Epistemology and artificial intelligence

In this essay we advance the view that analytical epistemology and artificial intelligence are complementary disciplines. Both fields study epistemic relations, but whereas artificial intelligence approaches this subject from the perspective of understanding formal and computational properties of frameworks purporting to model some epistemic relation or other, traditional epistemology approaches the subject from the perspective of understanding the properties of epistemic relations in terms of their conceptual properties. We argue that these two practices should not be conducted in isolation. We illustrate this point by discussing how to represent a class of inference forms found in standard inferential statistics. This class of inference forms is interesting because its members share two properties that are common to epistemic relations, namely defeasibility and paraconsistency. Our modeling of standard inferential statistical arguments exploits results from both logical artificial intelligence and analytical epistemology. We remark how our approach to this modeling problem may be generalized to an interdisciplinary approach to the study of epistemic relations.     

On working through: a model from artificial intelligence

Working through is centrally important to clinical psychoanalysis. It is inadequately explained in analytic theory. An artificial intelligence model of the process is proposed. Models of problem solving show that the complexity of necessary computation is an important determinant of how a problem is solved. Not optimal, but only good enough solutions are usually found. The quality of solutions depends on the time and resources available. Generally it is far easier to use existing methods than to develop new approaches. When problems must be solved in an emergency fashion, as in trauma, poor solutions are likely to emerge. In studying the annealing of metals and other complex optimization problems, a process, the Boltzman algorithm, was discovered, which continues the search for better solutions while gradually developing a coherent structure of the overall solution. The algorithm provides a model both for psychoanalytic working through and for the normally ongoing process of psychological development and reworking whose deficiency is characteristic of much psychopathology. Working through in the analytic situation is the reactivation of this normal process, and a good analytic outcome is achieved when the process can continue without the analyst. Properties of the Boltzman algorithm clarify such concepts as "optimal" frustration and anxiety which correspond to working in the area where the stable but not rigid structures emerge in the algorithms operation. These studies are an example of how computer science and artificial intelligence are a potentially rich source for psychoanalytic theory.     

Phenomenology and artificial intelligence: Husserl learns Chinese

For over a decade John Searle's ingenious argument against the possibility of artificial intelligence has held a prominent place in contemporary philosophy. This is not just because of its striking central example and the apparent simplicity of its argument. As its appearance in Scientific American testifies, it is also due to its importance to the wider scientific community. If Searle is right, artificial intelligence in the strict sense, the sense that would claim that mind can be instantiated through a formal program of symbol manipulation, is basically wrong. No set of formal conditions can provide us with the characteristic feature of mind which is the intentionally of its mental contents. Formally regarded, such intentionally is an irreducible primitive. It cannot be analyzed into non-intentional (purely syntactic, symbolic) components. This paper will argue that this objection is based on a misunderstanding. Intentionality is not simply something given which is incapable of further analysis. It only appears so when we mistakenly abstract it from time. When we regard its temporal structure, it shows itself as a rule-governed, synthetic process, one capable of being instantiated both by machines and men.     

Using interactive computing to expand intelligence testing: A critique and prospectus

Microcomputers can serve as automated testing stations for use in psychometric assessment. There are economic advantages in conducting aptitude and intelligence testing with such stations. It is possible to improve the quality of cognitive assessment by extending the range of cognitive abilities to be assessed? Two types of extension are considered; modifying and expanding testing procedures for psychological functions that are components of conventional tests, and the extension oof testing to psychological functions not generally assessed by conventional intelligence or aptitude tests. Computerized presentations will make relatively little difference in our ways of testing verbal comprehension. Computer controlled testing could well extend the ways in which we evaluate spatial-visual reasoning and memory. The impact of testing on the evaluation of reasoning is unclear. Computer-controlled item presentation makes it possible to conceive of tests of learning and attention, neither of which are evaluated in most psychometric programs today. The psychological nature of the abilities being assessed raises problems in assessment that are not addressed by the fact oof computer-control. Some research questions are identified that ought to be explored before testing is extended into these fields. Computer-controlled evaluation could be extended to the assessment of criterion performance, either in the normal working situation or in a simulation of the workplace. While evaluation of this sort does raise social questions, it clearly presents an opportunity to obtain validation data for psychological assessment studies.     

Jensen's reaction-time investigations of intelligence: A critique

Jensen has reported a series of reaction-time studies which lead him to conclude that various parameters correlate significantly with IQ. Certain of these parameters are especially emphasized because of their theoretical background and the resulting theoretical light they shed upon the nature of intelligence. Two of the lime-lighted parameters are slope of RT across set size and increasing correlations of RT with IQ as set size increases. I review these studies in detail. I conclude that Jensen's claims are unwarranted. There are many difficulties in his approach that cover the entire gamut from method to data to theory. Some original reseach of my own is reported to illustrate the methodological problems with Jensen's procedure. The data that he alludes to often do not support his claims. The theory that he applies does not fit his paradigm. My conclusion: such research is not easy.     

智能时代的工程心理学

智能技术为智能时代的工程心理学研究和应用提供了新的机遇。为此, 系统提出了智能时代工程心理学的工作框架。该工作框架包括工程心理学研究和应用的对象、核心问题空间、学科理念、研究重点、应用范围、方法等。智能时代的人机关系呈现出一种新的形式: 人机组队式的人机合作关系。“以人为中心的人工智能”应该是智能时代工程心理学的学科理念。针对智能技术, 近期工程心理学研究者开始开展围绕新型人机关系的理论框架和基本问题、人机组队中的心理结构和决策控制、人机交互等方面的研究工作。为有效支持智能系统的研发, 概括总结了一些工程心理学新方法和提升的方法。最后, 针对当前工程心理学所面对的一些挑战提出了具体的建议。     

人工智能决策的公平感知

不平等问题是全球社会和经济发展需要应对的首要挑战,也是实现全球可持续发展目标的核心障碍。人工智能(artificial intelligence, AI)为缓解不平等、促进社会公平提供了新的途径。然而,新近研究发现,即使客观上AI决策具有公平性和准确性,个体仍可能对AI决策的公平感知较低。因此,近年来越来越多的研究开始关注AI决策公平感知的影响因素。然而,目前研究较为分散,呈现出研究范式不统一、理论不清晰和机制未厘清等特征。这既不利于跨学科的研究对话,也不利于研究者和实践者对AI决策公平感知形成系统性理解。基于此,通过系统的梳理,现有研究可以划分为两类:(1) AI单一决策的公平感知研究,主要聚焦于AI特征和个体特征如何影响个体对AI决策的公平感知;(2) AI-人类二元决策的公平感知研究,主要聚焦于对比个体对AI决策与人类决策公平感知的差异。在上述梳理基础上,未来研究可以进一步探索AI决策公平感知的情绪影响机制等方向。     

Decision theory and artificial intelligence II: The hungry monkey

This paper describes a problem-solving framework In which aspects of mathematical decision theory are incorporated into symbolic problem-solving techniques currently predominant in artificial intelligence. The utility function of decision theory IS used to reveal tradeoffs among competing strategies for achieving various goals, taking into account such factors as reliability, the complexity of steps in the strategy, and the value of the goal. The utility function on strategies can therefore be used as a guide when searching for good strategies. It is also used to formulate solutions to the problems of how to acquire a world model, how much planning effort is worthwhile, and whether verification tests should be performed. These techniques are illustrated by application to the classic monkey and bananas problem.     

Predication,fiction, and artificial intelligence

This paper describes the SNePS knowledge-representation and reasoning system. SNePS is an intensional, propositional, semantic-network processing system used for research in AI. We look at how predication is represented in such a system when it is used for cognitive modeling and natural-language understanding and generation. In particular, we discuss issues in the representation of fictional entities and the representation of propositions from fiction, using SNePS. We briefly survey four philosophical ontological theories of fiction and sketch an epistemological theory of fiction (implemented in SNePS) using a story operator and rules for allowing propositions to migrate into and out of story spaces.     

Hypermedia, cognition, and artificial intelligence

Alice was beginning to get very tired of sitting by her sister on the bank and of having nothing to do: once or twice she had peeped into the book her sister was reading, but it had no pictures or conversation in it, “and what is the use of a book,” thought Alice, “without pictures or conversation?” Alice’s Adventures in Wonderland. Lewis Carroll Hari Seldon and his band of psychologists planted a colony—the Foundation—to incubate art, science, and technology, and form the nucleus of the Second Empire. The Foundation Trilogy. Isaac Asimov     

Performing the imago Dei: human enhancement,artificial intelligence and optative image-bearing

If the imago Dei is not a taxonomic definition but rather something that is performed in context, what are the implications for questions of human enhancement and the development of artificial intelligence (AI)? The author considers Alistair McFadyen’s performative vision of the imago Dei, one that actively seeks humanity in concrete situations, in the context of human enhancement and AI, asking the questions, ‘Does becoming cyborg through human enhancement make us less bearers of the divine image?’ And, ‘Can AI ever be considered to be in the image of God?’ Briefly tracing the shift in perspectives on the imago Dei, before considering what a performance of the image might look like, the author proposes three performances that have significant implications for questions about what it means to be human. To be an image-bearer is not dependent upon human DNA or species membership, but on an optative performance of the imago Dei.     

Affect,artificial intelligence,and internal space

Is Artificial Intelligence (AI) affectless? This essay explores a small fragment from the early history of AI when questions about affect became pressing. It focuses on biographical and intellectual data about Walter Pitts, one of the important early practitioners of cybernetics. The essay addresses two interlocking difficulties in early AI: (1) it points to the harm caused to a science that establishes itself by inhibiting the affective capacities of the mind; and (2) it ponders the melancholic effects of a research milieu that, contemptuously, rejects knowledge of internal psychological space.     

Against the iDoctor: why artificial intelligence should not replace physician judgment

Experts in medical informatics have argued for the incorporation of ever more machine-learning algorithms into medical care. As artificial intelligence (AI) research advances, such technologies raise the possibility of an “iDoctor,” a machine theoretically capable of replacing the judgment of primary care physicians. In this article, I draw on Martin Heidegger’s critique of technology to show how an algorithmic approach to medicine distorts the physician–patient relationship. Among other problems, AI cannot adapt guidelines according to the individual patient’s needs. In response to the objection that AI could develop this capacity, I use Hubert Dreyfus’s analysis of AI to argue that attention to the needs of each patient requires the physician to attune his or her perception to the patient’s history and physical exam, an ability that seems uniquely human. Human physician judgment will remain better suited to the practice of primary care despite anticipated advances in AI technology.     

Body,thought, being-human and artificial intelligence: Merleau-Ponty and Lyotard

Abstract

This article focuses in a comparative manner on the thought of Merleau-Ponty and Lyotard with a view to lending support to Busch’s claim, that ‘existentialism’ preceded poststructuralism and postmodernism as far as criticism of certain features of modem philosophy are concerned. Attention is first given to Lyotard’s critique of artificial intelligence, especially in so far as it displays a dependence on and development of insights on the part of Merleau-Ponty’s phenomenological-existential understanding of human embodiment and the specificity of human perception. The focus then shifts to Merleau-Ponty in order to demonstrate the remarkable extent to which his understanding of human embodiment and related issues such as perception and creativity, paved the way for the work of, among others, Lyotard, and anticipated the critique of artificial intelligence on the part of the latter.     

Impacts of artificial intelligence on organizational decision making

Of all of the new technologies emerging in the late 20th century, the production of artificial intelligence may provide the most profound impacts on organizational decision making. Because the development of artificial intelligence technologies and models has largely been based on psychological models of human cognition, the effects of their implementation in complex social settings have not been thoroughly examined. This paper is an attempt to generate research which will develop a comprehensive understanding of the impacts of artificial intelligence and its role in complex organizations. A set of 11 hypotheses has been developed which examine the relationships between artificial intelligence technologies and the dimensions of organizational decision making. It is argued here that the implementation of expert systems will lead to less complex and political decision processes, while the implementation of natural language systems will lead to more complex and political decision processes.