Despite the compelling subjective experience of executive self-control, we argue that ‘consciousness’ contains no top-down control processes. We propose that ‘consciousness’ involves no executive, causal or controlling relationship with any of the familiar psychological processes conventionally attributed to it. In our view all psychological processing and psychological products are non-conscious. In particular, we argue that all ‘contents of consciousness’ are generated by and within non-conscious brain systems in the form of a continuous self-referential personal narrative that is not directed or (...) influenced in any way by the ‘experience of consciousness’. This continuously updated personal narrative arises from selective ‘internal broadcasting’ of outputs from non-conscious executive systems that have access to all forms of cognitive processing, sensory information and motor control. The personal narrative provides information for storage in autobiographical memory and is underpinned by constructs of self and agency, also created in non-conscious systems. The experience of consciousness, is seen as a passive accompaniment to the non-conscious processes of internal broadcasting and the creation of the personal narrative. In this sense personal awareness is analogous to the rainbow which accompanies physical processes in the atmosphere but exerts no influence over them. Though at an individual level it is an end-product created by non-conscious executive systems, the personal narrative serves the powerful evolutionary function of enabling individuals to communicate (externally broadcast) the contents of internal broadcasting. This in turn allows the recipients to generate potentially adaptive strategies, such as predicting the behavior of others and underlies the development of social and cultural structures, that promote species survival. Consequently, it is the capacity to communicate to others the contents of the personal narrative that confers an evolutionary advantage – not the experience of consciousness (personal awareness) itself. (shrink)

Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...) intelligence encouraged by these successes, especially in the domain of language processing. We then show an alternative approach to language-centric AI, in which we identify a role for philosophy. (shrink)

This thesis explores the possibility of composite consciousness: phenomenally conscious states belonging to a composite being in virtue of the consciousness of, and relations among, its parts. We have no trouble accepting that a composite being has physical properties entirely in virtue of the physical properties of, and relations among, its parts. But a long­standing intuition holds that consciousness is different: my consciousness cannot be understood as a complex of interacting component consciousnesses belonging to parts of me. I ask why: (...) what is it about consciousness that makes us think it so different from matter? And should we accept this apparent difference? (shrink)

Meaning in life is too important not to study systematically, but doing so is made difficult by conceptual indeterminacy. An approach to meaning that is promising but, indeed, conceptually vague is Jonathan Haidt’s ‘cross-level coherence’ account. In order to remove the vagueness, I propose a concept of ‘good fit’ that a) captures central aspects of meaning as it is discussed in the literature; b) brings the subject of meaning under the survey of the dynamicist or ‘embodied-embedded’ philosophy of cognition; and (...) c) allows the theoretical discussion on meaning to become more focused and systematic. The article addresses two apparent problems with the idea of ‘good fit,’ namely the fact that both challenges and relations of an agent with the outside world are central to meaning. It is finally pointed out which implications adopting the concept of ‘good fit’ instead of ‘meaning’ would have. (shrink)

We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children (...) construct new causal maps and that their learning is consistent with the Bayes net formalism. (shrink)

According to Thagard and Stewart :1–33, 2011), creativity results from the combination of neural representations, and combination results from convolution, an operation on vectors defined in the holographic reduced representation framework. They use these ideas to understand creativity as it occurs in many domains, and in particular in science. We argue that, because of its algebraic properties, convolution alone is ill-suited to the role proposed by Thagard and Stewart. The semantic pointer concept allows us to see how we can apply (...) the full range of HRR operations while keeping the modal representations so central to Thagard and Stewart’s theory. By adding another combination operation and using semantic pointers as the combinatorial basis, this modified version overcomes the limitations of the original theory and perhaps helps us explain aspects of creativity not covered by the original theory. While a priori reasons cast doubts on the use of HRR operations with modal representations :5039–5054, 1987) such as semantic pointers, recent models point in the other direction, allowing us to be optimistic about the success of the revised version. (shrink)

Julian Reiss correctly identified a trilemma about economic models: we cannot maintain that they are false, but nevertheless explain and that only true accounts explain. In this reply we give reasons to reject the second premise ? that economic models explain. Intuitions to the contrary should be distrusted.