMOLOGY AND INFORMATION

May combine two claims.

Given that the messenger plucked a name at random, the conditional probabilities are 1/8, equivocation is at a maximum of 3 bits, and transmitted information is zero.

“Given that the messenger plucked a name at random, the probabilities look like this: Pr[Herman was selected/the name”

The quote only partly states this claim.

If employees were determined to protect Barbara, transmitted information drops from 3 to 2.75 bits.

“, I t drops from 3 to 2.75.Some information is transmitted, but not as much as in the first case.”

May combine two claims. The quote only partly states this claim.

If probability is subjective, you and I can both speak truly when you assert and I deny that S knows Judy left early.

“As a result, it will turn out that you and I can both speak truly when you assert and I deny that S knows Judy left early.”

May combine two claims.

If a message carries only 2.75 bits of information, then although it is enough to produce true belief, it could not produce knowledge.

“If it carries only 2.75 bits of information, as it did in the hypothetical case where employees were determined to protect (i.e., not name) Barbara, then the message, although enough (if it carries the name”

• AssumptionThe authors state this as an assumption: To know what happened at a source, the amount of information received about it must be equal to or greater than the amount of information generated by the event.

May combine two claims.

Since a contingent fact has possible alternatives, it generates information, so there will always be a possibly equivocal channel between knower and known.

“Since a contingent fact is a fact for which there are possible alternatives, a fact that might not have been a fact, a fact that (because it has a probability less than one) generates information, one will always have a channel of communication between knower and known that is possibly equivocal, a channel that might mislead.”

Classified as probably not a substantial claim.

The choice about what collection of events and conditions determine the communication channel between knower and known determines what conclusions one will reach about skepticism and the limits of human knowledge.

“The choice one makes here-a choice about what collection of events and conditions are to determine the channel of communication between knower and known--is an important one.In the end, it determines what conclusions one will reach about such traditional epistemological problems as skepticism and the limits of human knowledge.”

Probably not a substantial claim: may not pass S4 (based).

If the conditional probabilities relating events at source and receiver are objective, then the resulting notion of information is objective.

“If these conditional probabilities are objective, then the resulting idea of information is objective.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Externalism maintains that some conditions required to know that P may be completely beyond the knower.

“Externalism is the name for an epistemological view that maintains that some of the conditions required to know that P may be, and often are, completely beyond the ken of the knower.”

May combine two claims.

To know whether S knows something requires knowing whether S's belief meets appropriate informational (probabilistic) conditions, and people, including S, may not have this knowledge.

“To know whether S knows something -that Judy left early, say-requires knowing whether S's belief that Judy left early meets appropriate informational (i.e., probabilistic) conditions, and this is a piece of knowledge that people (including S herself) may well not have.”

Classified as probably not a substantial claim.

The conditional probability of s given r is really the probability of s given r within a background of stable or fixed circumstances B.

“The conditional probability of s, an event at a source, given r, the condition at the receiver is really the probability of s, given r within a background of stable or fixed circumstances B.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Information-theoretic accounts of knowledge are typically advanced as forms of externalism.

“Information-theoretic accounts of knowledge are typically advanced as forms of externalism.”

May combine two claims.

The computational/information-sciences usage counts false data as information and ignores fundamental distinctions between truth and falsity.

“There are, to be sure, special uses of the term “information”-computer science is a case in point-in which truth seems to be irrelevant.Almost anything that can be put into the memory of a computer, anything that can be entered into a “data” base, is counted as information.”

• Also stated in: § 1. Necessary Clarifications: Meaning, Truth, and Information. · plain

  “This approach to information--an approach that is, I believe, widespread in the information sciences-blithely skates over absolutely fundamental distinctions between truth and falsity, between meaning and information.”

Probably not a substantial claim: may not pass S3 (load-bearing).

One strategy for the information-amount problem is a relativistic picture of knowledge attributions in which the amount of information needed to know depends on contextual factors.

“One can adopt a relativistic picture of knowledge attributions wherein the amount of information needed to know depends on contextual factors.”

May combine two claims.

Non-natural (linguistic) meaning does not entail truth: a sentence can mean she has the measles even when she does not.

“This contrasts with a language related (Grice called it “non-natural) meaning in which something (e.g., the sentence “She has the measles”) can mean she has the measles even when she doesn't have them.”

• cites Grice (1957)Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Classified as probably not a substantial claim.

According to a causal theory of knowledge, a belief qualifies as knowledge only if the belief stands in an appropriate causal relation to the facts.

“According to a causal theory of knowledge, a belief qualifies as knowledge only if the belief stands in an appropriate causal relation to the facts.”

• cites Goldman (1967) sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S2 (checkable).

A communication channel that is sometimes unreliable is not good enough to know even when it happens to be right.

“a communication channel that is sometimes unreliable is not good enough to know even when it happens to be right.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Communication theory defines the amount of transmitted information between source and receiver in terms of conditional probabilities between events that occur, or might have occurred, at these two places.

“Communication theory defines the amount of transmitted information between source and receiver in terms of the conditional probabilities between events that occur, or might have occurred, at these two places.”

Probably not a substantial claim: may not pass S2 (checkable).

Communication theory, insofar as it concentrates on averages, is irrelevant to the ordinary, epistemologically important sense of information.

“Communication Theory, in so far as it concentrates on averages, then, is irrelevant to the ordinary, the epistemologically important, sense of information.”

• AssumptionRests on an assumption: The ordinary, common-sense conception of information is the appropriate target for a theory of information.

Probably not a substantial claim: may not pass S1 (asserted), S4 (based).

The Q meter does not deliver information about values of Q below 100 to trusting users.

“This instrument doesn't deliver what it takes to know (i.e., information in the ordinary sense) because although the particular reading (“84”) one ends up trusting is within the instrument's reliable range (the instrument wouldn't read “84” unless Q was 84) you don't know this.”

Classified as probably not a substantial claim.

If probability is subjective, then information and the knowledge that depends on it take on a relativistic character.

“If, on the other hand, probability is given a subjective interpretation, information -and therefore the knowledge that depends on it-takes on a more relativistic character.”

Classified as probably not a substantial claim. May combine two claims.

According to communication theory, nothing (in the way of information) is needed to know that 3 is the cube root of 27; anything whatsoever is good enough to know a necessary truth.

“According to communication theory, then, it would seem that nothing (in the way of information) is needed to know that 3 is the cube root of 27.Or, to put the same point differently, informationally speaking anything whatsoever is good enough to know a necessary truth.”

May combine two claims.

If probability is objective, whether someone knows is a matter about which everyone, including the knower, may be ignorant.

“Whether or not someone knows is a matter about which everyone (including the knower) may be ignorant.”

Classified as probably not a substantial claim.

Eliminating all reasonable or relevant chances of being wrong is equivalent to requiring that the amount of information received about the state known to exist be at least as much as the amount of information generated by that state.

“and elimination of these is simply another way of requiring that the amount of information received about the state known to exist be (at least) as much as the amount of information generated by that state.”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Natural meaning is what indicators indicate; it is information and it has to be true.

“Natural meaning is what indicators indicate.It is what natural signs are signs of.Natural meaning is information.It has to be true.”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Information does not need conscious beings to exist, but knowledge does.

“Information doesn't need conscious beings to exist, but knowledge does.Without life there is no knowledge (because there is nobody to know anything), but there is still information.”

Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims. The quote only partly states this claim.

Communication theory, and the concept of information it yields, does not solve philosophical problems; it is at best a tool one can use to express solutions reached by other means.

“I refer to this as a”

Probably not a substantial claim: may not pass S2 (checkable).

Knowledge is knowledge of the truth.

“For knowledge is knowledge of the truth.”

• Also stated in: § 1. Necessary Clarifications: Meaning, Truth, and Information. · plain

  “you cannot know that Paris is the capital of Italy, that pigs can fly or that there is a Santa Claus.”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Meaning does not require truth; false statements can be as meaningful as true statements.

“Meaning is fine.You can't have truth without it.False statements, though, are as meaningful as true statements.”

• Also stated in: § 1. Necessary Clarifications: Meaning, Truth, and Information. · plain

  “distinguish meaning, something that need not be true, from information which must be true.”

• AssumptionRests on an assumption: The ordinary, common-sense conception of information is the appropriate target for a theory of information.

Probably not a substantial claim: may not pass S3 (load-bearing).

A second strategy retains an absolute picture of knowledge and treats conditional probabilities as computed against a background of stable or fixed circumstances B.

“A second possible way of dealing with the problem, one that retains an absolute (i.e., non-relativistic) picture of knowledge, is to adopt a more flexible (I would say more realistic) way of thinking about the conditional probabilities defining equivocation and, therefore, amount of transmitted information.Probabilities, in so far as they are relevant to practical affairs, are always computed a”

May combine two claims.

Communication theory deals in amounts of information and does not tell what information is communicated or whether enough is communicated to know.

“It does not try to tell us what information is communicated from s to r or even, if some information is communicated, how much is enough to know what is happening at s.”

• Also stated in: § 2. Information and Communication. · plain

  “About that it is silent.”

• cites Shannon (1948) sourceNot checked — no full text of the source

May combine two claims.

If messages make selection probabilities high but less than 1, equivocation is positive and the amount of transmitted information is less than the amount generated.

“As long as these probabilities are neither 0 nor 1, the individual contributions to equivocation (see footnote 2) will be positive.The equivocation, E, on the channel will, therefore, be greater than 0 and the amount of transmitted information will be less than the amount of information generated.”

Classified as probably not a substantial claim. May combine two claims.

If one counts every signal that would produce a belief about who was selected (whether or not it is Nancy), then memos carrying the name 'Herman' are counted and the communication channel becomes noisy.

“Then we count memos carrying the name Herman, and the communication channel, as so defined, starts to get noisy.”

Probably not a substantial claim: may not pass S4 (based).

The information required to know can be obtained from a signal without having to know that the signal carries it.

“The idea is that the information required to know can be obtained from a signal without having to know that the signal from which you obtain this information actually carries it.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Contextualism in the theory of knowledge embraces the result that knowledge attributions vary with the attributor.

“Contextualism (see Cohn 1986Cohn , 1988Cohn , 1999;;DeRose 1995;Feldman 1999;Heller 1999;Lewis 1996) in the theory of knowledge is a view that embraces this result.”

• cites Cohn 1986Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

• cites DeRose 1995 sourceNot checked — no full text of the source
• cites Lewis 1996 sourceNot checked — no full text of the source

May combine two claims.

If information is what it takes to know, then in the first case the information that Herman was selected was transmitted and in the second and third cases it was not.

“So if information is what it takes to know, then it seem correct to conclude that in the first case the information that Herman was selected was transmitted and in the second and third case it was not.”

• AssumptionThe authors state this as an assumption: Information is necessary for knowledge.

Probably not a substantial claim: may not pass S3 (load-bearing).

A theory of knowledge can be restricted to perceptual knowledge or knowledge of contingent empirical fact.

“A third way to deal with the problem, the way I took in Dretske 1981, is to restrict one's theory of knowledge to perceptual knowledge or (more generally) to knowledge of contingent (empirical) fact.”

• cites Dretske 1981Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Classified as probably not a substantial claim.

Information is different from knowledge.

“Information is, in this way, different from knowledge.”

May combine two claims.

The communication of information depends on there being, in fact, a reliable channel between source and receiver; it does not require that this reliability itself be necessary.

“The communication of information depends on their being, in fact, a reliable channel between a source and a receiver.It doesn't require that this reliability itself be necessary.”

The quote only partly states this claim.

Messages about an employee's selection will never carry as much information as is generated by that employee's selection when the conditional probabilities are neither 0 nor 1.

“Messages about an employee's selection will never carry as much information as is generated by that employee's selection.”

Probably not a substantial claim: may not pass S2 (checkable).

Information, as commonly understood, must be true; false statements are not information.

“information, unlike meaning, has to be true.”

• Also stated in: § 1. Necessary Clarifications: Meaning, Truth, and Information. · plain

  “information which must be true.”

• Also stated in: § 1. Necessary Clarifications: Meaning, Truth, and Information. · plain

  “misinformation is not a kind of information anymore than decoy ducks are a kind of duck.”

• AssumptionRests on an assumption: The ordinary, common-sense conception of information is the appropriate target for a theory of information.

Classified as probably not a substantial claim.

In the ball example, before seeing the color, you cannot know that S selected a black ball even though the probability is 99%.

“Most people would say, for instance, that if S is drawing balls at random from a collection of balls (100, say) only one of which is white, all the rest being black, you can't, before you see the color of the ball, know that S selected a black ball even though you know the probability of its being black is 99%.”

May combine two claims.

If probability is subjective, whether S knows depends on who is attributing the knowledge.

“Whether or not S knows now depends on who is attributing the knowledge.”

May combine two claims.

In the scrupulous case one could know that Herman was selected; in the random and Barbara-protected cases one could not.

“One could know that it was Herman in the first case, when the message contained 3 bits of information-exactly the amount generated by Herman's selection -and one couldn't know in the second and third case, when the memo contains 0 bits and 2.75 bits of information, something less than the amount generated by Herman's selection.”

• AssumptionThe authors state this as an assumption: To know what happened at a source, the amount of information received about it must be equal to or greater than the amount of information generated by the event.