Results for 'D. Fallis'

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  1.  93
    The Reliability of Randomized Algorithms.D. Fallis - 2000 - British Journal for the Philosophy of Science 51 (2):255-271.
    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 (...)
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  2. An Objectivist Argument for Thirdism.Ian Evans, Don Fallis, Peter Gross, Terry Horgan, Jenann Ismael, John Pollock, Paul D. Thorn, Jacob N. Caton, Adam Arico, Daniel Sanderman, Orlin Vakerelov, Nathan Ballantyne, Matthew S. Bedke, Brian Fiala & Martin Fricke - 2008 - Analysis 68 (2):149-155.
    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 (...)
     
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  3.  26
    Lying and Deception: Theory and Practice, by Thomas L. Carson. [REVIEW]D. Fallis - 2011 - Mind 120 (480):1232-1237.
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  4. Wikipistemology.Don Fallis - 2011 - In Alvin I. Goldman & Dennis Whitcomb (eds.), Social Epistemology: Essential Readings. New York: Oxford University Press.
     
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  5.  43
    Goldman on Probabilistic Inference.Fallis Don - 2002 - Philosophical Studies 109 (3):223 - 240.
    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 (...)
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  6.  3
    Socrates and divine revelation.Lewis Fallis - 2018 - Rochester, NY: University of Rochester Press.
    An account of Socrates' encounter with divine revelation.
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  7. The truth about lying.Don Fallis - 2018 - In Heather L. Rivera & Alexander E. Hooke (eds.), The Twilight Zone and philosophy: a dangerous dimension to visit. Chicago: Open Court.
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  8.  30
    The Bioethics of Environmental Injustice: Ethical, Legal, and Clinical Implications of Unhealthy Environments.Keisha Ray & Jane Fallis Cooper - 2023 - American Journal of Bioethics 24 (3):9-17.
    Environmental health remains a niche topic in bioethics, despite being a prominent social determinant of health. In this paper we argue that if bioethicists are to take the project of health justice as a serious one, then we have to address environmental injustices and the threats they pose to our bioethics principles, health equity, and clinical care. To do this, we lay out three arguments supporting prioritizing environmental health in bioethics based on bioethics principles including a commitment to vulnerable populations (...)
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  9. What Is Lying.Don Fallis - 2009 - Journal of Philosophy 106 (1):29-56.
    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 (...)
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  10. The Epistemic Threat of Deepfakes.Don Fallis - 2020 - Philosophy and Technology 34 (4):623-643.
    Deepfakes are realistic videos created using new machine learning techniques rather than traditional photographic means. They tend to depict people saying and doing things that they did not actually say or do. In the news media and the blogosphere, the worry has been raised that, as a result of deepfakes, we are heading toward an “infopocalypse” where we cannot tell what is real from what is not. Several philosophers have now issued similar warnings. In this paper, I offer an analysis (...)
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  11.  76
    Accuracy, Conditionalization, and Probabilism.Peter J. Lewis & Don Fallis - manuscript
    Accuracy-based arguments for conditionalization and probabilism appear to have a significant advantage over their Dutch Book rivals. They rely only on the plausible epistemic norm that one should try to decrease the inaccuracy of one's beliefs. Furthermore, it seems that conditionalization and probabilism follow from a wide range of measures of inaccuracy. However, we argue that among the measures in the literature, there are some from which one can prove conditionalization, others from which one can prove probabilism, and none from (...)
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  12. Lies, damned lies, and statistics: An empirical investigation of the concept of lying.Adam J. Arico & Don Fallis - 2013 - Philosophical Psychology 26 (6):790 - 816.
    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. (...)
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  13. The greatest liar has his believers: the social epistemology of political lying.Kay Mathiesen & Don Fallis - 2016 - In Emily Crookston, David Killoren & Jonathan Trerise (eds.), Ethics in Politics: The Rights and Obligations of Individual Political Agents. Routledge.
     
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  14. Fake news is counterfeit news.Don Fallis & Kay Mathiesen - forthcoming - Tandf: Inquiry:1-20.
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  15. Davidson was Almost Right about Lying.Don Fallis - 2013 - Australasian Journal of Philosophy 91 (2):337-353.
    Donald Davidson once suggested that a liar ?must intend to represent himself as believing what he does not?. In this paper I argue that, while Davidson was mistaken about lying in a few important respects, his main insight yields a very attractive definition of lying. Namely, you lie if and only if you say something that you do not believe and you intend to represent yourself as believing what you say. Moreover, I show that this Davidsonian definition can handle counter-examples (...)
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  16. What is Disinformation?Don Fallis - 2015 - Library Trends 63 (3):401-426.
    Prototypical instances of disinformation include deceptive advertising (in business and in politics), government propaganda, doctored photographs, forged documents, fake maps, internet frauds, fake websites, and manipulated Wikipedia entries. Disinformation can cause significant harm if people are misled by it. In order to address this critical threat to information quality, we first need to understand exactly what disinformation is. This paper surveys the various analyses of this concept that have been proposed by information scientists and philosophers (most notably, Luciano Floridi). It (...)
     
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  17. Are Bald‐Faced Lies Deceptive after All?Don Fallis - 2014 - Ratio 28 (1):81-96.
    According to the traditional philosophical definition, you lie if and only if you say something that you believe to be false and you intend to deceive someone into believing what you say. However, philosophers have recently noted the existence of bald-faced lies, lies which are not intended to deceive anyone into believing what is said. As a result, many philosophers have removed deception from their definitions of lying. According to Jennifer Lackey, this is ‘an unhappy divorce’ because it precludes an (...)
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  18. Toward a formal analysis of deceptive signaling.Don Fallis & Peter J. Lewis - 2019 - Synthese 196 (6):2279-2303.
    Deception has long been an important topic in philosophy. However, the traditional analysis of the concept, which requires that a deceiver intentionally cause her victim to have a false belief, rules out the possibility of much deception in the animal kingdom. Cognitively unsophisticated species, such as fireflies and butterflies, have simply evolved to mislead potential predators and/or prey. To capture such cases of “functional deception,” several researchers Machiavellian intelligence II, Cambridge University Press, Cambridge, pp 112–143, 1997; Searcy and Nowicki, The (...)
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  19. Lying and Deception.Don Fallis - 2010 - Philosophers' Imprint 10.
    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 (...)
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  20. Tom Petty Didn't Really Need to Know.Daniel Zelinski & Don Fallis - 2019 - In Randall E. Auxier & Megan A. Volpert (eds.), Tom Petty and Philosophy: We Need to Know. Chicago, Illinois: Open Court Publishing.
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  21. Bullshitting, Lying, and Indifference toward Truth.Don Fallis & Andreas Stokke - 2017 - Ergo: An Open Access Journal of Philosophy 4:277-309.
    This paper is about some of the ways in which people sometimes speak while be- ing indifferent toward what they say. We argue that what Harry Frankfurt called ‘bullshitting’ is a mode of speech marked by indifference toward inquiry, the coop- erative project of reaching truth in discourse. On this view bullshitting is character- ized by indifference toward the project of advancing inquiry by making progress on specific subinquiries, represented by so-called questions under discussion. This ac- count preserves the central (...)
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  22. The Brier Rule Is not a Good Measure of Epistemic Utility.Don Fallis & Peter J. Lewis - 2016 - Australasian Journal of Philosophy 94 (3):576-590.
    Measures of epistemic utility are used by formal epistemologists to make determinations of epistemic betterness among cognitive states. The Brier rule is the most popular choice among formal epistemologists for such a measure. In this paper, however, we show that the Brier rule is sometimes seriously wrong about whether one cognitive state is epistemically better than another. In particular, there are cases where an agent gets evidence that definitively eliminates a false hypothesis, but where the Brier rule says that things (...)
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  23.  92
    Intentional gaps in mathematical proofs.Don Fallis - 2003 - Synthese 134 (1-2):45 - 69.
  24. The Epistemic Status of Probabilistic Proof.Don Fallis - 1997 - Journal of Philosophy 94 (4):165-186.
  25.  93
    Lying as a Violation of Grice’s First Maxim of Quality.Don Fallis - 2012 - Dialectica 66 (4):563-581.
    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 (...)
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  26.  88
    Attitudes Toward Epistemic Risk and the Value of Experiments.Don Fallis - 2007 - Studia Logica 86 (2):215-246.
    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 (...)
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  27.  56
    Skyrms on the Possibility of Universal Deception.Don Fallis - 2015 - Philosophical Studies 172 (2):375-397.
    In the Groundwork, Immanuel Kant famously argued that it would be self-defeating for everyone to follow a maxim of lying whenever it is to his or her advantage. In his recent book Signals, Brian Skyrms claims that Kant was wrong about the impossibility of universal deception. Skyrms argues that there are Lewisian signaling games in which the sender always sends a signal that deceives the receiver. I show here that these purportedly deceptive signals simply fail to make the receiver as (...)
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  28. Collective epistemic goals.Don Fallis - 2007 - Social Epistemology 21 (3):267 – 280.
    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 (...)
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  29.  42
    Shedding Light on Keeping People in the Dark.Don Fallis - 2018 - Topics in Cognitive Science 12 (2):535-554.
    We want to keep hackers in the dark about our passwords and our credit card numbers. We want to keep potential eavesdroppers in the dark about our private communications with friends and business associates. This need for secrecy raises important questions in epistemology (how do we do it?) and in ethics (should we do it?). In order to answer these questions, it would be useful to have a good understanding of the concept of keeping someone in the dark. Several philosophers (...)
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  30.  29
    Deceiving versus manipulating: An evidence‐based definition of deception.Don Fallis - forthcoming - Analytic Philosophy.
    What distinguishes deception from manipulation? Cohen (Australasian Journal of Philosophy, 96, 483 and 2018) proposes a new answer and explores its ethical implications. Appealing to new cases of “non‐deceptive manipulation” that involve intentionally causing a false belief, he offers a new definition of deception in terms of communication that rules out these counterexamples to the traditional definition. And, he leverages this definition in support of the claim that deception “carries heavier moral weight” than manipulation. In this paper, I argue that (...)
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  31. Epistemic Value Theory and Social Epistemology.Don Fallis - 2006 - Episteme 2 (3):177-188.
    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 (...)
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  32. Epistemic value theory and information ethics.Don Fallis - 2004 - Minds and Machines 14 (1):101-117.
    Three of the major issues in information ethics – intellectual property, speech regulation, and privacy – concern the morality of restricting people’s 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 (...)
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  33. Toward an epistemology of Wikipedia.Don Fallis - 2008 - Journal of the American Society for Information Science and Technology 59 (10):1662--1674.
    Wikipedia 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 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 article argues that the epistemic consequences of people using Wikipedia as a (...)
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  34. A World of States of Affairs.D. M. Armstrong - 1997 - New York: Cambridge University Press.
    In this important study D. M. Armstrong offers a comprehensive system of analytical metaphysics that synthesises but also develops his thinking over the last twenty years. Armstrong's analysis, which acknowledges the 'logical atomism' of Russell and Wittgenstein, makes facts the fundamental constituents of the world, examining properties, relations, numbers, classes, possibility and necessity, dispositions, causes and laws. All these, it is argued, find their place and can be understood inside a scheme of states of affairs. This is a comprehensive and (...)
  35. The Epistemic Costs and Benefits of Collaboration.Don Fallis - 2006 - Southern Journal of Philosophy 44 (S1):197-208.
    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 (...)
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  36.  47
    Animal deception and the content of signals.Don Fallis & Peter J. Lewis - 2021 - Studies in History and Philosophy of Science Part A 87 (C):114-124.
    In cases of animal mimicry, the receiver of the signal learns the truth that he is either dealing with the real thing or with a mimic. Thus, despite being a prototypical example of animal deception, mimicry does not seem to qualify as deception on the traditional definition, since the receiver is not actually misled. We offer a new account of propositional content in sender-receiver games that explains how the receiver is misled by mimicry. We show that previous accounts of deception, (...)
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  37.  61
    Privacy and lack of knowledge.Don Fallis - 2013 - Episteme 10 (2):153-166.
    Two sorts of connections between privacy and knowledge (or lack thereof) have been suggested in the philosophical literature. First, Alvin Goldman has suggested that protecting privacy typically leads to less knowledge being acquired. Second, several other philosophers (e.g. Parent, Matheson, Blaauw and Peels) have claimed that lack of knowledge is definitive of having privacy. In other words, someone not knowing something is necessary and sufficient for someone else having privacy about that thing. Or equivalently, someone knowing something is necessary and (...)
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  38. What Do Mathematicians Want? Probabilistic Proofs and the Epistemic Goals of Mathematicians.Don Fallis - 2002 - Logique Et Analyse 45.
    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 (...)
     
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  39.  10
    Probabilistic Proofs and the Collective Epistemic Goals of Mathematicians.Don Fallis - 2011 - In Hans Bernhard Schmid, Daniel Sirtes & Marcel Weber (eds.), Collective Epistemology. Heusenstamm, Germany: Ontos. pp. 157-175.
    Mathematicians only use deductive proofs to establish that mathematical claims are true. They never use inductive evidence, such as probabilistic proofs, for this task. Don Fallis (1997 and 2002) has argued that mathematicians do not have good epistemic grounds for this complete rejection of probabilistic proofs. But Kenny Easwaran (2009) points out that there is a gap in this argument. Fallis only considered how mathematical proofs serve the epistemic goals of individual mathematicians. Easwaran suggests that deductive proofs might (...)
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  40.  92
    What Liars Can Tell Us about the Knowledge Norm of Practical Reasoning.Don Fallis - 2011 - Southern Journal of Philosophy 49 (4):347-367.
    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 (...)
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  41.  56
    Information Ethics and the Library Profession.Kay Mathiesen & Don Fallis - 2008 - In Herman Tavani and Kenneth Himma (ed.), The handbook of information and computer ethics. New York, NY, USA: pp. 221-244.
    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.
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  42.  39
    Accuracy, conditionalization, and probabilism.Don Fallis & Peter J. Lewis - 2019 - Synthese 198 (5):4017-4033.
    Accuracy-based arguments for conditionalization and probabilism appear to have a significant advantage over their Dutch Book rivals. They rely only on the plausible epistemic norm that one should try to decrease the inaccuracy of one’s beliefs. Furthermore, conditionalization and probabilism apparently follow from a wide range of measures of inaccuracy. However, we argue that there is an under-appreciated diachronic constraint on measures of inaccuracy which limits the measures from which one can prove conditionalization, and none of the remaining measures allow (...)
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  43. Floridi on Disinformation.Don Fallis - 2011 - Etica and Politica / Ethics and Politics (2):201-214.
  44.  88
    Introduction: The Epistemology of Mass Collaboration.Don Fallis - 2009 - Episteme 6 (1):1-7.
    Human beings regularly work together to get things done. In particular, people frequently collaborate on the production and dissemination of knowledge. For example, scientists often work together in teams to make new discoveries. How such collaborations produce knowledge, and how well they produce knowledge, are important questions for epistemology. In fact, several epistemologists have addressed such questions regarding collaborative scientific research.
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  45.  90
    Epistemic Value Theory and Judgment Aggregation.Don Fallis - 2005 - Episteme 2 (1):39-55.
    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 (...)
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  46. Introduction: Social epistemology and information science.Don Fallis - 2002 - Social Epistemology 16 (1):1 – 4.
  47.  39
    On Verifying the Accuracy of Information: Philosophical Perspectives.Don Fallis - 2004 - Library Trends 52 (3):463-487.
    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. (...)
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  48. Veritistic Social Epistemology and Information Science.Don Fallis - 2000 - Social Epistemology 14 (4):305 – 316.
  49.  25
    Simulation and self-location.Don Fallis & Peter J. Lewis - 2023 - Synthese 202 (6):1-13.
    It is possible that you are living in a simulation—that your world is computer-generated rather than physical. But how likely is this scenario? Bostrom and Chalmers each argue that it is moderately likely—neither very likely nor very unlikely. However, they adopt an unorthodox form of reasoning about self-location uncertainty. Our main contention here is that Bostrom’s and Chalmers’ premises, when combined with orthodoxy about self-location, yields instead the conclusion that you are almost certainly living in a simulation. We consider how (...)
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  50.  24
    Social Epistemology and the Digital Divide.Don Fallis - 2003 - CRPIT '03: Selected Papers From Conference on Computers and Philosophy 37:79-84.
    The digital divide refers to inequalities in access to information technology. One of the main reasons why the digital divide is an important issue is that access to information technology has a tremendous impact on people's ability to acquire knowledge. According to Alvin Goldman (1999), the project of social epistemology is to identify policies and practices that have good epistemic consequences. In this paper, I argue that this sort of approach to social epistemology can help us to decide on policies (...)
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