Igor Douven

In a celebrated experiment, Joshua Knobe showed that people are much more prone to attribute intentionality to an agent for a side effect of a given act when that side effect is harmful than when it is beneficial. This asymmetry has become known as ‘the Knobe Effect’. According to Knobe's Moral Valence Explanation, bad effects trigger the attributions of intentionality, whereas good effects do not. Many others believe that the Knobe Effect is best explained in terms of the high amount of blame attributed in the harm condition, and the low amount of praise attributed in the help condition. This Blame Hypothesis explains the high number of intentionality attributions in the harm condition in terms of the high degree of blame people ascribe, and the low number of intentionality attributions in the help conditions in terms of the low degree of praise people attribute. We replicated Knobe's original experiment and conducted a logistic regression on the results to probe more deeply into the relationship between attributions of intentionality and responsibility. The statistical analysis revealed a hitherto unknown interaction effect: intentionality correlates with blame, but not with praise. This interaction effect is consistent with the Moral Valence Hypothesis, but inconsistent with the Blame Hypothesis, as well as with two of the three other hypotheses discussed here.

In previous published research (“Conditionals and Inferential Connections: A Hypothetical Inferential Theory,” Cognitive Psychology, 2018), we investigated experimentally what role the presence and strength of an inferential connection between a conditional’s antecedent and consequent plays in how people process that conditional. Our analysis showed the strength of that connection to be strongly predictive of whether participants evaluated the conditional as true, false, or neither true nor false. In this article, we re-analyse the data from our previous research, now focussing on the semantics of conditionals rather than on how they are processed. Specifically, we use those data to compare the main extant semantics with each other and with inferentialism, a semantics according to which the truth of a conditional requires the presence of an inferential connection between the conditional’s component parts.

Various authors have recently argued that you cannot rationally stick to your belief in the face of known disagreement with an epistemic peer, that is, a person you take to have the same evidence and judgmental skills as you do. For, they claim, because there is but one rational response to any body of evidence, a disagreement with an epistemic peer indicates that at least one of you is not responding rationally to the evidence. Given that you take your peer to have the same judgmental skills as you do, and thus regard her to be equally good at assessing the evidence as you are, you will have as much reason for thinking that it is you who is not responding rationally to the evidence as for thinking that it is her. You thus have reason for thinking that your belief on the disputed matter is not a rational response to the evidence. Hence, you cannot rationally stick to your belief.

We present a model for studying communities of epistemically interacting agents who update their belief states by averaging the belief states of other agents in the community. The agents in our model have a rich belief state, involving multiple independent issues which are interrelated in such a way that they form a theory of the world. Our main goal is to calculate the probability for an agent to end up in an inconsistent belief state due to updating. To that end, an analytical expression is given and evaluated numerically, both exactly and using statistical sampling. It is shown that, under the assumptions of our model, an agent always has a probability of less than 2% of ending up in an inconsistent belief state. Moreover, this probability can be made arbitrarily small by increasing the number of independent issues the agents have to judge or by increasing the group size. A real-world situation to which this model applies is a group of experts participating in a Delphi-study

This article addresses two questions related to colour categorization, to wit, the question what a colour category is, and the question how we identify colour categories. We reject both the relativist and universalist answers to these questions. Instead, we suggest that colour categories can be identified with the help of the criterion of psychological saliency, which can be operationalized by means of consistency and consensus measures. We further argue that colour categories can be defined as well-structured entities that optimally partition colour space. We provide some empirical support for this claim by presenting experimental results, which indicate that internal structure is a better predictor of colour categories than perceptual saliency

Conceptual spaces have become an increasingly popular modeling tool in cognitive psychology. The core idea of the conceptual spaces approach is that concepts can be represented as regions in similarity spaces. While it is generally acknowledged that not every region in such a space represents a natural concept, it is still an open question what distinguishes those regions that represent natural concepts from those that do not. The central claim of this paper is that natural concepts are represented by the cells of an optimally designed similarity space.

Regier, Kay, and Khetarpal report the results of computer simulations that cluster color stimuli on the basis of their coordinates in CIELAB space, one of two commonly used perceptual color spaces. Regier and coauthors find partitions of those stimuli that are strikingly similar to the way actual color lexicons partition color space. They do not argue for the custom-made clustering method used in their simulations, nor for the assumption of CIELAB space. The present paper aims to answer the question to what extent their computational results depend on these assumptions. It does this by applying a great variety of known clustering methods to Regier et al.’s stimuli, and by assuming not only CIELAB space but also CIELUV space, the other main color space.

The gift of life argument, the claim that suicide is immoral because our lives are not ours to dispose of as we are their guardians or stewards, is a persistent theme in debates about the morality of suicide, assisted-suicide, and euthanasia. I argue that this argument suffers from a fatal internal incoherence. The gift can either be interpreted literally or analogically. If it is interpreted literally there are serious problems in understanding who receives the gift. If it is understood analogically the question arises whether the gift is understood to be a finite or everlasting existence. If it is finite then it is hard to see how one can be punished for bringing that existence to an end for one will not be around to be punished. If the existence is infinite it is impossible to see how one can be punished for ending one’s life because one cannot end it. However, there is still ethical mileage to be gained from the description of life as a gift and in the concluding section I indicate one way in which this is so

According to what is now commonly referred to as “the Equation” in the literature on indicative conditionals, the probability of any indicative conditional equals the probability of its consequent of the conditional given the antecedent of the conditional. Philosophers widely agree in their assessment that the triviality arguments of Lewis and others have conclusively shown the Equation to be tenable only at the expense of the view that indicative conditionals express propositions. This study challenges the correctness of that assessment by presenting data that cast doubt on an assumption underlying all triviality arguments.

Many have the intuition that the right response to the Lottery Paradox is to deny that one can justifiably believe of even a single lottery ticket that it will lose. The paper shows that from any theory of justification that solves the paradox in accordance with this intuition, a theory not of that kind can be derived that also solves the paradox but is more conducive to our epistemic goal than the former. It is argued that currently there is no valid reason not to give preference to the derived accounts over the accounts from which they come.

Many philosophers deny that happiness can be equated with pleasurable experiences. Nozick introduced an experience machine thought experiment to support the idea that happiness requires pleasurable experiences that are “in contact with reality.” In this thought experiment, people can choose to plug into a machine that induces exclusively pleasurable experiences. We test Nozick’s hypothesis that people will reject this offer. We also contrast Nozick’s experience machine scenario with scenarios that are less artificial, and offer options which are less invasive or disruptive than being connected to a machine, specifically scenarios in which people are offered an experience pill or a pill that improves overall functioning.

This article aims to achieve two goals: to show that probability is not the only way of dealing with uncertainty ; and to provide evidence that logic-based methods can well support reasoning with uncertainty. For the latter claim, two paradigmatic examples are presented: logic programming with Kleene semantics for modelling reasoning from information in a discourse, to an interpretation of the state of affairs of the intended model, and a neural-symbolic implementation of input/output logic for dealing with uncertainty in dynamic normative contexts.

The Lottery Paradox is generally thought to point at a conflict between two intuitive principles, to wit, that high probability is sufficient for rational acceptability, and that rational acceptability is closed under logical derivability. Gilbert Harman has offered a solution to the Lottery Paradox that allows one to stick to both of these principles. The solution requires the principle that acceptance licenses conditionalization. The present study shows that adopting this principle alongside the principle that high probability is sufficient for rational acceptability gives rise to another paradox.

This paper is concerned with a version of Kamp and Partee's account of graded membership that relies on the conceptual spaces framework. Three studies are reported, one to construct a particular shape space, one to detect which shapes representable in that space are typical for certain sorts of objects, and one to elicit degrees of category membership for the various shapes from which the shape space was constructed. Taking Kamp and Partee's proposal as given, the first two studies allowed us to predict the degrees to which people would judge shapes representable in the space to be members of certain categories. These predictions were compared with the degrees that were measured in the third study. The comparison yielded a test of the account of graded membership at issue. The outcome of this test was found to support the conceptual spaces version of Kamp and Partee's account of graded membership.

According to the Lockean thesis, a proposition is believed just in case it is highly probable. While this thesis enjoys strong intuitive support, it is known to conflict with seemingly plausible logical constraints on our beliefs. One way out of this conflict is to make probability 1 a requirement for belief, but most have rejected this option for entailing what they see as an untenable skepticism. Recently, two new solutions to the conflict have been proposed that are alleged to be non-skeptical. We compare these proposals with each other and with the Lockean thesis, in particular with regard to the question of how much we gain by adopting any one of them instead of the probability 1 requirement, that is, of how likely it is that one believes more than the things one is fully certain of.