Frederick Hayes-Roth

Bio: Frederick Hayes-Roth is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 46 citations.

Artificial Intelligence: What Works and What Doesn't?

Abstract: AI has been well supported by government research and development dollars for decades now, and people are beginning to ask hard questions: What really works? What are the limits? What doesn't work as advertised? What isn't likely to work? What isn't affordable? This article holds a mirror up to the community, both to provide feedback and stimulate more self-assessment. The significant accomplishments and strengths of the field are highlighted. The research agenda, strategy, and heuristics are reviewed, and a change of course is recommend-ed to improve the field's ability to produce reusable and interoperable components.

Explanations from intelligent systems: theoretical foundations and implications for practice

Abstract: Information systems with an "intelligent" or "knowledge" component are now prevalent and include knowledge-based systems, decision support systems, intelligent agents and knowledge management systems These systems are in principle capable of explaining their reasoning or justifying their behavior There appears to be a lack of understanding, however, of the benefits that can flow from explanation use, and how an explanation function should be constructed Work with newer types of intelligent systems and help functions for everyday systems, such as word-processors, appears in many cases to neglect lessons learned in the past This paper attempts to rectify this situation by drawing together the considerable body of work on the nature and use of explanations Empirical studies, mainly with knowledge-based systems, are reviewed and linked to a sound theoretical base The theoretical base combines a cognitive effort perspective, cognitive learning theory, and Toulmin's model of argumentation Conclusions drawn from the review have both practical and theoretical significance Explanations are important to users in a number of circumstances - when the user perceives an anomaly, when they want to learn, or when they need a specific piece of knowledge to participate properly in problem solving Explanations, when suitably designed, have been shown to improve performance and learning and result in more positive user perceptions of a system The design is important, however, because it appears that explanations will not be used if the user has to exert "too much" effort to get them Explanations should be provided automatically if this can be done relatively unobtrusively, or by hypertext links, and should be context-specific rather than generic Explanations that conform to Toulmin's model of argumentation, in that they provide adequate justification for the knowledge offered, should be more persuasive and lead to greater trust, agreement, satisfaction, and acceptance - of the explanation and possibly also of the system as a whole

Funding a revolution : government support for computing research

Abstract: The past 50 years have witnessed a revolution in computing and related communications technologies. The contributions of industry and university researchers to this revolution are manifest; less widely recognized is the major role the federal government played in launching the computing revolution and sustaining its momentum. Funding a Revolution examines the history of computing since World War II to elucidate the federal government's role in funding computing research, supporting the education of computer scientists and engineers, and equipping university research labs. It reviews the economic rationale for government support of research, characterizes federal support for computing research, and summarizes key historical advances in which government-sponsored research played an important role. Funding a Revolution contains a series of case studies in relational databases, the Internet, theoretical computer science, artificial intelligence, and virtual reality that demonstrate the complex interactions among government, universities, and industry that have driven the field. It offers a series of lessons that identify factors contributing to the success of the nation's computing enterprise and the government's role within it.

The differential use and effect of knowledgebased system explanations in novice and expert judgment decisions

Abstract: Explanation facilities are considered essential in facilitating user interaction with knowledge-based systems (KBS). Research on explanation provision and the impact on KBS users has shown that the domain expertise affects the type of explanations selected by the user and the basis for seeking such explanations. The prior literature has been limited, however, by the use of simulated KBS that generally provide only feedback explanations (i.e., ex post to the recommendation of the KBS being presented to the user). The purpose of this study is to examine the way users with varying levels of expertise use alternative types of KBS explanations and the impact of that use on decision making. A total of 64 partner/ manager-level and 82 senior/staff-level insolvency professionals participated in an experiment involving the use of a fully functioning KBS to complete a complex judgment task. In addition to feedback explanations, the KBS also provided feedforward explanations (i.e., general explanations during user input about the relationships between information cues in the KBS) and included definition type explanations (i.e., declarative-level knowledge). The results show that users were more likely to adhere to recommendations of the KBS when an explanation facility was available. Choice patterns in using explanations indicated that novices used feedforward explanations more than experts did, while experts were more likely than novices to use feedback explanations. Novices also used more declarative knowledge and initial problem solving type explanations, while experts used more procedural knowledge explanations. Finally, use of feedback explanations led to greater adherence to the KBS recommendation by experts-a condition that was even more prevalent as the use of feedback explanations increased. The results have several implications for the design and use of KBS in a professional decision-making environment.

Artificial Intelligence and Natural Man

Abstract: sorts of philosophy in machine theories of memory. And, since one can test the resulting mechanisms, one can thereby indirectly test the underlying philosophies. Contrary to Bursen’s conclusion, not only the study of memory, but even the philosophy of mind is made more scientific due to machine theories. In conclusion, none of Bursen’s arguments provide any support for his final conclusion that ‘there cannot be a scientific, mechanistic, causal explanation for memory’ (p. 147).

Transhumanism and the imago Dei : narratives of apprehension and hope

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