Our beliefs and opinions are shaped by others, making our social networks crucial in determining what we believe to be true. Sometimes this is for the good because our peers help us form a more accurate opinion. Sometimes it is for the worse because we are led astray. In this context, we address via agent-based computer simulations the extent to which patterns of connectivity within our social networks affect the likelihood that initially undecided agents in a network converge on a (...) true opinion following group deliberation. The model incorporates a fine-grained and realistic representation of belief and trust, and it allows agents to consult outside information sources. We study a wide range of network structures and provide a detailed statistical analysis concerning the exact contribution of various network metrics to collective competence. Our results highlight and explain the collective risks involved in an overly networked or partitioned society. Specifically, we find that 96% of the variation in collective competence across networks can be attributed to differences in amount of connectivity and clustering, which are negatively correlated with collective competence. A study of bandwagon or “group think” effects indicates that both connectivity and clustering increase the probability that the network, wholly or partly, locks into a false opinion. Our work is interestingly related to Gerhard Schurz’s work on meta-induction and can be seen as broadly addressing a practical limitation of his approach. (shrink)

In “Reliabilism Leveled” Jonathan Vogel (2000) provides a strong case against epistemic theories that stress the importance of tracking/sensitivity conditions. A tracking/sensitivity condition is to be understood as some version of the following counterfactual: (T) ~p oÆ ~Bp (T) says that s would not believe p, if p were false. Among other things, tracking is supposed to express the external relation that explains why some justified true beliefs are not knowledge. Champions of the condition include Robert Nozick (...) (1981) and, more recently, Keith DeRose (1995). To my knowledge, the earliest formulation of the counterfactual condition is found in Fred Dretske’s conclusive reasons condition (1971), which says, s would not have had the reason that she does for believing p, if p were false. Vogel contends that any such counterfactual condition on knowledge will render the theory of knowledge too strong. He believes that there is at least some possible reflective knowledge that cannot satisfy the counterfactual--viz., the possible knowledge that one does not believe falsely that p. The alleged impossibility of such reflective knowledge is taken by Vogel to be a decisive objection to the tracking theories advocated by Dretske, Nozick, DeRose1 and others. The criticism finds its roots in Vogel’s earlier work (1987), and recurs in papers by Ernest Sosa (2002, 1996). Sosa suggests that the externalist idea behind tracking is on target, but that Nozick’s counterfactual is a misbegotten regimentation of the idea. In its place Sosa offers his own counterfactual “safety” condition, which he feels properly captures the externalist idea. Sosa’s counterfactual is not the topic of this paper. I mention it only to point out that the criticism that constitutes the subject of my investigation is meant to do a lot of work. In Sosa’s 1 case the criticism is meant to motivate his own counterfactual analysis, and in Vogel’s case the criticism promises to be a silver bullet against a theory that has recently found renewed life in the work of Keith DeRose.. (shrink)

We study the learning power of iterated belief revision methods. Successful learning is understood as convergence to correct, i.e., true, beliefs. We focus on the issue of universality: whether or not a particular belief revision method is able to learn everything that in principle is learnable. We provide a general framework for interpreting belief revision policies as learning methods. We focus on three popular cases: conditioning, lexicographic revision, and minimal revision. Our main result is that conditioning and lexicographic revision can (...) drive a universal learning mechanism, provided that the observations include only and all true data, and provided that a non-standard, i.e., non-well-founded prior plausibility relation is allowed. We show that a standard, i.e., well-founded belief revision setting is in general too narrow to guarantee universality of any learning method based on belief revision. We also show that minimal revision is not universal. Finally, we consider situations in which observational errors may occur. Given a fairness condition, which says that only finitely many errors occur, and that every error is eventually corrected, we show that lexicographic revision is still universal in this setting, while the other two methods are not. (shrink)

Is it possible to gain knowledge about the real world based solely on experiences in virtual reality? According to one influential theory of knowledge, you cannot. Robert Nozick's truth-tracking theory requires that, in addition to a belief being true, it must also be sensitive to the truth. Yet beliefs formed in virtual reality are not sensitive: in the nearest possible world where P is false, you would have continued to believe that P. This is problematic because there (...) is increasing awareness from philosophers and technologists that virtual reality is an important way in which we can arrive at beliefs and knowledge about the world. Here I argue that a suitably modified version of Nozick's sensitivity condition is able to account for knowledge from virtual reality. (shrink)

We present Backward Clock, an original counterexample to Robert Nozick’s truth-tracking analysis of propositional knowledge, which works differently from other putative counterexamples and avoids objections to which they are vulnerable. We then argue that four ways of analysing knowledge in terms of safety, including Duncan Pritchard’s, cannot withstand Backward Clock either.

In a recent paper, Tristan Haze offers two examples that, he claims, are counterexamples to Nozick's Theory of Knowledge. Haze claims his examples work against Nozick's theory understood as relativized to belief forming methods M. We believe that they fail to be counterexamples to Nozick's theory. Since he aims the examples at tracking theories generally, we will also explain why they are not counterexamples to Dretske's Conclusive Reasons Theory of Knowledge.

I present two counterexamples to the recently back-in-favour truth-tracking account of knowledge: one involving a true belief resting on a counterfactually robust delusion, one involving a true belief acquired alongside a bunch of false beliefs. These counterexamples carry over to a recent modification of the theory due to Briggs and Nolan (2012), and seem invulnerable to a recent defence of the theory against known counterexamples, by Adams and Clarke (2005).

Cognitivist theories of democratic decision-making come in two flavours, which I label transparently and intransparently epistemic. Lafont’s deliberative theory of democracy has strengths in accoun...

Scientific realism is the optimistic view that modern science is on the right track: that the world really is the way our best scientific theories describe it. In his book, Stathis Psillos gives us a detailed and comprehensive study which restores the intuitive plausibility of scientific realism. We see that throughout the twentieth century, scientific realism has been challenged by philosophical positions from all angles: from reductive empiricism, to instrumentalism and to modern sceptical empiricism. _Scientific Realism_ explains that the history (...) of science does not undermine the arguments for scientific realism, but instead makes it reasonable to accept scientific realism as the best philosophical account of science, its empirical success, its progress and its practice. Anyone wishing to gain a deeper understanding of the state of modern science and why scientific realism is plausible, should read this book. (shrink)

The problem of the aggregation of consistent individual judgments on logically interconnected propositions into a collective judgment on the same propositions has recently drawn much attention. The dificulty lies in the fact that a seemingly reasonable aggregation procedure, such as propositionwise majority voting, cannot ensure an equally consistent collective outcome. The literature on judgment aggregation refers to such dilemmas as the discursive paradox. So far, three procedures have been proposed to overcome the paradox: the premise-based and conclusion-based procedures on the (...) one hand, and the merging approach on the other hand. In this paper we assume that the decision which the group is trying to reach is factually right or wrong. Hence, the question is how good the merging approach is in tracking the truth, and how it compares with the premise-based and conclusion-based procedures. (shrink)

One of the major problems that artificial intelligence needs to tackle is the combination of different and potentially conflicting sources of information. Examples are multi-sensor fusion, database integration and expert systems development. In this paper we are interested in the aggregation of propositional logic-based information, a problem recently addressed in the literature on information fusion. It has applications in multi-agent systems that aim at aggregating the distributed agent-based knowledge into an (ideally) unique set of propositions. We consider a group of (...) autonomous agents who individually hold a logically consistent set of propositions. Each set of propositions represents an agent’s beliefs on issues on which the group has to make a collective decision. To make the collective decision, several aggregation procedures have been proposed in the literature. Assuming that all propositions in question are factually right or wrong, we ask how good belief fusion is as a truth tracker. Will it single out the true set of propositions? And how does information fusion compare with other aggregation procedures? We address these questions in a probabilistic framework and show that information fusion does especially well for agents with a middling competence of hitting the truth of an individual proposition. (shrink)

Sherrilyn Roush defends a new theory of knowledge and evidence, based on the idea of "tracking" the truth, as the best approach to a wide range of questions about knowledge-related phenomena. The theory explains, for example, why scepticism is frustrating, why knowledge is power, and why better evidence makes you more likely to have knowledge. Tracking Truth provides a unification of the concepts of knowledge and evidence, and argues against traditional epistemological realist and anti-realist positions about (...) scientific theories and for a piecemeal approach based on a criterion of evidence, a position Roush calls "real anti-realism." Epistemologists and philosophers of science will recognize this as a significant original contribution. (shrink)

Sharon Street’s 2006 article “A Darwinian Dilemma for Realist Theories of Value” challenges the epistemological pretensions of the moral realist, of the nonnaturalist in particular. Given that “Evolutionary forces have played a tremendous role in shaping the content of human evaluative attitudes” – why should one suppose such attitudes and concomitant beliefs would track an independent moral reality? Especially since, on a nonnaturalist view, moral truth is causally inert. I abstract a logical skeleton of Street’s argument and, with its (...) aid, focus on problematic assumptions regarding the (a)causality of moral truth. It emerges that there are acquired causal powers that compensate for the intrinsic impotence of moral truth, as well as two distinct levels at which truth-tracking might occur. I argue that while evolution’s selective forces do not track moral truth, that does not imply individual organisms could not have evolved that capability. -/- . (shrink)

When ordinary people - mathematicians among them - take something to follow from something else, they are exposing the backbone of our self-ascribed ability to reason. Jody Azzouni investigates the connection between that ordinary notion of consequence and the formal analogues invented by logicians. One claim of the book is that, despite our apparent intuitive grasp of consequence, we do not introspect rules by which we reason, nor do we grasp the scope and range of the domain, as it were, (...) of our reasoning. This point is illustrated with a close analysis of a paradigmatic case of ordinary reasoning: mathematical proof. (shrink)

Scientific Realism is the optimistic view that modern science is on the right track: that the world really is the way our best scientific theories describe it to be. In his book, Stathis Psillos gives us a detailed and comprehensive study, which restores the intuitive plausibility of scientific realism. We see that throughout the twentieth century, scientific realism has been challenged by philosophical positions from all angles: from reductive empiricism, to instrumentalism and modern skeptical empiricism. Scientific Realism explains that the (...) history of science does not undermine the notion of scientific realism, and instead makes it reasonable to accept scientific as the best philosophical account of science, its empirical success, its progress and its practice. Anyone wishing to gain a deeper understanding of the state of modern science and why scientific realism is plausible, should read this book. (shrink)

When ordinary people--mathematicians among them--take something to follow from something else, they are exposing the backbone of our self-ascribed ability to reason. Jody Azzouni investigates the connection between that ordinary notion of consequence and the formal analogues invented by logicians. One claim of the book is that, despite our apparent intuitive grasp of consequence, we do not introspect rules by which we reason, nor do we grasp the scope and range of the domain, as it were, of our reasoning. This (...) point is illustrated with a close analysis of a paradigmatic case of ordinary reasoning: mathematical proof. (shrink)

We propose a new model for forming and revising beliefs about unknown probabilities. To go beyond what is known with certainty and represent the agent’s beliefs about probability, we consider a plausibility map, associating to each possible distribution a plausibility ranking. Beliefs are defined as in Belief Revision Theory, in terms of truth in the most plausible worlds. We consider two forms of conditioning or belief update, corresponding to the acquisition of two types of information: learning observable evidence obtained (...) by repeated sampling from the unknown distribution; and learning higher-order information about the distribution. The first changes only the plausibility map, but leaves the given set of possible distributions essentially unchanged; the second rules out some distributions, thus shrinking the set of possibilities, without changing their plausibility ordering.. We look at stability of beliefs under either of these types of learning, defining two related notions, as well as a measure of the verisimilitude of a given plausibility model. We prove a number of convergence results, showing how our agent’s beliefs track the true probability after repeated sampling, and how she eventually gains in a sense knowledge of that true probability. Finally, we sketch the contours of a dynamic doxastic logic for statistical learning. (shrink)

(No abstract is available for this citation).

Suppose a committee has to take a stand on a complex issue, where the decision presupposes answering a number of sub-questions. There is an agreement within the committee which sub-questions should be posed. All questions are of the ”yes or no?”-type and the main question is to be given the yes-answer if and only if each sub-question is answered with “yes”. Two different voting procedures can be used. On one procedure, the committee members vote on each sub-question and the voting (...) results then determine the committee’s conclusion on the main issue. This premise-based procedure (or pbp, for short) can be contrasted with the conclusion-based procedure (cbp), on which the members directly vote on the conclusion, with the vote of each member being guided by her views on the relevant sub-questions. The problem we want to examine concerns the relative advantages and disadvantages of the two procedures from the epistemic point of view. In some cases one can assume that the question before the committee has a right answer, which the committee is trying to reach. Is one of the two procedures better when it comes to tracking the truth? As it turns out, the answer to this query is not univocal: On the basis of Condorcet’s jury theorem we shall show that the premise-based procedure is clearly superior if we want to reach truth for the right reasons, i.e. without making any mistakes on the road to the conclusion. However, if the goal instead is to reach truth for whatever reasons, right or wrong, there will be special cases in which using the conclusion-based procedure turns out to be more reliable. But for the most part, the premise-based procedure will still retain its superiority. In this respect, our results disconfirm the tentative conjectures that have been put forward in Pettit and Rabinowicz (2001). (shrink)

The simplicity of a theory seems closely related to how well the theory summarizes individual data points. Think, for example, of classic curve-fitting. It is easy to get perfect data-fit with a ‘‘theory’’ that simply lists each point of data, but such a theory is maximally unsimple (for the data-fit). The simple theory suggests instead that there is one underlying curve that summarizes this data, and we usually prefer such a theory even at some expense in data-fit. In general, it (...) seems, theorizing involves looking for regularities or patterns in our experience, and such regularities are interesting to us because they summarize how our experience goes. We could list all the ravens we’ve encountered, and their colors, or we could summarize.. (shrink)

This paper takes as its starting point a decision to accept a particular commission for a piece of educational research which is subject to contractual restrictions. In the light of recent debate on the contentious politics and ethics of contractual research, it then addresses the problem of what might constitute an ethical defence, or critique, of such research and such contracts.

This paper takes as its starting point a decision to accept a particular commission for a piece of educational research which is subject to contractual restrictions. In the light of recent debate on the contentious politics and ethics of contractual research, it then addresses the problem of what might constitute an ethical defence, or critique, of such research and such contracts.

The aggregation of consistent individual judgments on logically interconnected propositions into a collective judgment on those propositions has recently drawn much attention. Seemingly reasonable aggregation procedures, such as propositionwise majority voting, cannot ensure an equally consistent collective conclusion. The literature on judgment aggregation refers to that problem as the discursive dilemma. In this paper, we motivate that many groups do not only want to reach a factually right conclusion, but also want to correctly evaluate the reasons for that conclusion. In (...) other words, we address the problem of tracking the true situation instead of merely selecting the right outcome. We set up a probabilistic model analogous to Bovens and Rabinowicz (2006) and compare several aggregation procedures by means of theoretical results, numerical simulations and practical considerations. Among them are the premise-based, the situation-based and the distance-based procedure. Our findings confirm the conjecture in Hartmann, Pigozzi and Sprenger (2008) that the premise-based procedure is a crude, but reliable and sometimes even optimal form of judgment aggregation. (shrink)

In Tracking Truth I undertook a broader project than is typical today toward questions about knowledge, evidence, and scientific realism. The range of knowledge phenomena is much wider than the kind of homely examples—such as ‘‘She has a bee in her bonnet’’—that are often the fare in discussions of knowledge. Scientists have knowledge gained in sophisticated and deliberate ways, and non-human animals have reflexive and rudimentary epistemic achievements that we can easily slip into calling ‘‘knowledge.’’ What is it (...) about knowledge that makes it natural for us to use the same word in cases that are so vastly different? How is it possible for knowledge to have evolved? What is it about knowledge that it should enhance our power over nature, as Francis Bacon observed? What is it about evidence and knowledge that makes you more likely to have the latter when you have the former? Specialization is necessary to progress, but the division of labor it requires has allowed such questions to fall through the gaps between discussions. These gaps are opportunities. Sometimes newly discovered problems can bring new and better answers even to old questions. The questions I have asked above are ‘‘Why?’’ questions expressed as (apparently) Socratic ‘‘What is?’’ questions, and that is the approach taken in the first five chapters of this book, to offer explanations of familiar phenomena on the basis of rigorous definitions of knowledge and evidence. One might object that this is an old, not a new, style of answer, and one that I ought to be educated enough to reject. Many have thought the project of giving necessary and sufficient conditions for knowledge was in its death rattle long ago. The most common argument for this conclusion is an empirical one, that no such attempt has ever been successful in giving the right answer for all examples. And when one asks, as one must, what the ‘‘right’’ answer would be answering to anyway, the project can look even more depressing. But even if there is a clear.... (shrink)

Reply to Goldman I would like to thank Alvin for a spirited, and gentlemanly, debate we’ve had on these issues, which is extended further here. Alvin is exactly right that if we make his assumption about maximum specificity and deduceability (which I have doubts about), then on my view of knowledge Sphere Guy doesn’t know there’s a sphere in front of him. This may sound silly when we focus on his tactile access to the sphere in the actual world, but (...) if we take a broader view we see that there is more at stake than this. Contrary to Alvin’s impression, methods are not at all excised from my view of knowledge. My theory of how to judge whether someone knows requires us to consider everything (probable) that is and would be responsible for the fact that the person believes or not, whether these occur in his head or in the world, which the formulation in terms of probability helps to make very clear. (See Chapter 3.) Ironically, my refusal to relativize to method has us taking into consideration more facts about the subject’s method than Alvin’s criteria do, for my view takes into account, as appropriate, what process the person would have used and has a tendency to use, and not just the properties of the one he happened in fact to use. When the fact that a method was used by a subject in coming to belief in p is independent of the truth of p, which is actually most of the time in our lives, the conditions of application of the variation condition insure that we evaluate the subject by considering only what he would do and how he would fare in his beliefs were he to use that method he actually used. So, under that condition, my view agrees with Alvin, and Nozick also. But when whether a subject used that method is not independent of the truth value of p, then the variation condition in my view says we must consider in addition the subject’s resulting beliefs in all probable scenarios where he is such that he might well.. (shrink)

A committee has to address a complex question, the answer to which requires answering several sub-questions. Two different voting procedures can be used. On one procedure, the committee members vote on each sub-question and the voting results then are used as premises for the committee’s conclusion on the main issue. This premise-based procedure can be contrasted with the conclusion-based procedure. On that procedure, the members directly vote on the conclusion, with the vote of each member being guided by her views (...) on the relevant sub-questions. These procedures are by no means equivalent, which has been pointed out in legal theory in connection with jury votes. There may be a majority of voters supporting each premise, but if these majorities do not significantly overlap, there will be a majority against the conclusion. Pettit connects the choice between the two procedures with general political theory, in particular, with the discussion of deliberative democracy. However, the problem we want to examine concerns the relative advantages and disadvantages of the two procedures from the epistemic point of view. In some cases one can assume that the question before the committee has the right answer. In cases like this, is one of the two procedures better when it comes to tracking the truth? As it turns out, the answer to this query is not univocal. On the basis of Condorcet’s jury theorem, we show that the premise-based procedure is clearly superior if the objective is reach truth for the right reasons, i.e. without making any mistakes on the way. However, if the goal instead is to reach truth for whatever reasons, right or wrong, there will be cases in which using the conclusion-based procedure turns out to be more reliable, even though, for the most part, the premise-based procedure will retain its superiority. Our results partly confirm and partly disconfirm the tentative conjectures that have been put forward in Pettit and Rabinowicz. (shrink)

In this paper, we will discuss Peter van Inwagen’s contribution to the epistemological debate about revealed peer disagreement. Roughly, this debate focuses on situations in which at least two participants disagree on a certain proposition based on the same evidence. This leads to the problem of how one should react rationally when peer disagreement is revealed. Van Inwagen, as we will show, discusses four possible reactions, all of which he rejects as unsatisfying. Our proposal will be to point to hidden (...) assumptions in van Inwagen’s reasoning and ask whether he is willing to reject at least one of these to get rid of the problem. In short, our thesis amounts to the following: Of the two epistemological claims, which we call “Weak” and “Full-blown Fallibilism”, van Inwagen cannot simultaneously accept the first and reject the latter, while this is what he seems to suggest. Revealing this potential dilemma for van Inwagen’s position will lead to a more detailed discussion of how “rationality”, “truth”, “evidence” and “justification” interrelate and how a closer look at their relation might help solving the puzzle of revealed peer disagreement. (shrink)

Tracking theories see knowledge as a relation between a subject’s belief and the truth, where the former is responsive to the latter. This relationship involves causation in virtue of a sensitivity condition, which is constrained by an adherence condition. The result is what I call a stable causal relationship between a fact and a subject’s belief in that fact. I argue that when we apprehend the precise role of causation in the theory, previously obscured problems pour out. This (...) paper presents thirteen distinct and original counterexamples to Nozick’s tracking theory—many of which also constitute problems for more recent tracking theories. I begin by discussing how tracking relates to causation: Nozick invokes causation through conditions similar to those of Lewisian causal dependence. As a result, when causal dependence is not necessary for causation, Nozick fails to identify knowledge. I then address the inability of causation to capture epistemically important concepts, such as justification and truth. I conclude by discussing the underlying asymmetries between causation and knowledge that undermine any attempt to reduce knowledge to a purely metaphysical relation. (shrink)

I argue that our general disposition to make moral judgments and our core moral intuitions are likely the product of social selection—a kind of gene–culture coevolution driven by the enforcement of collectively agreed-upon rules. Social selection could potentially track mind-independent moral truth by a process that I term realist social selection: our ancestors could have acquired moral knowledge via reason and enforced rules based on that knowledge, thereby creating selection pressures that drove the evolution of our moral psychology. Given (...) anthropological evidence that early humans designed rules with the conscious aim of preserving individual autonomy and advancing their collective interests, the theory of realist social selection appears to be attractive for moral realists. The goal of evolutionary debunking arguments should be to show not that our moral beliefs are the product of natural selection, but that realist social selection did not occur. (shrink)

In the form of inference known as inference to the best explanation there are various ways to characterise what is meant by the best explanation. This paper considers a number of such characterisations including several based on confirmation measures and several based on coherence measures. The goal is to find a measure which adequately captures what is meant by 'best' and which also yields the truth with a high degree of probability. Computer simulations are used to show that the (...) overlap coherence measure achieves this goal, enabling the true explanation to be identified almost as often as an approach which simply selects the most probable explanation. Further advantages to this approach are also considered in the case where there is uncertainty in the prior probability distribution. (shrink)

This book is a comprehensive defence of a modified Nozickian tracking account of knowledge. The account is presented as an analysis of knowledge, rather than justification. Roush allows that a tracking analysis of justification may be possible. But she denies that justification is required for knowledge. Her view is externalist, but not reliabilist.

In relevant logics, necessary truths need not imply each other. In justification logic, necessary truths need not all be justified by the same reason. There is an affinity to these two approaches that suggests their pairing will provide good logics for tracking reasons in a fine-grained way. In this paper, I will show how to extend relevant logics with some of the basic operators of justification logic in order to track justifications or reasons. I will define and study three (...) kinds of frames for these logics. For the first kind of frame, I show soundness and highlight a difficulty in proving completeness. This motivates two alternative kinds of frames, with respect to which completeness results are obtained. Axioms to strengthen the justification logic portions of these logics are considered. I close by developing an analogy between the dot operator of justification logic and theory fusion in relevant logics. (shrink)

Humans look at, think about, and manipulate things with tools.1 Some tools are largely pragmatic in nature, and they have a long history in our lineage, but more recently, humans have innovated tools for keeping track of features of the environment. Epistemic tracking tools (as I shall dub them) allow us to think, perceive and manipulate the world with a precision that we would otherwise lack. These epistemic tracking tools (henceforth ETTs) will be the focus of this chapter. (...) ETTs track particular environmental variables examples of such tools include maps, compasses telescopes, sextants, and so on. There are also abstract systems of representation that track numbers, sets, sounds, and phonemes, and collectively as sets of propositions and equations can track physical phenomena, or perhaps even the truth. This chapter will focus on providing an account of the evolutionary platform for ETTs, look at some examples of ETTs in action and some of the consequences of the account for the extended knowledge literature. (shrink)

In “The Backward Clock, Truth-Tracking, and Safety”, Neil Sinhababu and I gave Backward Clock, a counterexample to Robert Nozick’s truth-tracking analysis of knowledge. In “Knowledge as Fact-Tracking True Belief”, Fred Adams, John Barker and Murray Clarke propose that a true belief constitutes knowledge if and only if it is based on reasons that are sensitive to the fact that makes it true, that is, reasons that wouldn’t obtain if the belief weren’t true. They argue that (...) their analysis evades Backward Clock. Here I show that it doesn’t. Backward Clock likewise shows their analysis to be too weak. The broader lesson seems to be that Backward Clock tells us the time is up for purely modal analyses of knowledge. (shrink)

A basic challenge to naturalistic moral realism is that, even if moral properties existed, there would be no way to naturalistically represent or track them. Here, the basic structure for a tracking account of moral epistemology is given in empirically respectable terms, based on a eudaimonist conception of morality. The goal is to show how this form of moral realism can be seen as consistent with the details of evolutionary biology as well as being amenable to the most current (...) understanding of representationalist or correspondence theories of truth. (shrink)

[Peter Lipton] From a reliabilist point of view, our inferential practices make us into instruments for determining the truth value of hypotheses where, like all instruments, reliability is a central virtue. I apply this perspective to second-order inductions, the inductive assessments of inductive practices. Such assessments are extremely common, for example whenever we test the reliability of our instruments or our informants. Nevertheless, the inductive assessment of induction has had a bad name ever since David Hume maintained that any (...) attempt to justify induction by means of an inductive argument must beg the question. I will consider how the inductive justification of induction fares from the reliabilist point of view. I will also consider two other well-known arguments that can be construed as inductive assessments of induction. One is the miracle argument, according to which the truth of scientific theories should be inferred as the best explanation of their predictive success; the other is the disaster argument, according to which we should infer that all present and future theories are false on the grounds that all past theories have been found to be false. \\\ [John Worrall] Science seems in some ways to have been remarkably successful. What does this success tell us about the epistemological status of current scientific claims? Peter Lipton considers various meta-inductive arguments each of which start from premises about science's 'track record'. I show that his endorsements of the 'strongest' of these are, on analysis, remarkably weak. I argue that this is a reflection of difficulties within the general epistemological framework that he adopts-that of reliabilism. Finally, I briefly outline the quite different approach that I take to this issue, in the process responding to Lipton's criticisms of the 'pessimistic meta-induction'. (shrink)