‘Naturalizing phenomenology’ by limiting it to the ontology of the sciences is problematic on both metaphysical and phenomenological grounds. While most assessments of the prospects for a ‘naturalized phenomenology’ have focused on approaches based in Husserlian transcendental phenomenology, problems also arise for non-reductive approaches based in Heideggerian existential phenomenology. ‘Heideggerian cognitive science’ faces a dilemma. On the one hand, if it is directly concerned with the nature of subjectivity, and this subjectivity is assumed to be ontologically irreducible to its physical (...) enablers yet still metaphysically dependent on them, then Heideggerian cognitive science will either leave that metaphysical dependence an unexplained instance of supervenience, or ground it in speculation about brute metaphysical laws that have an unclear relationship to the ontology of the sciences. On the other hand, if Heideggerian cognitive science is not directly concerned with the nature of subjectivity, but is instead merely aimed at the development of a Heideggerian phenomenological psychology, then it doesn’t fully address the ontological implications of phenomenology’s transcendental approach, and so, while it might succeed in explaining the realization of psychological phenomena scientifically, the existence of subjectivity will remain inexplicable based on the ontology of the sciences. Neither strategy succeeds in ‘naturalizing phenomenology’: either rejects scientific naturalism, or makes its requirements trivial, while either rejects the transcendental dimension of phenomenology, or fails to address its ontological implications. (shrink)

Recent advances in philosophical thinking about consciousness, such as cognitive phenomenology and mereological analysis, provide a framework that facilitates using computational models to explore issues surrounding the nature of consciousness. Here we suggest that, in particular, studying the computational mechanisms of working memory and its cognitive control is highly likely to identify computational correlates of consciousness and thereby lead to a deeper understanding of the nature of consciousness. We describe our recent computational models of human working memory and propose that (...) three computational correlates of consciousness follow from the results of this work: itinerant attractor sequences, top-down gating, and very fast weight changes. Our current investigation is focused on evaluating whether these three correlates are sufficient to create more complex working memory models that encompass compositionality and basic causal inference. We conclude that computational models of working memory are likely to be a fruitful approach to advancing our understanding of consciousness in general and in determining the long-term potential for development of an artificial consciousness specifically. (shrink)

While substantial progress has been made in the field known as artificial consciousness, at the present time there is no generally accepted phenomenally conscious machine, nor even a clear route to how one might be produced should we decide to try. Here, we take the position that, from our computer science perspective, a major reason for this is a computational explanatory gap: our inability to understand/explain the implementation of high-level cognitive algorithms in terms of neurocomputational processing. We explain how addressing (...) the computational explanatory gap can identify computational correlates of consciousness. We suggest that bridging this gap is not only critical to further progress in the area of machine consciousness, but would also inform the search for neurobiological correlates of consciousness and would, with high probability, contribute to demystifying the “hard problem” of understanding the mind–brain relationship. We compile a listing of previously proposed computational correlates of consciousness and, based on the results of recent computational modeling, suggest that the gating mechanisms associated with top-down cognitive control of working memory should be added to this list. We conclude that developing neurocognitive architectures that contribute to bridging the computational explanatory gap provides a credible and achievable roadmap to understanding the ultimate prospects for a conscious machine, and to a better understanding of the mind–brain problem in general. (shrink)

This paper aims to address the relevance of the natural sciences for transcendental phenomenology, that is, the issue of naturalism. The first section distinguishes three varieties of naturalism and corresponding forms of naturalization: an ontological one, a methodological one, and an epistemological one. In light of these distinctions, in the second section, I examine the main projects aiming to “naturalize phenomenology”: neurophenomenology, front-loaded phenomenology, and formalized approaches to phenomenology. The third section then considers the commitments of Husserl’s transcendental phenomenology with (...) respect to the three varieties of naturalism previously discussed. I argue that Husserl rejected strong and weak forms of epistemological naturalism, strong methodological naturalism, and ontological naturalism. The fourth section presents the argument that Husserl endorsed a weak, conditional form of methodological naturalism. This point is illustrated with Husserl’s proposal of “somatology,” a natural science apt to study the corporeality of the lived body. The final section addresses the complementarity and respective limits of the transcendental phenomenological and the natural scientific frameworks. I argue that, on Husserl’s account, the function of transcendental phenomenology with respect to the natural sciences is to provide them with an epistemological foundation and an ontological clarification. I suggest that certain natural sciences can be understood, within the transcendental phenomenological framework, as “sciences of constitution,” that is, as sciences investigating the contribution of real structures acting as conditions of possibility for the occurrence of certain kinds of comprehensive unities in lived experience. (shrink)

Scientific theories of consciousness identify its contents with the spatiotemporal structure of neural population activity. We follow up on this approach by stating and motivating Dynamical Emergence Theory, which defines the amount and structure of experience in terms of the intrinsic topology and geometry of a physical system’s collective dynamics. Specifically, we posit that distinct perceptual states correspond to coarse-grained macrostates reflecting an optimal partitioning of the system’s state space—a notion that aligns with several ideas and results from computational neuroscience (...) and cognitive psychology. We relate DET to existing work, offer predictions for empirical studies, and outline future research directions. (shrink)

In this paper I will present three reservations about the claims made by Hutto and Satnet. First of all, though TNOC is presented as drawing on teleological theories of mental content for a conception of Ur-Intentionaltiy, what is separated out after objectionable claims are removed from teleological accounts may not retain enough to give us directed intelligence. This problem raises a question about what we need in a naturalistic basis for an account of the mental. Secondly, I think that the (...) authors’ objections to cognitive science’s supposed notion of a mental representation in fact attack a philosophers’ invention, one that sprung into vibrant being in the mid-1970’s. It is not employed in cognitive neuroscience to any significant extent and it isn’t needed by other disciplines involved in cognitive science. Finally, I worry that the account of the origin of content – namely, explanatory narrative - presents us with a too limited view of human discourse, particularly as it is needed for a social theory of mind. (shrink)

Shanahan’s eloquently argued version of the global workspace theory fits well into the emerging understanding of consciousness as a computational phenomenon. His disinclination toward metaphysics notwithstanding, Shanahan’s book can also be seen as supportive of a particular metaphysical stance on consciousness — the computational identity theory.

Information processing in neural systems can be described and analysed at multiple spatiotemporal scales. Generally, information at lower levels is more fine-grained but can be coarse-grained at higher levels. However, only information processed at specific scales of coarse-graining appears to be available for conscious awareness. We do not have direct experience of information available at the scale of individual neurons, which is noisy and highly stochastic. Neither do we have experience of more macro-scale interactions, such as interpersonal communications. Neurophysiological evidence (...) suggests that conscious experiences co-vary with information encoded in coarse-grained neural states such as the firing pattern of a population of neurons. In this article, we introduce a new informational theory of consciousness: Information Closure Theory of Consciousness (ICT). We hypothesise that conscious processes are processes which form non-trivial informational closure (NTIC) with respect to the environment at certain coarse-grained scales. This hypothesis implies that conscious experience is confined due to informational closure from conscious processing to other coarse-grained scales. ICT proposes new quantitative definitions of both conscious content and conscious level. With the parsimonious definitions and a hypothesise, ICT provides explanations and predictions of various phenomena associated with consciousness. The implications of ICT naturally reconcile issues in many existing theories of consciousness and provides explanations for many of our intuitions about consciousness. Most importantly, ICT demonstrates that information can be the common language between consciousness and physical reality. (shrink)

The proponents of machine consciousness predicate the mental life of a machine, if any, exclusively on its formal, organizational structure, rather than on its physical composition. Given that matter is organized on a range of levels in time and space, this generic stance must be further constrained by a principled choice of levels on which the posited structure is supposed to reside. Indeed, not only must the formal structure fit well the physical system that realizes it, but it must do (...) so in a manner that is determined by the system itself, simply because the mental life of a machine cannot be up to an external observer. To illustrate just how tall this order is, we carefully analyze the scenario in which a digital computer simulates a network of neurons. We show that the formal correspondence between the two systems thereby established is at best partial, and, furthermore, that it is fundamentally incapable of realizing both some of the essential properties of actual neuronal systems and some of the fundamental properties of experience. Our analysis suggests that, if machine consciousness is at all possible, conscious experience can only be instantiated in a class of machines that are entirely different from digital computers, namely, time-continuous, open, analog dynamical systems. (shrink)

This book provides a comprehensive overview of my recent theoretical work that aims to explain some of the more puzzling properties of life and mind, in particular agency, goal-directedness and consciousness. It contains published papers as well as new material. Table of contents: Preface - PART I: GROUNDWORK - 1. Introduction - 2. The basic mechanism - 3. Inclusive and extensive fitness - 4. Components of F and X - 5. The consequences: a preview - PART II: LIFE - 6. (...) What qualifies as life? - 7. Biological meaning - 8. Biological functions - PART III: MIND - 9. Minimal agency, goal-directedness and value - 10. Intentionality and meaning - 11. Language - 12. Consciousness - 13. The human self - PART IV: PHILOSOPHY - 14. Strong emergence - 15. The real, the true and the good - 16. Philosophical problems of consciousness - Epilogue - Appendix A: Summaries of computational simulations - Appendix B: Examples of minimal intentionality - References. -/- . (shrink)

A computational theory of consciousness should include a quantitative measure of consciousness, or MoC, that (i) would reveal to what extent a given system is conscious, (ii) would make it possible to compare not only different systems, but also the same system at different times, and (iii) would be graded, because so is consciousness. However, unless its design is properly constrained, such an MoC gives rise to what we call the boundary problem: an MoC that labels a system as conscious (...) will do so for some – perhaps most – of its subsystems, as well as for irrelevantly extended systems (e.g., the original system augmented with physical appendages that contribute nothing to the properties supposedly supporting consciousness), and for aggregates of individually conscious systems (e.g., groups of people). This problem suggests that the properties that are being measured are epiphenomenal to consciousness, or else it implies a bizarre proliferation of minds. We propose that a solution to the boundary problem can be found by identifying properties that are intrinsic or systemic: properties that clearly differentiate between systems whose existence is a matter of fact, as opposed to those whose existence is a matter of interpretation (in the eye of the beholder). We argue that if a putative MoC can be shown to be systemic, this ipso facto resolves any associated boundary issues. As test cases, we analyze two recent theories of consciousness in light of our definitions: the Integrated Information Theory and the Geometric Theory of consciousness. (shrink)