Creativity is one of the least understood aspects of intelligence and is often seen as intuitive' and not susceptible to rational enquiry. Recently, however, there has been a resurgence of interest in the area, principally in artificial intelligence and cognitive science, but also in psychology, philosophy, computer science, logic, mathematics, sociology, and architecture and design. This volume brings this work together and provides an overview of this rapidly developing field. It addresses a range of issues. Can computers be creative? Can (...) they help us to understand human creativity? How can artificial intelligence (AI) enhance human creativity? How, in particular, can it contribute to the sciences of the artificial', such as design? Does the new wave of AI (connectionism, geneticism and artificial life) offer more promise in these areas than classical, symbol-handling AI? What would the implications be for AI and cognitive science if computers could not be creative? These issues are explored in five interrelated parts, each of which is introducted and explained by a leading figure in the field. - Prologue (Margaret Boden) - Part I: Foundational Issues (Terry Dartnall) - Part II: Creativity and Cognition (Graeme S. Halford and Robert Levinson) - Part III: Creativity and Connectionism (Chris Thornton) - Part IV: Creativity and Design (John Gero) - Part V: Human Creativity Enhancement (Ernest Edmonds) - Epilogue (Douglas Hofstadter) For researchers in AI, cognitive science, computer science, philosophy, psychology, mathematics, logic, sociology, and architecture and design; and anyone interested in the rapidly growing field of artificial intelligence and creativity. (shrink)

One of the arguments for active externalism (also known as the extended mind thesis) is that if a process counts as cognitive when it is performed in the head, it should also count as cognitive when it is performed in the world. Consequently, mind extends into the world. I argue for a corollary: We sometimes perform actions in our heads that we usually perform in the world, so that the world leaks into the mind. I call this internalism. Internalism has (...) epistemological implications: If a process gives us an empirical discovery when it is performed in the world, it will also give us an empirical discovery when it is performed in the head. I look at a simple example that highlights this implication. I then explore the relation between internalism and active externalism in more detail and conclude by comparing internalism with mental modeling. (shrink)

How can a pain wake you up? You were not dreaming, nor did any bodily stimuli filter into your consciousness. You did not just wake up and realize you were in pain, as you might wake up and realize it is Saturday. You were deeply, dreamlessly asleep, and suddenly you were awake, and in pain. How is this possible? If pain exists only inasmuch as it is experienced, it seems that the pain did not exist when you were asleep, and (...) so could not have woken you up. I shall argue that you were woken by a pain sensation that you did not know you had, so that the distinction between what is and what is known holds even for the contents of consciousness. This illuminates the relationship between consciousness and attention, and casts light on the Classical Empiricist tradition that identifies the foundations of knowledge with direct experience. (shrink)

Active externalism (also known as the extended mind hypothesis) says that we use objects and situations in the world as external memory stores that we consult as needs dictate. This gives us economies of storage: We do not need to remember that Bill has blue eyes and wavy hair if we can acquire this information by looking at Bill. I argue for a corollary to this position, which I call ‘internalism.’ Internalism says we can acquire knowledge on a need‐to‐know basis (...) by consulting portable, inner analogues of the world. This, however, leads to a dilemma. If the knowledge was stored in memory, it is difficult to see how we could have acquired it by consulting inner analogues, for it would seem that we knew it already. Moreover, if it was stored in memory, we lose the economies of storage that provide much of the rationale for external memory stores and hence for their inner analogues. If, on the other hand, the knowledge was not stored in memory, it is difficult to see how we could have acquired it by consulting inner analogues, for it was not there to be acquired. I propose a solution to this problem that turns on the concept of nonconceptual content, and I relate the solution to Stephen Kosslyn's (1994) architecture of perception and visual mental imagery. Viewed in a broader context, the solution shows that the world leaks into the mind, as well as mind leaking into the world. (shrink)

Grush's framework has epistemological implications and explains how it is possible to acquire offline empirical knowledge. It also complements the extended-mind thesis, which says that mind leaks into the world. Grush's framework suggests that the world leaks into the mind through the offline deployment of emulators that we usually deploy in our experience of the world.

This collection written by leading figures in cognitive science includes their lively debates with Dartnall about his call for a new epistemology, an alternative to the standard representational story in cognitive science. Dartnall aims to show that new epistemology is already with us in some leading-edge models of human creativity. Such an epistemology steers a middle road between the representationism of classical cognitive science and a radical anti-representationism that denies the existence or importance of representations.

Clark & Thornton's “superficially distinct ploys and mechanisms” are in fact very different: there is a deep difference between (a) filters and feature detectors, which “let the information in,” and (b) contentful representations and theories, which reconfigure it into a computationally tractable form. (a) is bringing abilities to experience whereas (b) is bringing content to experience. Both have well known problems. I outline an evolutionary story that avoids these problems and begins to explain how representations and theories developed out of (...) feature detectors and filters. (shrink)