I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to (...) the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the 'imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart front the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B. We now ask the question, "What will happen when a machine takes the part of A in this game?" Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, "Can machines think?". (shrink)

A classic collection of interlocking tales chronicles the near-future development of the robot and features models that have the ability to read minds, experience human emotions, and take over the world--and, perhaps, render humankind itself obsolete. Reprint. 25,000 first printing.

In this paper, we move toward offering psychological benchmarks to measure success in building increasingly humanlike robots. By psychological benchmarks we mean categories of interaction that capture conceptually fundamental aspects of human life, specified abstractly enough to resist their identity as a mere psychological instrument, but capable of being translated into testable empirical propositions. Nine possible benchmarks are considered: autonomy, imitation, intrinsic moral value, moral accountability, privacy, reciprocity, conventionality, creativity, and authenticity of relation. Finally, we discuss how getting the right (...) group of benchmarks in human–robot interaction will, in future years, help inform on the foundational question of what constitutes essential features of being human. (shrink)

The first generation of children to grow up with electronic toys and games saw computers as our “nearest neighbors.” They spoke of computers as rational machines and of people as emotional machines, a fragile formulation destined to be challenged. By the mid-1990s, computational creatures, including robots, were presenting themselves as “relational artifacts,” beings with feelings and needs. One consequence of this development is a crisis in authenticity in many quarters. In an increasing number of situations, people behave as though they (...) no longer place value on living things and authentic emotion. This paper examines watershed moments in the history of human–machine interaction, focusing on the pertinence of relational artifacts to our collective perception of aliveness, life’s purposes, and the implications of relational artifacts for relationships. For now, the exploration of human–robot encounters leads us to questions about the morality of creating believable digital companions that are evocative but not authentic. (shrink)

A BSTRACT: I argue that theory theory approaches to autism offer a wholly inadequate explanation of autistic symptoms because they offer a wholly inadequate account of the non-autistic understanding of others. As an alternative I outline interaction theory, which incorporates evidence from both developmental and phenomenological studies to show that humans are endowed with important capacities for intersubjective understanding from birth or early infancy. As part of a neurophenomenological analysis of autism, interaction theory offers an account of interpersonal problems that (...) is fully consistent with the variety of social and nonsocial symptoms found in autism. (shrink)

The first generation of children to grow up with electronic toys and games saw computers as our “nearest neighbors.” They spoke of computers as rational machines and of people as emotional machines, a fragile formulation destined to be challenged. By the mid-1990s, computational creatures, including robots, were presenting themselves as “relational artifacts,” beings with feelings and needs. One consequence of this development is a crisis in authenticity in many quarters. In an increasing number of situations, people behave as though they (...) no longer place value on living things and authentic emotion. This paper examines watershed moments in the history of human–machine interaction, focusing on the pertinence of relational artifacts to our collective perception of aliveness, life’s purposes, and the implications of relational artifacts for relationships. For now, the exploration of human–robot encounters leads us to questions about the morality of creating believable digital companions that are evocative but not authentic. (shrink)

Searle's celebrated Chinese Room Argument has shaken the foundations of Artificial Intelligence. Many refutations have been attempted, but none seem convincing. This paper is an attempt to sort out explicitly the assumptions and the logical, methodological and empirical points of disagreement. Searle is shown to have underestimated some features of computer modeling, but the heart of the issue turns out to be an empirical question about the scope and limits of the purely symbolic (computational) model of the mind. Nonsymbolic modeling (...) turns out to be immune to the Chinese Room Argument. The issues discussed include the Total Turing Test, modularity, neural modeling, robotics, causality and the symbol-grounding problem. (shrink)