The truly philosophical issue in machine conscioiusness is whether machines can have 'hard consciounsess'. Criteria for hard consciousness are higher than for phenomenal consciousness, since the latter incorporates first-person functional consciousness.

This paper extends three decades of work arguing that researchers who discuss consciousness should not restrict themselves only to (adult) human minds, but should study (and attempt to model) many kinds of minds, natural and artificial, thereby contributing to our understanding of the space containing all of them. We need to study what they do or can do, how they can do it, and how the natural ones can be emulated in synthetic minds. That requires: (a) understanding sets of requirements (...) that are met by different sorts of minds, i.e. the niches that they occupy, (b) understanding the space of possible designs, and (c) understanding complex and varied relationships between requirements and designs. Attempts to model or explain any particular phenomenon, such as vision, emotion, learning, language use, or consciousness lead to muddle and confusion unless they are placed in that broader context. A methodology for making progress is summarised and a novel requirement proposed for a theory of how human minds work: the theory should support a single generic design for a learning, developing system that, in addition to meeting familiar requirements, should be capable of developing different and opposed philosophical viewpoints about consciousness, and the so-called hard problem. In other words, we need a common explanation for the mental machinations of mysterians, materialists, functionalists, identity theorists, and those who regard all such theories as attempting to answer incoherent questions. No designs proposed so far come close. (shrink)

Machine consciousness is not only a technological challenge, but a new way to approach scientific and theoretical issues which have not yet received a satisfactory solution from AI and robotics. We outline the foundations and the objectives of machine consciousness from the standpoint of building a conscious robot.

It is argued here that the phenomenon of consciousness is nothing more than a special way of a subjective internal appearance of information. To explain consciousness is to explain how this subjective internal appearance of information can arise in the brain. To create a conscious robot is to create subjective internal appearances of information inside the robot. Other features that are often attributed to the phenomenon of consciousness are related to the contents of consciousness and cognitive functions. The internal conscious (...) appearance of these is caused by the mechanism that gives rise to the internal appearances in the first place. A useful conscious robot must have a variety of cognitive abilities, but these abilities alone, no matter how advanced, will not make the robot conscious; the phenomenal internal appearances must be present as well. The Haikonen Cognitive Architecture (HCA) tries to facilitate both internal appearances and cognitive functions. The experimental robot XCR-1 is the first implementation experiment with the HCA. (shrink)

Pylyshyn restricts cognitively penetrable vision to late vision, whereas he does not make any distinction between different kinds of penetrating cognition. I argue that this approach disconnects early vision content from late vision content and blurs the distinction between the latter and the content of thought. To overcome this problem I suggest that we should not distinguish between different kinds of visual content but instead introduce a restriction on the kind of cognition that can directly penetrate visual experience. In particular, (...) I suggest that visual experience, unlike thought, is directly penetrated only by practical non-propositional knowledge. I specify this weak cognitive penetrability in anti-representational terms. In particular, I suggest that the dependence of visual content on practical non-propositional knowledge should be conceived as a rational non-inferential relation, for it is in this way that we can account for the distinctive content of visual experience. (shrink)

The accurate measurement of the level of consciousness of a creature remains a major scientific challenge, nevertheless a number of new accounts that attempt to address this problem have been proposed recently. In this paper we analyze the principles of these new measures of consciousness along with other classical approaches focusing on their applicability to Machine Consciousness (MC). Furthermore, we propose a set of requirements of what we think a suitable measure for MC should be, discussing the associated theoretical and (...) practical issues. Using the proposed requirements as a framework for the design of an integrative measure of consciousness, we explore the possibility of designing such a measure in the context of current state of the art in consciousness studies. (shrink)

Sloman suggests that although many try to model consciousness as a unitary and abstract entity, the project is an incoherent one. This claim will be supported, but it will also be argued that current movements in consciousness research are broadly consistent with Sloman's "alternative" suggestions of how best to make progress in this area.