Conscious experiences are characterized by mental qualities, such as those involved in seeing red, feeling pain, or smelling cinnamon. The standard framework for modeling mental qualities represents them via points in geometrical spaces, where distances between points inversely correspond to degrees of phenomenal similarity. This paper argues that the standard framework is structurally inadequate and develops a new framework that is more powerful and flexible. The core problem for the standard framework is that it cannot capture precision structure: for example, (...) consider the phenomenal contrast between seeing an object as crimson in foveal vision versus merely as red in peripheral vision. The solution I favor is to model mental qualities using regions, rather than points. I explain how this seemingly simple formal innovation not only provides a natural way of modeling precision, but also yields a variety of further theoretical fruits: it enables us to formulate novel hypotheses about the space and structures of mental qualities, formally differentiate two dimensions of phenomenal similarity, generate a quantitative model of the phenomenal sorites, and define a measure of discriminatory grain. A noteworthy consequence is that the structure of the mental qualities of conscious experiences is fundamentally different from the structure of the perceptible qualities of external objects. (shrink)

When we see objects blurrily, in the periphery, or in dim light, we often experience their features unclearly. This paper argues that perceptual clarity is a dimension along which experiences vary, distinct from their distal contents. Drawing on models in perception science, the paper accounts for clarity by using the probabilistic notion of precision. The account’s first part is ecumenical: it says that experiences carry information about the precision of the representations from which each distal content of experience was selected (...) and that this precision information accounts for perceptual clarity. The account’s second part entails that experiences carry the relevant precision information in the manner in which their distal contents are represented. The precision account of clarity is shown to conform to common intuitions about experiences’ contents and accuracy conditions. And it is used to illustrate how experiences could assign probability distributions over distal possibilities, even while experiences’ contents are non-probabilistic. (shrink)

1. Sometimes perceptual experience is crystal clear, as when one inspects an object close-up in bright light with corrective lenses. But experience can be less clear. To illustrate how experiences...

According to the recent Perceptual Confidence view, perceptual experiences possess not only a representational content, but also a degree of confidence in that content. The motivations for this view are partly phenomenological and partly epistemic. We discuss both the phenomenological and epistemic motivations for the view, and the resulting account of the interface between perceptual experiences and degrees of belief. We conclude that, in their present state of development, orthodox accounts of perceptual experience are still to be favoured over the (...) perceptual confidence view. (shrink)

It has been argued recently that perception is indeterminate. But there are more than one ways of spelling out what this means. The standard line is that perceptual states attribute different probabilities to different propositions. I provide an alternative to this view, where it is not the attitude, but the content of perceptual states that is indeterminate, inasmuch as it consists of the representation of determinable properties. This view does justice to the more general claim that perception is indeterminate without (...) appealing to probability either in the attitude or in the content. (shrink)

Perceptual Confidence is the view that our conscious perceptual experiences assign confidence. In previous papers, I motivated it using first-personal evidence (Morrison, 2016), and Jessie Munton motivated it using normative evidence (Munton, 2016). In this paper, I will consider the extent to which it is motivated by third-personal evidence. I will argue that the current evidence is supportive but not decisive. I will then describe experiments that might provide stronger evidence. I hope to thereby provide a roadmap for future research.

In “Perceptual Confidence,” I argue that our perceptual experiences assign degrees of confidence. In “Precision, not Confidence, Describes the Uncertainty of Perceptual Experience,” Rachel Denison disagrees. In this reply I first clarify what i mean by ‘perceptual experiences’, ‘assign’ and ‘confidence’. I then argue, contra Denison, that perception involves automatic categorization, and that there is an intrinsic difference between a blurry perception of a sharp image and a sharp perception of a blurry image. -/- .

It is increasingly common in cognitive science and philosophy of perception to regard perceptual processing as a probabilistic engine, taking into account uncertainty in computing representations of the distal environment. Models of this kind often postulate probabilistic representations, or what we will call probabilistic states,. These are states that in some sense mark or represent information about the probabilities of distal conditions. It has also been argued that perceptual experience itself in some sense represents uncertainty (Morrison _Analytic Philosophy_ 57 (1): (...) 15 48, 2016 ). In this article, we will first consider three models of sensory activity from perceptual neuroscience, namely signal detection theory (SDT), probabilistic population codes (PPC), and sampling. We will then reflect on the sense in which the probabilistic states introduced in these models are probabilistic representations. To sharpen this discussion, we will compare and contrast these probabilistic states to credences as they are understood in epistemology. We will suggest that probabilistic representation, in an appropriately robust sense, can be understood as a form of analog representation. In the last part of the paper, we apply this to the issue of whether conscious experience represents uncertainty—we will interpret this as the claim that there are phenomenal features of experience that serve as analog probabilistic representations. (shrink)

Perceptual Confidence is the thesis that perceptual experiences can be probabilistic. This thesis has been defended and criticised based on a variety of phenomenological, epistemological, and explanatory arguments. One gap in these arguments is that they neglect the question of whether perceptual experiences satisfy the formal conditions that define the notion of probability to which Perceptual Confidence is committed. Here, we focus on this underexplored question and argue that perceptual experiences do not satisfy such conditions. But if they do not, (...) then ascriptions of perceptual confidence are undefined; and so, Perceptual Confidence cannot be true. (shrink)

ABSTRACT Issues concerning the putative perception/cognition divide are not only age-old, but also resurface in contemporary discussions in various forms. In this paper, I connect a relatively new debate concerning perceptual confidence to the perception/cognition divide. The term ‘perceptual confidence’ is quite common in the empirical literature, but there is an unsettled question about it, namely: are confidence assignments perceptual or post-perceptual? John Morrison in two recent papers puts forward the claim that confidence arises already at the level of perception. (...) In this paper, I first argue that Morrison’s case is unconvincing, and then develop one picture on perceptual precision with the notion of ‘matching profile’ and ‘supervaluation’ : 481–495.), highlighting the fact that this is a vagueness account, which is similar to but importantly different from indeterminacy accounts : 156–184.). With this model in hand, there can be rich resources with which to draw a theoretical line between perception and cognition. (shrink)

Philosophy and Phenomenological Research, Volume 104, Issue 2, Page 343-363, March 2022.

One very popular framework in contemporary epistemology is Bayesian. The central epistemic state is subjective confidence, or credence. Traditional epistemic states like belief and knowledge tend to be sidelined, or even dispensed with entirely. Credences are often introduced as familiar mental states, merely in need of a special label for the purposes of epistemology. But whether they are implicitly recognized by the folk or posits of a sophisticated scientific psychology, they do not appear to fit well with perception, as is (...) often noted. -/- This paper investigates the tension between probabilistic cognition and non-probabilistic perception. The tension is real, and the solution—to adapt a phrase from Quine and Goodman—is to renounce credences altogether. (shrink)

John Morrison has argued that confidences are assigned in perceptual experience. For example, when you perceive a figure in the distance, your experience might assign a 55-percent confidence to the figure’s being Isaac. Morrison’s argument leans on the phenomenon of ‘completely trusting your experience’. I argue that Morrison presupposes a problematic ‘importation model’ of this familiar phenomenon, and propose a very different way of thinking about it. While the article’s official topic is whether confidences are assigned in perceptual experience, it (...) is also about two more general issues: how we can determine which properties are assigned in perceptual experience; and how we transition from perception to belief. (shrink)

A reply to commentators -- Jake Beck, Nico Orlandi and Aaron Franklin, and Ian Phillips -- on our paper "Does perceptual consciousness overflow cognitive access?".