This paper challenges the view that arguments are (by definition, as it were) attempts to persuade or convince an audience to accept (or reject) a point of view by presenting reasons for (or against) that point of view. I maintain, first, that an arguer need not intend any effect beyond that of making it manifest to readers or hearers that there is a reason for doing some particular thing (e.g., for believing a certain proposition, or alternatively for rejecting it), and (...) second that when an arguer is in fact trying to induce an effect above and beyond rendering a reason manifest, the effect intended—the use to which his or her argument is put—need not be that hearers do what the stated reasons are reasons for doing. Where the actual or intended effect of making a reason R for doing X manifest is something other than doing X, I call it an oblique—as opposed to a direct—effect of making that reason manifest. The core of the paper presents an overview or map of the main categories of effect which arguments can have, and the main sub-types within each category, calling attention to the points at which such effects can be indirect or oblique effects. The purpose of that typology is to make it clear (i) how oblique effects can come about and (ii) how important a role they can play in the conduct of argumentation. (shrink)

Argumentation involves offering and/or exchanging reasons – either reasons for adopting various attitudes towards specific propositional contents or else reasons for acting in various ways. This paper develops the idea that the force of reasons is through and through a normative force because what good reasons accomplish is precisely to give one a certain sort of entitlement to do what they are reasons for. The paper attempts to shed light on what it is to have a reason, how the sort (...) of entitlement arising from reasons differs from other species of entitlement and how the norms by which such entitlement is assessed obtain their status as norms. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (shrink)

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions.

The Church–Turing Thesis (CTT) is often employed in arguments for computationalism. I scrutinize the most prominent of such arguments in light of recent work on CTT and argue that they are unsound. Although CTT does nothing to support computationalism, it is not irrelevant to it. By eliminating misunderstandings about the relationship between CTT and computationalism, we deepen our appreciation of computationalism as an empirical hypothesis.

According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.

Philosophy invariably starts with the attempt to spell out ideas and beliefs that we already hold, whether on topics like time or causality, colour or value, consciousness or free will, democracy or justice or freedom. It may go well beyond such pre-philosophical assumptions in its further developments, regimenting them in unexpected ways, revising them on novel lines, even discarding them entirely in favour of other views. But philosophy always begins with the articulation of ordinary ideas and beliefs. This is where (...) its ladder starts. As the name suggests, articulation requires that the ideas and beliefs articulated were already there waiting to be spelled out, and that identifying them is a matter of analysing.. (shrink)

Although they may differ on the reason why, many philosophers hold that it is a priori that an object is red if and only if it is such as to look red to normal observers in normal conditions.

This article is an extended critical study of Robert C. Stalnaker, 'Inquiry' (Cambridge, MA: MIT Press, 1984).

We propose a model for belief which is free of presuppositions. Current models for belief suffer from two difficulties. One is the well known problem of logical omniscience which tends to follow from most models. But a more important one is the fact that most models do not even attempt to answer the question what it means for someone to believe something, and just what it is that is believed. We provide a flexible model which allows us to give meaning (...) to beliefs in general contexts, including the context of animal belief , and of human belief which is expressed in language. (shrink)

Bromwich (2010) argues that a belief is motivationally efficacious in that, other things being equal, it disposes an agent to answer a question in accordance with that belief. I reply that what we are disposed to do is largely determined by our genes, whereas what we believe is largely determined by stimuli from the environment. We have a standing and default disposition to answer questions honestly, ceteris paribus, even before we are exposed to environmental stimuli. Since this standing and default (...) disposition is innate, and our beliefs have their source in environmental stimuli, our beliefs cannot be the source of the disposition. Moreover, a recent finding in neuroscience suggests that motivation is extrinsic to belief. (shrink)

When I woke up a few days ago, the following thoughts ran through my mind. ‘I need a haircut. If I don't get it first thing this morning, I won't have another chance for two weeks. But if I go to the barber down the road, he'll want to talk to me about philosophy. So I'd better go to the one in Camden Town. The tube will be very crowded, though. Still, it's a nice day. Why don't I just walk (...) there? It will only take twenty minutes. So I'd better put on these shoes now, have breakfast straight away, and then set out for Camden.’. (shrink)

In the late preschool years children acquire a "theory of mind", the ability to ascribe intentional states, including beliefs, desires and intentions, to themselves and others. In this paper I trace how children's ability to ascribe intentions is derived from parental attempts to hold them responsible for their talk and action, that is, the attempt to have their behavior meet a normative standard or rule. Self-control is children's developing ability to take on or accept responsibility, that is, the ability to (...) ascribe intentions to themselves. This is achieved, I argue, when they possess the ability to hold an utterance or rule in mind in the form of a quoted expression, and second, when they grasp the causal relation between the rule and their action. The account of how children learn to ascribe intention to themselves and others will then be used to explore the larger question of the relations amongst language, intentional states and the ascription and avowal of those states. (shrink)

Computational models of emotions have been thriving and increasingly popular since the 1990s. Such models used to be concerned with the emotions of individual agents when they interact with other agents. Out of the array of models for the emotions, we are going to devote special attention to the approach in Adamatzky’s Dynamics of Crowd-Minds. The reason it stands out, is that it considers the crowd, rather than the individual agent. It fits in computational intelligence. It works by mathematical simulation (...) on a crowd of simple artificial agents: by letting the computer program run, the agents evolve, and crowd behaviour emerges. Adamatzky’s purpose is to give an account of the emergence of allegedly “irrational” behaviour. This is not without problem, as the irrational to one person may seem entirely rational to another, and this in turn is an insight that, in the history of crowd psychology, has affected indeed the competition among theories of crowd dynamics. Quite importantly, Adamatzky’s book argues for the transition from individual agencies to a crowd’s or a mob’s coalesced mind as so, and at any rate for coalesced crowd’s agency. (shrink)

John Searle has argued that one can imagine embodying a machine running any computer program without understanding the symbols, and hence that purely computational processes do not yield understanding. The disagreement this argument has generated stems, I hold, from ambiguity in talk of 'understanding'. The concept is analysed as a relation between subjects and symbols having two components: a formal and an intentional. The central question, then becomes whether a machine could possess the intentional component with or without the formal (...) component. I argue that the intentional state of a symbol's being meaningful to a subject is a functionally definable relation between the symbol and certain past and present states of the subject, and that a machine could bear this relation to a symbol. I sketch a machine which could be said to possess, in primitive form, the intentional component of understanding. Even if the machine, in lacking consciousness, lacks full understanding, it contributes to a theory of understanding and constitutes a counterexample to the Chinese Room argument. (shrink)

John Searle has argued that one can imagine embodying a machine running any computer program without understanding the symbols, and hence that purely computational processes do not yield understanding. The disagreement this argument has generated stems, I hold, from ambiguity in talk of 'understanding'. The concept is analysed as a relation between subjects and symbols having two components: a formal and an intentional. The central question, then becomes whether a machine could possess the intentional component with or without the formal (...) component. I argue that the intentional state of a symbol's being meaningful to a subject is a functionally definable relation between the symbol and certain past and present states of the subject, and that a machine could bear this relation to a symbol. I sketch a machine which could be said to possess, in primitive form, the intentional component of understanding. Even if the machine, in lacking consciousness, lacks full understanding, it contributes to a theory of understanding and constitutes a counterexample to the Chinese Room argument. (shrink)