Wikipedia (the "free online encyclopedia that anyone can edit") is having a huge impact on how a great many people gather information about the world. So, it is important for epistemologists and information scientists to ask whether or not people are likely to acquire knowledge as a result of having access to this information source. In other words, is Wikipedia having good epistemic consequences? After surveying the various concerns that have been raised about the reliability of Wikipedia, this paper argues (...) that the epistemic consequences of people using Wikipedia as a source of information are likely to be quite good. According to several empirical studies, the reliability of Wikipedia compares favorably to the reliability of traditional encyclopedias. Furthermore, the reliability of Wikipedia compares even more favorably to the reliability of those information sources that people would be likely to use if Wikipedia did not exist (viz., websites that are as freely and easily accessible as Wikipedia). In addition, Wikipedia has a number of other epistemic virtues (e.g., power, speed, and fecundity) that arguably outweigh any deficiency in terms of reliability. Even so, epistemologists and information scientists should certainly be trying to identify changes (or alternatives) to Wikipedia that will bring about even better epistemic consequences. This paper suggests that, in order to improve Wikipedia, we need to clarify what our epistemic values are and we need a better understanding of why Wikipedia works as well as it does. (shrink)
Several philosophers have used the framework of means/ends reasoning to explain the methodological choices made by scientists and mathematicians (see, e.g., Goldman 1999, Levi 1962, Maddy 1997). In particular, they have tried to identify the epistemic objectives of scientists and mathematicians that will explain these choices. In this paper, the framework of means/ends reasoning is used to study an important methodological choice made by mathematicians. Namely, mathematicians will only use deductive proofs to establish the truth of mathematical claims. In this (...) paper, I argue that none of the epistemic objectives of mathematicians that are currently on the table provide a satisfactory explanation of this rejection of probabilistic proofs. (shrink)
We consider the mission of the librarian as an information provider and the core value that gives this mission its social importance. Our focus here is on those issues that arise in relation to the role of the librarian as an information provider. In particular, we focus on questions of the selection and organization of information, which bring up issues of bias, neutrality, advocacy, and children's rights to access information.
There are many philosophical questions surrounding the notion of lying. Is it ever morally acceptable to lie? Can we acquire knowledge from people who might be lying to us? More fundamental, however, is the question of what, exactly, constitutes the concept of lying. According to one traditional definition, lying requires intending to deceive (Augustine. (1952). Lying (M. Muldowney, Trans.). In R. Deferrari (Ed.), Treatises on various subjects (pp. 53?120). New York, NY: Catholic University of America). More recently, Thomas Carson (2006. (...) The definition of lying. Nous, 40, 284?306) has suggested that lying requires warranting the truth of what you do not believe. This paper examines these two prominent definitions and some cases that seem to pose problems for them. Importantly, theorists working on this topic fundamentally disagree about whether these problem cases are genuine instances of lying and, thus, serve as counterexamples to the definitions on offer. To settle these disputes, we elicited judgments about the proposed counterexamples from ordinary language users unfettered by theoretical bias. The data suggest that everyday speakers of English count bald-faced lies and proviso lies as lies. Thus, we claim that a new definition is needed to capture common usage. Finally, we offer some suggestions for further research on this topic and about the moral implications of our investigation into the concept of lying. (shrink)
(2013). Veritistic Epistemology and the Epistemic Goals of Groups: A Reply to Vähämaa. Social Epistemology: Vol. 27, No. 1, pp. 21-25. doi: 10.1080/02691728.2012.760666.
According to the traditional philosophical definition, you lie if and only if you assert what you believe to be false with the intent to deceive. However, several philosophers (e.g., Carson 2006, Sorensen 2007, Fallis 2009) have pointed out that there are lies that are not intended to deceive and, thus, that the traditional definition fails. In 2009, I suggested an alternative definition: you lie if and only if you say what you believe to be false when you believe that one (...) of Paul Grice's conversational norms (“Do not say what you believe to be false”) is in effect. Faulkner (forthcoming), Stokke (forthcoming), and Pruss (2012) have subsequently argued that my 2009 definition fails as well because it counts some statements that are clearly not lies as being lies. In this paper, I identify some additional counter-examples of this sort. But I argue that my 2009 definition can easily be revised to deal with such counter-examples once we clarify that the relevant norm is really against communicating something false rather than against merely saying it. Nevertheless, I show that even this revised version of my 2009 definition fails because it counts some statements that are lies as not being lies. Lies told by young children – which uncontroversially count as lies on the traditional philosophical definition – suggest that lying (as well as asserting in general) does not require believing that such a norm is in effect. Even so, I claim that, since all liars intend to do something that would violate this norm if it were in effect, there is a successful definition of lying that is at least in the spirit of my 2009 definition. (shrink)
If knowledge is the norm of practical reasoning, then we should be able to alter people's behavior by affecting their knowledge as well as by affecting their beliefs. Thus, as Roy Sorensen (2010) suggests, we should expect to find people telling lies that target knowledge rather than just lies that target beliefs. In this paper, however, I argue that Sorensen's discovery of “knowledge-lies” does not support the claim that knowledge is the norm of practical reasoning. First, I use a Bayesian (...) framework to show that in each of Sorensen's examples, knowledge-lies alter people's behavior by affecting their beliefs. Second, I show that while we can imagine lies that target knowledge without targeting beliefs, they cannot alter people's behavior. In other words, knowledge-lies actually work (i.e., manipulate behavior) by targeting beliefs or they do not work at all. (shrink)
According to the standard philosophical definition of lying, you lie if you say something that you believe to be false with the intent to deceive. Recently, several philosophers have argued that an intention to deceive is not a necessary condition on lying. But even if they are correct, it might still be suggested that the standard philosophical definition captures the type of lie that philosophers are primarily interested in (viz., lies that are intended to deceive). In this paper, I argue (...) that the standard philosophical definition is not adequate as a definition of deceptive lying either. I then suggest two plausible alternative definitions of this concept. (shrink)
In order to lie, you have to say something that you believe to be false. But lying is not simply saying what you believe to be false. Philosophers have made several suggestions for what the additional condition might be. For example, it has been suggested that the liar has to intend to deceive (Augustine 395, Bok 1978, Mahon 2006), that she has to believe that she will deceive (Chisholm and Feehan 1977), or that she has to warrant the truth of (...) what she says (Carson 2006). In this paper, I argue that none of the existing definitions of lying identify a necessary condition on lying. I claim that lying is saying what you believe to be false when you believe that the following norm of conversation is in effect: "Do not say what you believe to be false" (Grice 1989, 27). And I argue that this definition handles all of the counter-examples to the existing definitions. (shrink)
Bayesians take “definite” or “single-case” probabilities to be basic. Definite probabilities attach to closed formulas or propositions. We write them here using small caps: PROB(P) and PROB(P/Q). Most objective probability theories begin instead with “indefinite” or “general” probabilities (sometimes called “statistical probabilities”). Indefinite probabilities attach to open formulas or propositions. We write indefinite probabilities using lower case “prob” and free variables: prob(Bx/Ax). The indefinite probability of an A being a B is not about any particular A, but rather about the (...) property of being an A. In this respect, its logical form is the same as that of relative frequencies. For instance, we might talk about the probability of a human baby being female. That probability is about human babies in general — not about individuals. If we examine a baby and determine conclusively that she is female, then the definite probability of her being female is 1, but that does not alter the indefinite probability of human babies in general being female. Most objective approaches to probability tie probabilities to relative frequencies in some way, and the resulting probabilities have the same logical form as the relative frequencies. That is, they are indefinite probabilities. The simplest theories identify indefinite probabilities with relative frequencies.3 It is often objected that such “finite frequency theories” are inadequate because our probability judgments often diverge from relative frequencies. For example, we can talk about a coin being fair (and so the indefinite probability of a flip landing heads is 0.5) even when it is flipped only once and then destroyed (in which case the relative frequency is either 1 or 0). For understanding such indefinite probabilities, it has been suggested that we need a notion of probability that talks about possible instances of properties as well as actual instances.. (shrink)
Several different Bayesian models of epistemic utilities (see, e. g., [37], [24], [40], [46]) have been used to explain why it is rational for scientists to perform experiments. In this paper, I argue that a model-suggested independently by Patrick Maher [40] and Graham Oddie [46]-that assigns epistemic utility to degrees of belief in hypotheses provides the most comprehensive explanation. This is because this proper scoring rule (PSR) model captures a wider range of scientifically acceptable attitudes toward epistemic risk than the (...) other Bayesian models that have been proposed. I also argue, however, that even the PSR model places unreasonably tight restrictions on a scientist's attitude toward epistemic risk. As a result, such Bayesian models of epistemic utilities fail as normative accounts-not just as descriptive accounts (see, e. g., [31], [14])-of scientific inquiry. (shrink)
We all pursue epistemic goals as individuals. But we also pursue collective epistemic goals. In the case of many groups to which we belong, we want each member of the group - and sometimes even the group itself - to have as many true beliefs as possible and as few false beliefs as possible. In this paper, I respond to the main objections to the very idea of such collective epistemic goals. Furthermore, I describe the various ways that our collective (...) epistemic goals can come into conflict with each other. And I argue that we must appeal to pragmatic considerations in order to resolve such conflicts. (shrink)
How can one verify the accuracy of recorded information (e.g., information found in books, newspapers, and on Web sites)? In this paper, I argue that work in the epistemology of testimony (especially that of philosophers David Hume and Alvin Goldman) can help with this important practical problem in library and information science. This work suggests that there are four important areas to consider when verifying the accuracy of information: (i) authority, (ii) independent corroboration, (iii) plausibility and support, and (iv) presentation. (...) I show how philosophical research in these areas can improve how information professionals go about teaching people how to evaluate information. Finally, I discuss several further techniques that information professionals can and should use to make it easier for people to verify the accuracy of information. (shrink)
An important issue for information ethics is how much control people should have over the dissemination of information that they have created. Since intellectual property policies have an impact on our welfare primarily because they have a huge impact on our ability to acquire knowledge, there is an important role for epistemology in resolving this issue. This paper discusses the various ways in which intellectual property policies can impact knowledge acquisition both positively and negatively. In particular, it looks at how (...) intellectual property policies can affect the amount of information that people create, the quality of that information, the accessibility of that information, the diversity of that information, and the locatability of that information. (shrink)
In “How to Collaborate,” Paul Thagard tries to explain why there is so much collaboration in science, and so little collaboration in philosophy, by giving an epistemic cost-benefit analysis. In this paper, I argue that an adequate explanation requires a more fully developed epistemic value theory than Thagard utilizes. In addition, I offer an alternative to Thagard’s explanation of the lack of collaboration in philosophy. He appeals to its lack of a tradition of collaboration and to the a priori nature (...) of much philosophical research. I claim that philosophers rarely collaborate simply because they can usually get the benefits without paying the costs of actually collaborating. (shrink)
In order to guide the decisions of real people who want to bring about good epistemic outcomes for themselves and others, we need to understand our epistemic values. In Knowledge in a Social World, Alvin Goldman has proposed an epistemic value theory that allows us to say whether one outcome is epistemically better than another. However, it has been suggested that Goldman's theory is not really an epistemic value theory at all because whether one outcome is epistemically better than another (...) partly depends on our non-epistemic interests. In this paper, I argue that an epistemic value theory that serves the purposes of social epistemology must incorporate non- epistemic interests in much the way that Goldman's theory does. In fact, I argue that Goldman's theory does not go far enough in this direction. In particular, the epistemic value of having a particular true belief should actually be weighted by how interested we are in the topic. (shrink)
The doctrinal paradox shows that aggregating individual judgments by taking a majority vote does not always yield a consistent set of collective judgments. Philip Pettit, Luc Bovens, and Wlodek Rabinowicz have recently argued for the epistemic superiority of an aggregation procedure that always yields a consistent set of judgments. This paper identifies several additional epistemic advantages of their consistency maintaining procedure. However, this paper also shows that there are some circumstances where the majority vote procedure is epistemically superior. The epistemic (...) value of maintaining consistency does not always outweigh the epistemic value of making true judgments. (shrink)
In “How to Collaborate,” Paul Thagard tries to explain why there is so much collaboration in science, and so little collaboration in philosophy, by giving an epistemic cost-benefit analysis. In this paper, I argue that an adequate explanation requires a more fully developed epistemic value theory than Thagard utilizes. In addition, I offer an alternative to Thagard’s explanation of the lack of collaboration in philosophy. He appeals to its lack of a tradition of collaboration and to the a priori nature (...) of much philosophical research. I claim that philosophers rarely collaborate simply because they can usually get the benefits without paying the costs of actually collaborating. (shrink)
Three of the major issues in information ethics – intellectual property, speech regulation, and privacy – concern the morality of restricting peoples access to certain information. Consequently, policies in these areas have a significant impact on the amount and types of knowledge that people acquire. As a result, epistemic considerations are critical to the ethics of information policy decisions (cf. Mill, 1978 [1859]). The fact that information ethics is a part of the philosophy of information highlights this important connection with (...) epistemology. In this paper, I illustrate how a value-theoretic approach to epistemology can help to clarify these major issues in information ethics. However, I also identify several open questions about epistemic values that need to be answered before we will be able to evaluate the epistemic consequences of many information policies. (shrink)
In his recent book, Knowledge in a Social World, Alvin Goldman claims to have established that if a reasoner starts with accurate estimates of the reliability of new evidence and conditionalizes on this evidence, then this reasoner is objectively likely to end up closer to the truth. In this paper, I argue that Goldman's result is not nearly as philosophically significant as he would have us believe. First, accurately estimating the reliability of evidence – in the sense that Goldman requires (...) – is not quite as easy as it might sound. Second, being objectively likely to end up closer to the truth – in the sense that Goldman establishes – is not quite as valuable as it might sound. (shrink)
Recently, certain philosophers of mathematics (Fallis [1997]; Womack and Farach [(1997]) have argued that there are no epistemic considerations that should stop mathematicians from using probabilistic methods to establish that mathematical propositions are true. However, mathematicians clearly should not use methods that are unreliable. Unfortunately, due to the fact that randomized algorithms are not really random in practice, there is reason to doubt their reliability. In this paper, I analyze the prospects for establishing that randomized algorithms are reliable. I end (...) by arguing that it would be inconsistent for mathematicians to suspend judgement on the truth of mathematical propositions on the basis of worries about the reliability of randomized algorithms. (shrink)
