It is a popular view thatpractical deliberation excludes foreknowledge of one's choice. Wolfgang Spohn and Isaac Levi have argued that not even a purely probabilistic self-predictionis available to thedeliberator, if one takes subjective probabilities to be conceptually linked to betting rates. It makes no sense to have a betting rate for an option, for one's willingness to bet on the option depends on the net gain from the bet, in combination with the option's antecedent utility, rather than on the offered (...) odds. And even apart from this consideration, assigning probabilities to the options among which one is choosing is futile since such probabilities could be of no possible use in choice. The paper subjects these arguments to critical examination and suggests that, appearances notwithstanding, practical deliberation need not crowd outself-prediction. (shrink)

This chapter seeks to recover an approach to consciousness from a general theory of brain function, namely the prediction error minimization theory. The way this theory applies to mental and developmental disorder demonstrates its relevance to consciousness. The resulting view is discussed in relation to a contemporary theory of consciousness, namely the idea that conscious perception depends on Bayesian metacognition; this theory is also supported by considerations of psychopathology. This Bayesian theory is first disconnected from the higher-order thought theory, and (...) then, via a prediction error conception of action, connected instead to the global neuronal workspace theory. Considerations of mental and developmental disorder therefore show that a very general theory of brain function is relevant to explaining the structure of conscious perception; furthermore, this theory can subsume and unify two contemporary approaches to consciousness, in a move that seeks to elucidate the fundamental mechanism for selection of representational content into consciousness. (shrink)

Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks to (...) predict whether a person is diabetic or not. The criterion was to minimize the error function in neural network training using a neural network model. After training the ANN model, the average error function of the neural network was equal to 0.01 and the accuracy of the prediction of whether a person is diabetics or not was 87.3%. (shrink)

an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the (...) key is the concept of overfitting. We float the hypothesis that accommodation is a defective methodology only when the methods used to accommodate the data fail to guard against the risk of overfitting. We connect our analysis with the proposals that other philosophers have made. We also discuss its bearing on the conflict between instrumentalism and scientific realism. Introduction Predictivisms—a taxonomy Observations Formulating the problem What might Annie be doing wrong? Solutions Observations explained Mayo on severe tests The miracle argument and scientific realism Concluding comments. (shrink)

To succeed, political science usually requires either prediction or contextual historical work. Both of these methods favor explanations that are narrow-scope, applying to only one or a few cases. Because of the difficulty of prediction, the main focus of political science should often be contextual historical work. These epistemological conclusions follow from the ubiquity of causal fragility, under-determination, and noise. They tell against several practices that are widespread in the discipline: wide-scope retrospective testing, such as much large-n statistical work; lack (...) of emphasis on prediction; and resources devoted to ‘pure theory’ divorced from frequent empirical application. I illustrate, via Donatella della Porta’s work on political violence, the important role that is still left for theory. I conclude by assessing the scope for political science to offer policy advice. (shrink)

Although prediction has been largely absent from discussions of explanation for the past 40 years, theories of explanation can gain much from a reintroduction. I review the history that divorced prediction from explanation, examine the proliferation of models of explanation that followed, and argue that accounts of explanation have been impoverished by the neglect of prediction. Instead of a revival of the symmetry thesis, I suggest that explanation should be understood as a cognitive tool that assists us in generating new (...) predictions. This view of explanation and prediction clarifies what makes an explanation scientific and why inference to the best explanation makes sense in science. *Received August 2009; revised September 2009. †To contact the author, please write to: Department of Philosophy, University of Tennessee, 801 McClung Tower, Knoxville, TN 37920‐0480; e‐mail: [email protected]. (shrink)

Shared activity is often simply willed into existence by individuals. This poses a problem. Philosophical reflection suggests that shared activity involves a distinctive, interlocking structure of intentions. But it is not obvious how one can form the intention necessary for shared activity without settling what fellow participants will do and thereby compromising their agency and autonomy. One response to this problem suggests that an individual can have the requisite intention if she makes the appropriate predictions about fellow participants. I argue (...) that implementing this predictive strategy risks derailing practical reasoning and preventing one from forming the intention. My alternative proposal for reconciling shared activity with autonomy appeals to the idea of acting directly on another's intention. In particular, I appeal to the entitlement one sometimes has to another's practical judgment, and the corresponding authority the other sometimes has to settle what one is to do. (shrink)

How is it that thoroughly physical material beings such as ourselves can think, dream, feel, create and understand ideas, theories and concepts? How does mere matter give rise to all these non-material mental states, including consciousness itself? An answer to this central question of our existence is emerging at the busy intersection of neuroscience, psychology, artificial intelligence, and robotics.In this groundbreaking work, philosopher and cognitive scientist Andy Clark explores exciting new theories from these fields that reveal minds like ours to (...) be prediction machines - devices that have evolved to anticipate the incoming streams of sensory stimulation before they arrive. These predictions then initiate actions that structure our worlds and alter the very things we need to engage and predict. Clark takes us on a journey in discovering the circular causal flows and the self-structuring of the environment that define "the predictive brain." What emerges is a bold, new, cutting-edge vision that reveals the brain as our driving force in the daily surf through the waves of sensory stimulation. (shrink)

1. Introduction 2. Reward-Guided Decision Making 3. Content in the Model 4. How to Deflate a Metarepresentational Reading Proust and Carruthers on metacognitive feelings 5. A Deflationary Treatment of RPEs? 5.1 Dispensing with prediction errors 5.2 What is use of the RPE focused on? 5.3 Alternative explanations—worldly correlates 5.4 Contrast cases 6. Conclusion Appendix: Temporal Difference Learning Algorithms.

A widely endorsed thesis in the philosophy of science holds that if evidence for a hypothesis was not known when the hypothesis was proposed, then that evidence confirms the hypothesis more strongly than would otherwise be the case. The thesis has been thought to be inconsistent with Bayesian confirmation theory, but the arguments offered for that view are fallacious. This paper shows how the special value of prediction can in fact be given Bayesian explanation. The explanation involves consideration of the (...) reliability of the method by which the hypothesis was discovered, and thus reveals an intimate connection between the 'logic of discovery' and confirmation theory. (shrink)

Gregor Betz explores the following questions: Where are the limits of economics, in particular the limits of economic foreknowledge? Are macroeconomic forecasts credible predictions or mere prophecies and what would this imply for the way economic policy decisions are taken? Is rational economic decision making possible without forecasting at all?

This paper examines the famous doctrine that independent prediction garners more support than accommodation. The standard arguments for the doctrine are found to be invalid, and a more realistic position is put forward, that whether evidence supports or not a hypothesis depends on the prior probability of the hypothesis, and is independent of whether it was proposed before or after the evidence. This position is implicit in the subjective Bayesian theory of confirmation, and the paper ends with a brief account (...) of this theory, and answer to the principal objections to it. (shrink)

Are predictions about how one will freely and intentionally behave in the future ever relevant to how one ought to behave? There is good reason to think they are. As imperfect agents, we have responsibilities of self-management, which seem to require that we take account of the predictable ways we're liable to go wrong. I defend this conclusion against certain objections to the effect that incorporating predictions concerning one's voluntary conduct into one's practical reasoning amounts to evading responsibility for that (...) conduct. There is, however, some truth to this sort of objection. To understand the legitimate role of self-prediction in practical reasoning, we need to distinguish instances of coping responsibly with an anticipated failure to behave as one ought, on the one hand, from mere acquiescence in one's flaws, on the other. I argue that, to draw this distinction, we must recognize certain limits on the use of self-prediction as a ground of choice. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

Predictive success as an aim of science -- On the very possibility of prediction in the social sciences -- Empirical facts about social prediction: its mode, object and performance -- Understanding poor forecast performance.

Should we insist on prediction, i.e. on correctly forecasting the future? Or can we rest content with accommodation, i.e. empirical success only with respect to the past? I apply general considerations about this issue to the case of economics. In particular, I examine various ways in which mere accommodation can be sufficient, in order to see whether those ways apply to economics. Two conclusions result. First, an entanglement thesis: the need for prediction is entangled with the methodological role of orthodox (...) economic theory. Second, a conditional predictivism: if we are not committed to orthodox economic theory, then we should demand prediction rather than accommodation – against most current practice. (shrink)

This essay aims to provide a rigorous foundation for Gilboa's, Postlewaite's, Samuelson's and Schmeidler's (GPSS's) account of the constitution of models and the role of models in explanation and prediction. Although I shall offer some criticisms, my goal is to sketch analyses of explanations and models that complement GPSS's distinctions between the uses of models to explain, prescribe, predict, and explore the consequences of theories.

We consider an extension of signaling games to the case of prediction, where one agent perceives the current state of the world and sends a signal. The second agent perceives this signal, and makes a prediction about the next state of the world. We suggest that such games may be the basis of a model for the evolution of successful theorizing about the world.

Here we briefly review the concept of "prediction" within the context of classical relativity theory. We prove a theorem asserting that one may predict one's own future only in a closed universe. We then question whether prediction is possible at all (even in closed universes). We note that interest in prediction has stemmed from considering the epistemological predicament of the observer. We argue that the definitions of prediction found thus far in the literature do not fully appreciate this predicament. We (...) propose a more adequate alternative and show that, under this definition, prediction is essentially impossible in general relativity. (shrink)

Drawing on recent findings in the cognitive and neurosciences, this article discusses how people manage to predict each other’s actions, which is fundamental for joint action. We explore how a common coding of perceived and performed actions may allow actors to predict the what, when, and where of others’ actions. The “what” aspect refers to predictions about the kind of action the other will perform and to the intention that drives the action. The “when” aspect is critical for all joint (...) actions requiring close temporal coordination. The “where” aspect is important for the online coordination of actions because actors need to effectively distribute a common space. We argue that although common coding of perceived and performed actions alone is not sufficient to enable one to engage in joint action, it provides a representational platform for integrating the actions of self and other. The final part of the paper considers links between lower‐level processes like action simulation and higher‐level processes like verbal communication and mental state attribution that have previously been at the focus of joint action research. (shrink)

In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions (...) can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone. (shrink)

The debate about the relative epistemic weights carried in favour of a theory by predictions of new phenomena as opposed to accommodations of already known phenomena has a long history. We readdress the issue through a detailed re-examination of a particular historical case that has often been discussed in connection with it—that of Mendeleev and the prediction by his periodic law of the three ‘new’ elements, gallium, scandium and germanium. We find little support for the standard story that these predictive (...) successes were outstandingly important in the success of Mendeleev's scheme. Accommodations played an equal role—notably that of argon, the first of the ‘noble gases’ to be discovered; and the methodological situation in this chemical example turns out to be in interesting ways different from that in other cases—invariably from physics—that have been discussed in this connection. The historical episode when accurately analysed provides support for a different account of the relative weight of prediction and accommodation—one that is further articulated here. (shrink)

How might advanced neuroscience—in which perfect neuro-predictions are possible—interact with ordinary judgments of free will? We propose that peoples' intuitive ideas about indeterminist free will are both imported into and intrude into their representation of neuroscientific scenarios and present six experiments demonstrating intrusion and importing effects in the context of scenarios depicting perfect neuro-prediction. In light of our findings, we suggest that the intuitive commitment to indeterminist free will may be resilient in the face of scientific evidence against such free (...) will. (shrink)

This paper reviews the recent (post-DSM) history of subjective and semi-structured methods of psychiatric diagnosis, as well as evidence for the superiority of structured and computer-aided diagnostic techniques. While there is evidence that certain forms of therapy are effective for alleviating the psychiatric suffering, distress, and dysfunction associated with certain psychiatric disorders, this paper addresses some of the difficult methodological and ethical challenges of evaluating the effectiveness of therapy.

How might advanced neuroscience—in which perfect neuro-predictions are possible—interact with ordinary judgments of free will? We propose that peoples' intuitive ideas about indeterminist free will are both imported into and intrude into their representation of neuroscientific scenarios and present six experiments demonstrating intrusion and importing effects in the context of scenarios depicting perfect neuro-prediction. In light of our findings, we suggest that the intuitive commitment to indeterminist free will may be resilient in the face of scientific evidence against such free (...) will. (shrink)

McRae, Brown and Elman argue against the view that events are structured as frequently‐occurring sequences of world stimuli. They underline the importance of temporal structure defining event types and advance a more complex temporal structure, which allows for some variance in the component elements.

The use of machine learning instead of traditional models in neuroscience raises significant questions about the epistemic benefits of the newer methods. I draw on the literature on model intelligibility in the philosophy of science to offer some benchmarks for the interpretability of artificial neural networks used as a predictive tool in neuroscience. Following two case studies on the use of ANN’s to model motor cortex and the visual system, I argue that the benefit of providing the scientist with understanding (...) of the brain trades off against the predictive accuracy of the models. This trade-off between prediction and understanding is better explained by a non-factivist account of scientific understanding. (shrink)

In the absence of a fundamental theory that precisely predicts values for observable parameters, anthropic reasoning attempts to constrain probability distributions over those parameters in order to facilitate the extraction of testable predictions. The utility of this approach has been vigorously debated of late, particularly in light of theories that claim we live in a multiverse, where parameters may take differing values in regions lying outside our observable horizon. Within this cosmological framework, we investigate the efficacy of top-down anthropic reasoning (...) based on the weak anthropic principle. We argue contrary to recent claims that it is not clear one can either dispense with notions of typicality altogether or presume typicality, in comparing resulting probability distributions with observations. We show in a concrete, top-down setting related to dark matter, that assumptions about typicality can dramatically affect predictions, thereby providing a guide to how errors in reasoning regarding typicality translate to errors in the assessment of predictive power. We conjecture that this dependence on typicality is an integral feature of anthropic reasoning in broader cosmological contexts, and argue in favour of the explicit inclusion of measures of typicality in schemes invoking anthropic reasoning, with a view to extracting predictions from multiverse scenarios. (shrink)

This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses (...) are commonly seen as necessary in order to identify aggregate-level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds of prediction necessary and possible in spatial planning of urban development. Finally, the political implications of positions within theory of science rejecting the possibility of predictions about social phenomena are addressed. (shrink)

When we make a prediction we select, among the conceivable future descriptions of the world, those that appear to us to be most plausible. We capture this by means of two binary relations, ≺c and ≺p: if t1 and t2 are points in time, we interpret t1 ≺ct2 as sayingthat t2 is in the conceivable future of t1, while t1 ≺pt2 is interpreted to mean that t2 isin the predicted future of t1. Within a branching-time framework we propose the following (...) notion of “consistency of prediction”. Suppose that at t1 some future moment t2 is predicted to occur, then every moment t on the unique path from t1 to t2 should also be predicted at t1 and the prediction of t2 should continue to hold at every such t. A sound and complete axiomatization is provided. (shrink)

We identify a number of principles with respect to prediction that, we argue, underpin adult language comprehension: (a) comprehension consists in realizing a mapping between the unfolding sentence and the event representation corresponding to the real‐world event being described; (b) the realization of this mapping manifests as the ability to predict both how the language will unfold, and how the real‐world event would unfold if it were being experienced directly; (c) concurrent linguistic and nonlinguistic inputs, and the prior internal states (...) of the system, each drive the predictive process; (d) the representation of prior internal states across a representational substrate common to the linguistic and nonlinguistic domains enables the predictive process to operate over variable time frames and variable levels of representational abstraction. We review empirical data exemplifying the operation of these principles and discuss the relationship between prediction, event structure, thematic role assignment, and incrementality. (shrink)

We often need to have beliefs about things on which we are not experts. Luckily, we often have access to expert judgements on such topics. But how should we form our beliefs on the basis of expert opinion when experts conflict in their judgments? This is the core of the novice/2-expert problem in social epistemology. A closely related question is important in the context of policy making: how should a policy maker use expert judgments when making policy in domains in (...) which she is not herself an expert? This question is more complex, given the messy and strategic nature of politics. In this paper we argue that the prediction with expert advice framework from machine learning provides helpful tools for addressing these problems. We outline conditions under which we should expert PWEA to be helpful and those under which we should not expect these methods to perform well. (shrink)

Considers that intuitive predictions follow a judgmental heuristic-representativeness. By this heuristic, people predict the outcome that appears most representative of the evidence. Consequently, intuitive predictions are insensitive to the reliability of the evidence or to the prior probability of the outcome, in violation of the logic of statistical prediction. The hypothesis that people predict by representativeness was supported in a series of studies with both naive and sophisticated university students. The ranking of outcomes by likelihood coincided with the ranking by (...) representativeness, and Ss erroneously predicted rare events and extreme values if these happened to be representative. The experience of unjustified confidence in predictions and the prevalence of fallacious intuitions concerning statistical regression are traced to the representativeness heuristic. (shrink)

Psychiatric diagnosis and prognosis is fraught with important philosophical and conceptual problems. This chapter focuses on some epistemological issues and moral issues that arise in contemporary psychiatric practice. It examines various clinical and actuarial techniques for psychiatric diagnosis, ordered very loosely in terms of how "structured" or "automated" they are. The chapter makes the case for assessing psychiatric treatments with controlled experiments, raises several epistemological dangers that arise from relying on uncontrolled investigations, and considers some of the unique methodological and (...) ethical issues that arise when trying to assess talk therapy. (shrink)

An original study of the philosophical problems associated with inductive reasoning. Like most of the main questions in epistemology, the classical problem of induction arises from doubts about a mode of inference used to justify some of our most familiar and pervasive beliefs. The experience of each individual is limited and fragmentary, yet the scope of our beliefs is much wider; and it is the relation between belief and experience, in particular the belief that the future will in some respects (...) resemble the past and the unobserved the observed, which forms the subject of this book. Dr Blackburn's first aim is to state the problem of induction properly, to show that there does exist a genuine problem immune to the solutions in vogue at present, yet no tin principle insoluble. He gives an extended and original account of the concept of a reason and goes on to discuss prediction. In the end Dr Blackburn produces a rationale for belief in certain short-term predictions based on his reinterpretation of the classical principle of indifference. He claims that a justification for induction can be found along the lines he has suggested and must indeed be found there if anywhere. (shrink)

The two-factor theory (Davies, Coltheart, Langdon & Breen 2001; Coltheart 2007; Coltheart, Menzies & Sutton 2010) is an influential account of delusion formation. According to the theory, there are two distinct factors that are causally responsible for delusion formation. The first factor is supposed to explain the content of the delusion, while the second factor is supposed to explain why the delusion is adopted and maintained. Recently, another remarkable account of delusion formation has been proposed, in which the notion of (...) “prediction error” plays the central role (Fletcher & Frith 2009; Corlett, Krystal, Taylor & Fletcher 2009; Corlett, Taylor, Wang, Fletcher & Krystal 2010). According to this account, the prediction-error theory, delusions are formed in response to aberrant prediction-error signals, those signals that indicate a mismatch between expectation and actual experience. -/- In this chapter, we examine the relationship between the two-factor theory and the prediction-error theory in some detail. Our view is that the prediction-error theory does not have to be understood as a rival to the two-factor theory. We do not deny that there are some important differences between them. However, those differences are not as significant as they have been presented in the literature. Moreover, the core ideas of the prediction-error theory may be incorporated into the two- factor framework. For instance, the aberrant prediction-error signal that is posited by prediction-error theorists can be (or underlie) the first factor contributing to the formation of some delusions, and help explain the content of those delusions. Alternatively, the aberrant prediction-error signal can be (or underlie) the second factor, and help explain why the delusion is adopted and maintained. (shrink)

Two studies examined the allegiance bias – the rendering of biased predictions by individuals who are psychologically invested in a desired outcome. In Study 1, fans of either Notre Dame or University of Miami college football read information about an upcoming game between the two teams and then explained a hypothetical victory either by Notre Dame or Miami. Although explaining a hypothetical victory biased the judgments of controls (i.e., fans of neither team) in the direction of the team explained, the (...) judgments of Notre Dame and Miami fans favored their team in every explanation condition. In addition, fans exhibited biased recall for facts favoring their own teams and this biased recall predicted fans’ judgments regarding the upcoming game. Study 2 attempted to specify a debiasing technique that might attenuate the allegiance bias. Indiana University basketball fans described what they thought might happen in an upcoming game between Indiana and the University of Michigan while anticipating having a discussion about the game (i.e., predecisional accountability) with either an Indiana fan, a Michigan fan, or a fan of unknown allegiance. As predicted, anticipating a discussion with a fan of unknown allegiance engendered game predictions that were the least biased in favor of an Indiana victory. Implications for social explanation and prediction research are discussed. (shrink)

Both children and adults predict the content of upcoming language, suggesting that prediction is useful for learning as well as processing. We present an alternative model which can explain prediction behaviour as a by-product of language learning. We suggest that a consideration of language acquisition places important constraints on Pickering & Garrod's (P&G's) theory.

In earlier work ( Cleland [2001] , [2002]), I sketched an account of the structure and justification of ‘prototypical’ historical natural science that distinguishes it from ‘classical’ experimental science. This article expands upon this work, focusing upon the close connection between explanation and justification in the historical natural sciences. I argue that confirmation and disconfirmation in these fields depends primarily upon the explanatory (versus predictive or retrodictive) success or failure of hypotheses vis-à-vis empirical evidence. The account of historical explanation that (...) I develop is a version of common cause explanation. Common cause explanation has long been vindicated by appealing to the principle of the common cause. Many philosophers of science (e.g., Sober and Tucker) find this principle problematic, however, because they believe that it is either purely methodological or strictly metaphysical. I defend a third possibility: the principle of the common cause derives its justification from a physically pervasive time asymmetry of causation (a.k.a. the asymmetry of overdetermination). I argue that explicating the principle of the common cause in terms of the asymmetry of overdetermination illuminates some otherwise puzzling features of the practices of historical natural scientists. (shrink)

What is medicine? One obvious answer in the context of the contemporary clinical tradition is that medicine is the process of curing sick people. However, this “curative thesis” is not satisfactory, even when “cure” is defined generously and even when exceptions such as cosmetic surgery are set aside. Historian of medicine Roy Porter argues that the position of medicine in society has had, and still has, little to do with its ability to make people better. Moreover, the efficacy of medicine (...) for improving population health has been famously doubted by historians and epidemiologists. The curative thesis demands that we have mostly been stupid, duped, or staggeringly hopeful, given that medicine has not until recently offered more than a handful of effective cures. I suggest, in this article, that the core medical competence is neither to cure, nor to prevent, disease, but to understand and to predict it. I argue that this approach does a better job than the curative thesis at explaining why not all medicine is concerned with curative efforts and that it enjoys historical support from the ancient entanglement of prophecy and medicine and from the fact that medicine thrived for centuries with almost no effective cures and continues to thrive today in various forms that are mostly without curative efficacy. I suggest that this approach grounds a fairer approach to alternative, traditional, and other medical practices, as well as some fresh lessons for the development of mainstream medicine. (shrink)

Predictive processing is an increasingly popular approach to cognition, perception and action. It says that the brain is essentially a hierarchical prediction machine. It is typically construed in a representationalist and inferentialist fashion so that the brain makes contentful inferences on the basis of representational models. In this paper, I argue that the predictive processing framework is inconsistent with this epistemic position. In particular, I argue that the combination of hierarchical modeling, contentful inferentialism and representationalism entail an internal inconsistency. Specifically, (...) for a particular set of states, there will be both a representation requirement and not. Yet a system cannot both be required to represent a certain set of states and not be required to represent those states. Due to this contradiction, I propose to reject the standard view. I suggest that predictive processing is best interpreted in terms of reliable covariation instead, entailing an instrumentalist approach to the statistical machinery. (shrink)

The paper presents a further articulation and defence of the view on prediction and accommodation that I have proposed earlier. It operates by analysing two accounts of the issue-by Patrick Maher and by Marc Lange-that, at least at first sight, appear to be rivals to my own. Maher claims that the time-order of theory and evidence may be important in terms of degree of confirmation, while that claim is explicitly denied in my account. I argue, however, that when his account (...) is analysed, Maher reveals no scientifically significant way in which the time-order counts, and that indeed his view is in the end best regarded as a less than optimally formulated version of my own. Lange has also responded to Maher by arguing that the apparent relevance of temporal considerations is merely apparent: what is really involved, according to Lange, is whether or not a hypothesis constitutes an "arbitrary conjunction." I argue that Lange's suggestion fails: the correct analysis of his and Maher's examples is that provided by my account. (shrink)

The accommodation of evidence has been argued to be associated with several methodological problems that should prompt evaluators to lower their confidence in the accommodative theory. Accommodators may overfit their model to data (Hitchcock and Sober, Br J Philos Sci 55(1):1–34, 2004. https://doi.org/10.1093/bjps/55.1.1), hunt for (spurious) associations between variables (Mayo, Error and the growth of experimental knowledge. University of Chicago Press, Chicago, 1996, pp 294–318), or ‘fudge’ their theory in the effort to accommodate a particular datum (Lipton, Inference to the (...) best explanation. Routledge, London, 2004, pp. 164–183). The converse of accommodation, novel prediction, has been offered as a solution. If theorists novelly predict empirical results rather than accommodate those results, the potential risks of accommodation are avoided, and the theory warrants greater confidence. This paper evaluates if the problems of accommodation justify a preference for novel prediction over accommodation for evaluators of a scientific theory. I argue that there is currently insufficient evidence to conclude that the problems of accommodation result in a predictivist advantage in theory confirmation. Taking into consideration the disadvantages of novel prediction and the advantages of accommodation, the impact of further evidential factors, and recent scientific evidence about the consequences of novel prediction and accommodation, novel prediction and accommodation appear roughly on a par, or accommodation is even superior in the current context. (shrink)