Myles Jackson, Harmonious Triads: Physicists, Musicians, and Instrument Makers in Nineteenth-Century Germany. Cambridge, MA: MIT Press, 2006. x + 395 pp. $40.00/£25.95. ISBN-10 0-262-10116-5. Much...

Research on interdisciplinary science has for the most part concentrated on the institutional obstacles that discourage or hamper interdisciplinary work, with the expectation that interdisciplinary interaction can be improved through institutional reform strategies such as through reform of peer review systems. However institutional obstacles are not the only ones that confront interdisciplinary work. The design of policy strategies would benefit from more detailed investigation into the particular cognitive constraints, including the methodological and conceptual barriers, which also confront attempts to work (...) across disciplinary boundaries. Lessons from cognitive science and anthropological studies of labs in sociology of science suggest that scientific practices may be very domain specific, where domain specificity is an essential aspect of science that enables researchers to solve complex problems in a cognitively manageable way. The limit or extent of domain specificity in scientific practice, and how it constrains interdisciplinary research, is not yet fully understood, which attests to an important role for philosophers of science in the study of interdisciplinary science. This paper draws upon two cases of interdisciplinary collaboration; those between ecologists and economists, and those between molecular biologists and systems biologists, to illustrate some of the cognitive barriers which have contributed to failures and difficulties of interactions between these fields. Each exemplify some aspect of domain specificity in scientific practice and show how such specificity may constrain interdisciplinary work. (shrink)

A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: we take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. (...) We believe that this equation formally captures the concept of machine intelligence in the broadest reasonable sense. We then show how this formal definition is related to the theory of universal optimal learning agents. Finally, we survey the many other tests and definitions of intelligence that have been proposed for machines. (shrink)

A SECOND COMPLETELY REVISED EDITION OF THIS TEXTBOOK ON INTERDISCIPLINARY RESEARCH WAS PUBLISHED WITH AMSTERDAM UNIVERSITY PRESS IN 2022. Check out that version here and a PDF of its ToC and Introduction, as this first edition (AUP 2016) is no longer available. [This book (128 pp.) serves as an introduction and manual to guide students through the interdisciplinary research process. We are becoming increasingly aware that, as a result of technological developments and globalisation, problems are becoming so complex that they (...) can only be solved through cooperation between multiple disciplines. Healthcare, climate change, food security, energy, financial markets and quality of life are just a few examples of issues that require scientists and academics to work in a crossdisciplinary way. As a result of these developments, an interdisciplinary approach is becoming increasingly popular in higher education and must be considered an absolute necessity. Young academics are being called on to step beyond the boundaries of traditional disciplines in order to contribute to addressing fundamental problems and solving challenges facing society. There is a need for people who are not afraid to ask critical questions, who can work together well and can look beyond the boundaries of their own field. This means students need to learn more about how they can integrate and apply knowledge, methods and skills from different fields. Interdisciplinary research projects and practical training courses offer students more than one perspective on the same subject. Comparing and contrasting, connecting, adding and adapting concepts, theories and methodologies from different disciplines ultimately results in new insights and better answers to complex problems.]. (shrink)

Artificial intelligence experts are currently divided into “presentist” and “futurist” factions that call for attention to near-term and long-term AI, respectively. This paper argues that the presentist–futurist dispute is not the best focus of attention. Instead, the paper proposes a reconciliation between the two factions based on a mutual interest in AI. The paper further proposes realignment to two new factions: an “intellectualist” faction that seeks to develop AI for intellectual reasons and a “societalist faction” that seeks to develop AI (...) for the benefit of society. The paper argues in favor of societalism and offers three means of concurrently addressing societal impacts from near-term and long-term AI: advancing societalist social norms, thereby increasing the portion of AI researchers who seek to benefit society; technical research on how to make any AI more beneficial to society; and policy to improve the societal benefits of all AI. In practice, it will often be advantageous to emphasize near-term AI due to the greater interest in near-term AI among AI and policy communities alike. However, presentist and futurist societalists alike can benefit from each others’ advocacy for attention to the societal impacts of AI. The reconciliation between the presentist and futurist factions can improve both near-term and long-term societal impacts of AI. (shrink)

This paper discusses means for promoting artificial intelligence that is designed to be safe and beneficial for society. The promotion of beneficial AI is a social challenge because it seeks to motivate AI developers to choose beneficial AI designs. Currently, the AI field is focused mainly on building AIs that are more capable, with little regard to social impacts. Two types of measures are available for encouraging the AI field to shift more toward building beneficial AI. Extrinsic measures impose constraints (...) or incentives on AI researchers to induce them to pursue beneficial AI even if they do not want to. Intrinsic measures encourage AI researchers to want to pursue beneficial AI. Prior research focuses on extrinsic measures, but intrinsic measures are at least as important. Indeed, intrinsic factors can determine the success of extrinsic measures. Efforts to promote beneficial AI must consider intrinsic factors by studying the social psychology of AI research communities. (shrink)

There is no strong reason to believe that human-level intelligence represents an upper limit of the capacity of artificial intelligence, should it be realized. This poses serious safety issues, since a superintelligent system would have great power to direct the future according to its possibly flawed motivation system. Solving this issue in general has proven to be considerably harder than expected. This paper looks at one particular approach, Oracle AI. An Oracle AI is an AI that does not act in (...) the world except by answering questions. Even this narrow approach presents considerable challenges. In this paper, we analyse and critique various methods of controlling the AI. In general an Oracle AI might be safer than unrestricted AI, but still remains potentially dangerous. (shrink)

Taking stock of interdisciplinarity as it nears its century mark, the Oxford Handbook of Interdisciplinarity constitutes a major new reference work on the topic of interdisciplinarity, a concept of growing academic and societal importance.

An enormous intellectual adventure. In this groundbreaking new book, the American biologist Edward O. Wilson, considered to be one of the world's greatest living scientists, argues for the fundamental unity of all knowledge and the need to search for consilience --the proof that everything in our world is organized in terms of a small number of fundamental natural laws that comprise the principles underlying every branch of learning. Professor Wilson, the pioneer of sociobiology and biodiversity, now once again breaks out (...) of the conventions of current thinking. He shows how and why our explosive rise in intellectual mastery of the truths of our universe has its roots in the ancient Greek concept of an intrinsic orderliness that governs our cosmos and the human species--a vision that found its apogee in the Age of Enlightenment, then gradually was lost in the increasing fragmentation and specialization of knowledge in the last two centuries. Drawing on the physical sciences and biology, anthropology, psychology, religion, philosophy, and the arts, Professor Wilson shows why the goals of the original Enlightenment are surging back to life, why they are reappearing on the very frontiers of science and humanistic scholarship, and how they are beginning to sketch themselves as the blueprint of our world as it most profoundly, elegantly, and excitingly is. (shrink)

Interdisciplinary understanding requires integration of insights from different perspectives, yet it appears questionable whether disciplinary experts are well prepared for this. Indeed, psychological and cognitive scientific studies suggest that expertise can be disadvantageous because experts are often more biased than non-experts, for example, or fixed on certain approaches, and less flexible in novel situations or situations outside their domain of expertise. An explanation is that experts’ conscious and unconscious cognition and behavior depend upon their learning and acquisition of a set (...) of mental representations or knowledge structures. Compared to beginners in a field, experts have assembled a much larger set of representations that are also more complex, facilitating fast and adequate perception in responding to relevant situations. This article argues how metacognition should be employed in order to mitigate such disadvantages of expertise: By metacognitively monitoring and regulating their own cognitive processes and representations, experts can prepare themselves for interdisciplinary understanding. Interdisciplinary collaboration is further facilitated by team metacognition about the team, tasks, process, goals, and representations developed in the team. Drawing attention to the need for metacognition, the article explains how philosophical reflection on the assumptions involved in different disciplinary perspectives must also be considered in a process complementary to metacognition and not completely overlapping with it. (Disciplinary assumptions are here understood as determining and constraining how the complex mental representations of experts are chunked and structured.) The article concludes with a brief reflection on how the process of Reflective Equilibrium should be added to the processes of metacognition and philosophical reflection in order for experts involved in interdisciplinary collaboration to reach a justifiable and coherent form of interdisciplinary integration. An Appendix of “Prompts or Questions for Metacognition” that can elicit metacognitive knowledge, monitoring, or regulation in individuals or teams is included at the end of the article. (shrink)