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)

This paper provides a survey of philosophical discussion of the "the Turing Test". In particular, it provides a very careful and thorough discussion of the famous 1950 paper that was published in Mind.

Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether these (...) principles converge upon a set of agreed-upon principles, or diverge, with significant disagreement over what constitutes ‘ethical AI.’ Our analysis finds a high degree of overlap among the sets of principles we analyze. We then identify an overarching framework consisting of five core principles for ethical AI. Four of them are core principles commonly used in bioethics: beneficence, non-maleficence, autonomy, and justice. On the basis of our comparative analysis, we argue that a new principle is needed in addition: explicability, understood as incorporating both the epistemological sense of intelligibility (as an answer to the question ‘how does it work?’) and in the ethical sense of accountability (as an answer to the question: ‘who is responsible for the way it works?’). In the ensuing discussion, we note the limitations and assess the implications of this ethical framework for future efforts to create laws, rules, technical standards, and best practices for ethical AI in a wide range of contexts. (shrink)

Empathy is a topic of continuous debate in the nursing literature. Many argue that empathy is indispensable to effective nursing practice. Yet others argue that nurses should rather rely on sympathy, compassion, or consolation. However, a more troubling disagreement underlies these debates: There’s no consensus on how to define empathy. This lack of consensus is the primary obstacle to a constructive debate over the role and import of empathy in nursing practice. The solution to this problem seems obvious: Nurses need (...) to reach a consensus on the meaning and definition of empathy. But this is easier said than done. Concept analyses, for instance, reveal a profound ambiguity and heterogeneity of the concept of empathy across the nursing literature. Since the term “empathy” is used to refer to a range of perceptual, cognitive, emotional, and behavioral phenomena, the presence of a conceptual ambiguity and heterogeneity is hardly surprising. Our proposal is simple. To move forward, we need to return to the basics. We should develop the concept from the ground up. That is, we should begin by identifying and describing the most fundamental form of empathic experience. Once we identify the most fundamental form of empathy, we will be able to distinguish among the more derivative experiences and behaviors that are addressed by the same name and, ideally, determine the place of these phenomena in the field of nursing. The aim of this article is, consequently, to lay the groundwork for a more coherent concept of empathy and thereby for a more fruitful debate over the role of empathy in nursing. In Part 1, we outline the history of the concept of empathy within nursing, explain why nurses are sometimes warry of adapting concepts from other disciplines, and argue that nurses should distinguish between adapting concepts from applied disciplines and from more theoretical disciplines. In Part 2, we show that the distinction between emotional and cognitive empathy—borrowed from theoretical psychology—has been a major factor in nurses’ negative attitudes toward emotional empathy. We argue, however, that both concepts fail to capture the most fundamental form of empathy. In Part 3, we draw on and present some of the seminal studies of empathy that can be found in the work of phenomenological philosophers including Max Scheler, Edmund Husserl, and Edith Stein. In Part 4, we outline how their understanding of empathy may facilitate current debates about empathy’s role in nursing. (shrink)