A prominent view holds that perception and memory are distinguished at least partly by their temporal orientation: Perception functions to represent the present, while memory functions to represent the past. Call this view perceptual presentism. This chapter critically examines perceptual presentism in light of contemporary perception science. I adduce evidence for three forms of perceptual sensitivity to the past: (i) shaping perception by past stimulus exposure, (ii) recruitment of mnemonic representations in perceptual processing, and (iii) perceptual representation of present objects (...) as possessing past properties. I argue that forms (i) and (ii) are consistent with perceptual presentism, while form (iii) poses a genuine threat to the view. While the empirical case for form (iii) remains inconclusive, I suggest that the most serious challenges to perceptual presentism derive from representations that integrate mnemonic and present-tensed elements in the performance of canonical perceptual functions, such as perceiving object continuity over time. (shrink)

This article comprehensively examines how information processing relates to attention and consciousness. We argue that no current theoretical framework investigating consciousness has a satisfactory and holistic account of their informational relationship. Our key theoretical contribution is showing how the dissociation between consciousness and attention must be understood in informational terms in order to make the debate scientifically sound. No current theories clarify the difference between attention and consciousness in terms of information. We conclude with two proposals to advance the debate. (...) First, neurobiological homeostatic processes need to be more explicitly associated with conscious information processing, since information processed through attention is algorithmic, rather than being homeostatic. Second, to understand subjectivity in informational terms, we must define information uniqueness in consciousness (e.g., irreproducible information, biologically encrypted information). These approaches could help cognitive scientists better understand conflicting accounts of the neural correlates of consciousness and work toward a more unified theoretical framework. (shrink)

Perceptual processes differ from cognitive, this paper argues, in functioning to be causally controlled by proximal stimuli, and being modular, at least in a modest sense that excludes their being isotropic in Jerry Fodor's sense. This claim agrees with such theorists as Jacob Beck and Ben Phillips that a function of stimulus-control is needed for perceptual status. In support of this necessity claim, I argue, inter alia, that E.J. Green's recent architectural account misclassifies processes deploying knowledge of grammar as perceptual. (...) _Pace_ Beck and Phillips, however, I argue a function of stimulus-control is insufficient for perceptual as opposed to cognitive status. One consideration in favour of such insufficiency, noted but (I argue) not convincingly rebutted by these theorists, concerns perpetually grounded demonstrative thought. Two other considerations trade on the fact that a function of stimulus-control can arise not from blind nature but intentional design or social institutions, where so-functioning processes may but need not be perceptual. I offer two cases where such processes are cognitive, viz. skilful play-by-play announcing of ongoing events, and voluntary visualizing of ongoing events under the guidance of apt play-by-play announcements, dubbed announcement-driven visualizing (ADV). The cognitive status of these three diverse phenomena cannot be explained by an absence of a perception-like representational format or content (for ADV has such) or by a presence of personal-level mental states causally mediating between stimuli and outputs (for perception has such). A bettter explanation invokes, I argue, the non-modular character of the generating process. (shrink)

Perception solves computationally demanding problems at lightning fast speed. It recovers sophisticated representations of the world from degraded inputs, often in a matter of milliseconds. Any theory of perception must be able to explain how this is possible; in other words, it must be able to explain perception's computational tractability. One of the few attempts to move toward such an explanation has been the information encapsulation hypothesis, which posits that perception can be fast because it keeps computational costs low by (...) forgoing access to information stored in cognition. I argue that we have no compelling reason to believe that encapsulation explains (or even contributes to an explanation of) perceptual tractability, and much reason to doubt it. This is because there exist much deeper computational challenges for perception than information access, and these threaten to make the costs of access irrelevant. If this is right, it undermines a core computational motivation for encapsulation and sends us back to the drawing board for explanations of perceptual tractability. (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.

According to phenomenal conservatism or dogmatism, perceptual experiences can give us immediate justification for beliefs about the external world in virtue of having a distinctive kind of phenomenal character—namely phenomenal force. I present three cases to show that phenomenal force is neither pervasive among nor exclusive to perceptual experiences. The plausibility of such cases calls out for explanation. I argue that contrary to a long-held assumption, phenomenal force is a separate, non-perceptual state generated by some metacognitive mechanisms that monitor one’s (...) first-order mental processes and states. This new account advances our understanding of the nature of phenomenal force. (shrink)

A theoretical pillars of vision science in the information-processing tradition is that perception involves unconscious inference. The classic support for this claim is that, since retinal inputs underdetermine their distal causes, visual perception must be the conclusion of a process that starts with premises representing both the sensory input and previous knowledge about the visible world. Focus on this “argument from underdetermination” gives the impression that, if it fails, there is little reason to think that visual processing involves unconscious inference. (...) Here an alternative means of support for this pillar is proposed, based on another foundational challenge for the visual system: recognizing invariant properties of objects in the environment even though anything we encounter is never seen exactly the same way twice. Explaining how the visual system solves this invariance problem requires positing visual processes that exhibit many commonalities with inductive inference. Thus, this novel “argument from invariance” reveals one way in which visual processing clearly involves unconscious inference. (shrink)

Fodor argued that learning a concept by hypothesis testing would involve an impossible circularity. I show that Fodor's argument implicitly relies on the assumption that actually φ-ing entails an ability to φ. But this assumption is false in cases of φ-ing by luck, and just such luck is involved in testing hypotheses with the kinds of generative random sampling methods that many cognitive scientists take our minds to use. Concepts thus can be learned by hypothesis testing without circularity, and it (...) is plausible that this is how humans in fact acquire at least some of their concepts. (shrink)

Clark (2018) worries that predictive processing accounts of perception introduce a puzzling disconnect between the content of personal-level perceptual states and their underlying subpersonal representations. According to PP, in perception, the brain encodes information about the environment in conditional probability density distributions over causes of sensory input. But it seems perceptual experience only presents us with one way the world is at a time. If perception is at bottom probabilistic, shouldn’t this aspect of subpersonally represented content show up in consciousness? (...) To address this worry, Clark argues that representations underlying personal-level content are constrained by the need to provide a single action-guiding take on the environment. However, this proposal rests a conception of the nature of agency, famously articulated by Davidson (1980a,b), that is inconsistent with a view of the mind as embodied-extended. Since Clark and other enactivist PP theorists present the extended mind as an important consequence of the predictive framework, the proposal is in tension with his complete view. I claim that this inconsistency could be resolved either by retaining the Davidsonian view of action and abandoning the extended-embodied approach, or by adopting a more processual, world-involving account of agency and perceptual experience than Clark currently endorses. To solve the puzzle he raises, Clark must become a radical enactivist or a consistent internalist. (shrink)

Is attention both necessary and sufficient for consciousness? Call this central question of this treatise, “Q.” We commonly have the experience of consciously paying attention to something, but is it possible to be conscious of something you are not attending to, or to attend to something of which you are not conscious? Where might we find examples of these? This treatise is a quest to find an answer to Q in two parts. Part I reviews the foundations upon which the (...) discourse on Q is built. Different inputs to Q produce different answers. After consideration of the many ways “attention” and “consciousness” have been defined, I settle upon phenomenal consciousness and Executive Attention (defined as a suite of strategies for structuring cognition for further processing implemented by the executive of working memory) as the most interesting inputs to Q, and the ones on which Part II focuses. Attention without consciousness seems relatively easy to establish empirically, but consciousness without attention is much harder. The putative candidates all seem to have major problems, but I build a strong abductive case for the hitherto ignored case of foveal phenomenal overflow. We consciously see far more detail in our foveal fields than we can Executively Attend, although there is a serious obstacle to our ever confirming that empirically—identifying conscious content relies on Executive Attentional report. Triangulating the capacity limitations of attention, consciousness, and working memory strengthens this case for consciousness without attention, and suggests that cognition must work something like my “Witches’ Hat Model,” on which content can become conscious outside of Executive Attention or working memory. I conclude with some reflections on the implications of my arguments for the discourse on Q, and for other discourses such as the ontologies of attention and consciousness, theories of consciousness, some other cognitive concepts, and ethical considerations in humans, animals, and machines. A conclusive answer to Q continues to elude us. It may perhaps be an ultimately insoluble conundrum. But it is the very essence of humanity to seek an answer, and in so doing, to improve our understanding of our own nature: “The proper study of mankind is man.”1. (shrink)

Introspection is a fundamental part of our mental lives. Nevertheless, its reliability and its underlying cognitive architecture have been widely disputed. Here, I propose a principled way to model introspection. By using time-tested principles from signal detection theory (SDT) and extrapolating them from perception to introspection, I offer a new framework for an introspective signal detection theory (iSDT). In SDT, the reliability of perceptual judgments is a function of the strength of an internal perceptual response (signal- to-noise ratio) which is, (...) to a large extent, driven by the intensity of the stimulus. In parallel to perception, iSDT models the reliability of introspective judgments as a function of the strength of an internal introspective response (signal-to-noise ratio) which is, to a large extent, driven by the intensity of conscious experiences. Thus, by modelling introspection after perception, iSDT can calibrate introspection’s reliability across a whole range of contexts. iSDT offers a novel, illuminating way of thinking about introspection and the cognitive processes that support it. (shrink)

A venerable view holds that a border between perception and cognition is built into our cognitive architecture and that this imposes limits on the way information can flow between them. While the deliverances of perception are freely available for use in reasoning and inference, there are strict constraints on information flow in the opposite direction. Despite its plausibility, this approach to the perception-cognition border has faced criticism in recent years. This article develops an updated version of the architectural approach, which (...) I call the dimension restriction hypothesis (DRH). According to DRH, perceptual processes are constrained to compute over a bounded range of dimensions, while cognitive processes are not. This view allows that perception is cognitively penetrable, but places strict limits on the varieties of penetration that can occur. The article argues that DRH enjoys both theoretical and empirical support, and also defends the view against several objections. (shrink)

Can perceptual experiences be states of uncertainty? We might expect them to be, if the perceptual processes from which they're generated, as well as the behaviors they help produce, take account of probabilistic information. Yet it has long been presumed that perceptual experiences purport to tell us about our environment, without hedging or qualifying. Against this long-standing view, I argue that perceptual experiences may well occasionally be states of uncertainty, but that they are never probabilistically structured. I criticize a powerful (...) line of reasoning that we should expect perceptual experience to be probabilistic, given their interfaces with unconscious probabilistic information, with behavior responsive to it, and with credences. (shrink)

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)

In their constructive reviews, Frances Egan, Randy Gallistel and Steven Gross have raised some important problems for the account of content advanced by Nicholas Shea in Representation in Cognitive Science. Here the author addresses their main challenges. Egan argues that the account includes an unrecognised pragmatic element; and that it makes contents explanatorily otiose. Gallistel raises questions about homomorphism and correlational information. Gross puts the account to work to resolve a dispute about probabilistic contents in perception, but argues that a (...) question remains about whether probabilities are found in the content or instead in the manner of representation. (shrink)

This paper explores aspects of GPT-3 that have been discussed as harbingers of artificial general intelligence and, in particular, linguistic intelligence. After introducing key features of GPT-3 and assessing its performance in the light of the conversational standards set by Alan Turing in his seminal paper from 1950, the paper elucidates the difference between clever automation and genuine linguistic intelligence. A central theme of this discussion on genuine conversational intelligence is that members of a linguistic community never merely respond “algorithmically” (...) to queries through a selective kind of pattern recognition, because they must also jointly attend and act with other speakers in order to count as genuinely intelligent and trustworthy. This presents a challenge for systems like GPT-3, because representing the world in a way that makes conversational common ground salient is an essentially collective task that we can only achieve jointly with other speakers. Thus, the main difficulty for any artificially intelligent model of conversation is to account for the communicational intentions and motivations of a speaker through joint attention. These joint motivations and intentions seem to be completely absent from the standard way in which systems like GPT-3 and other artificial intelligent systems work. This is not merely a theoretical issue. Since GPT-3 and future iterations of similar systems will likely be available for commercial use through application programming interfaces, caution is needed regarding the risks created by these systems, which pass for “intelligent” but have no genuine communicational intentions, and can thereby produce fake and unreliable linguistic exchanges. (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)

Among the exciting prospects raised by advocates of predictive processing [PP] is the offer of a systematic description of our neural activity suitable for drawing explanatory bridges to the structure of conscious experience. Yet the gulf to cross seems wide. For, as critics of PP have argued, our visual experience certainly doesn’t seem probabilistic.While Clark proposes a means to make PP compatible with the experience of a determinate world, I argue that we should not rush to do so. Two notions (...) of determinacy are conflated in the claim that perception is determinate: ‘univocality’ and ‘full detail’. The former, as Clark argues, is only to be expected in any PP agent that models its world for the purpose of acting on it. But as Husserl argued, and as perceptual psychology has borne out, we significantly overestimate the degree of detail with which we perceive a univocal world.This second form of indeterminacy is due not to the probabilistic nature of PP’s model, but rather to its hierarchical structure, with increasingly coarse-grained representations as we move further from the sensory periphery. A PP system may, or may not, deliver a univocal hypothesis at each of these levels. An action-oriented PP system would only be expected to do so only at the level needed for successful action guidance. A naïve reporter’s overestimation of the degree of determinate detail in their visual experience can thereby be accounted for with a more gradual version of the ‘refrigerator light’ effect: we experience determinate details just to the degree that they’re needed – immediately as they’re needed. (shrink)

It has been widely asserted that humans have a “Bayesian brain.” Surprisingly, however, this term has never been defined and appears to be used differently by different authors. I argue that Bayesian brain should be used to denote the realist view that brains are actual Bayesian machines and point out that there is currently no evidence for such a claim.

This article will provide a unifying perspective on perception and cognitionviathe route of linguistic representations of emotion. Linguistic representations of emotions provide a fertile ground for explorations into the nature and form of integration of perception and cognition because emotion has facets of both perceptual and cognitive processes. In particular, this article shows that certain types of linguistic representations of emotion allow for the integration of perception and cognition through a series of steps and operations in cognitive systems, whereas certain (...) other linguistic representations of emotion are not so representationally structured as to permit the unity of perception and cognition. It turns out that the types of linguistic representations of emotion that readily permit the desired unity of perception and cognition are exactly those that are linguistically encoded emotive representations of everyday objects, events, and things around us. It is these ordinary objects, events and things that provide the scaffolding for task-dependent or goal-oriented activities of cognitive systems including autonomous systems. In this way, cognitive systems can be saliently tuned to the outer world by being motivated and also subtly governed by emotion-driven representations. This helps not only tie together perceptual and cognitive processesviathe interface between language and emotive representations, but also reveal the limits of emotive representations in amalgamating perceptual and cognitive processes in cognitive systems. (shrink)