This paper examines the explanatory gap account. The key notions for its proper understanding are analysed. In particular, the analysis is concerned with the role of “thick” and “thin” modes of presentation and “thick” and “thin” concepts which are relevant for the notions of “thick” and “thin” conceivability, and to that effect relevant for the gappy and non-gappy identities. The last section of the paper discusses the issue of the intelligibility of explanations. One of the conclusions is that the (...) explanatory gap account only succeeds in establishing the epistemic gap. The claim that psychophysical identity is not intelligibly explicable, and thus opens the explanatory gap, would require an indepen- dent argument which would prove that intelligible explanations stem only from conceptual analysis. This, I argue, is not the case. (shrink)

Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty's Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are stored, not as representations in the mind, (...) but as dispositions to respond to the solicitations of situations in the world. A phenomenology of skill acquisition confirms that, as one acquires expertise, the acquired know-how is experienced as finer and finer discriminations of situations paired with the appropriate response to each. Maximal grip names the body's tendency to refine its responses so as to bring the current situation closer to an optimal gestalt. Thus, successful learning and action do not require propositional mental representations. They do not require semantically interpretable brain representations either.Simulated neural networks exhibit crucial structural features of the intentional arc, and Walter Freeman's account of the brain dynamics underlying perception and action is structurally isomorphic with Merleau-Ponty's account of the way a skilled agent is led by the situation to move towards obtaining a maximal grip. (shrink)

The question of liability in the case of using intelligent agents is far from simple, and cannot sufficiently be answered by deeming the human user as being automatically responsible for all actions and mistakes of his agent. Therefore, this paper is specifically concerned with the significant difficulties which might arise in this regard especially if the technology behind software agents evolves, or is commonly used on a larger scale. Furthermore, this paper contemplates whether or not it is possible to share (...) the responsibility with these agents and what are the main objections surrounding the assumption of considering such agents as responsible entities. This paper, however, is not intended to provide the final answer to all questions and challenges in this regard, but to identify the main components, and provide some perspectives on how to deal with such issue. (shrink)

We make how a person acts intelligible by revealing it as rational in the light of what she perceives, thinks, wants and so on. For example, we might explain that she reached out and picked up a glass because she was thirsty and saw that it contained water. In doing this, we are giving a causal explanation of her behaviour in terms of her antecedent beliefs, desires and other attitudes. Her wanting a drink and realizing that the glass contained (...) one caused her reaching out and grasping for it. This tells us how the action came about and makes sense of why it happened. At least, something broadly along these lines strikes me as a fairly crude and partial regimentation of our pretheoretic understanding of everyday action explanation. (shrink)

This paper outlines a procedure for assessing the quality of failure explanations in engineering failure analysis. The procedure structures the information contained in explanations such that it enables to find weak points, to compare competing explanations, and to provide redesign recommendations. These features make the procedure a good asset for critical reflection on some areas of the engineering practice of failure analysis and redesign. The procedure structures relevant information contained in an explanation by means of structural equations so as (...) to make the relations between key elements more salient. Once structured, the information is examined on its potential to track counterfactual dependencies by offering answers to relevant what-if-things-had-been-different questions. This criterion for explanatory goodness derives from the philosophy of science literature on scientific explanation. The procedure is illustrated by applying it to two case studies, one on Failure Analysis in Mechanical Engineering (a broken vehicle shaft) and one on Failure Analysis in Civil Engineering (a collapse in a convention center). The procedure offers failure analysts a practical tool for critical reflection on some areas of their practice while offering a deeper understanding of the workings of failure analysis (framing it as an explanatory practice). It, therefore, allows to improve certain aspects of the explanatory practices of failure analysis and redesign, but it also offers a theoretical perspective that can clarify important features of these practices. Given the programmatic nature of the procedure and its object (assessing and refining explanations), it extends work on the domain of computational argumentation. (shrink)

This paper offers a dialogue theory of explanation. A successful explanation is defined as a transfer of understanding in a dialogue system in which a questioner and a respondent take part. The questioner asks a special sort of why-question that asks for understanding of something and the respondent provides a reply that transfers understanding to the questioner. The theory is drawn from recent work on explanation in artificial intelligence (AI), especially in expert systems, but applies to scientific, (...) legal and everyday conversational explanations. (shrink)

Existential phenomenologists hold that the two most basic forms of intelligent behavior, learning, and skillful action, can be described and explained without recourse to mind or brain representations. This claim is expressed in two central notions in Merleau-Ponty's Phenomenology of Perception: the intentional arc and the tendency to achieve a maximal grip. The intentional arc names the tight connection between body and world, such that, as the active body acquires skills, those skills are “stored”, not as representations in the mind, (...) but as dispositions to respond to the solicitations of situations in the world. A phenomenology of skill acquisition confirms that, as one acquires expertise, the acquired know-how is experienced as finer and finer discriminations of situations paired with the appropriate response to each. Maximal grip names the body's tendency to refine its responses so as to bring the current situation closer to an optimal gestalt. Thus, successful learning and action do not require propositional mental representations. They do not require semantically interpretable brain representations either.Simulated neural networks exhibit crucial structural features of the intentional arc, and Walter Freeman's account of the brain dynamics underlying perception and action is structurally isomorphic with Merleau-Ponty's account of the way a skilled agent is led by the situation to move towards obtaining a maximal grip. (shrink)

Explanation-Aware Computing: Papers from the 2007 AAAI Workshop, Association for the Advancement of Artificial Intelligence, Technical Report WS-07-06, Menlo Park California, AAAI Press, 2007, 1-9.

Early modern experimental philosophers were opposed to speculation, and yet many endorsed speculative theories. This chapter gives a partial explanation of why this is so, using Robert Boyle’s acceptance and promotion of the corpuscular philosophy as a case study. It argues that, in addition to furnishing experimental evidence for the corpuscular hypothesis in his Forms and Qualities, Boyle attempted to establish its epistemic superiority over other speculative theories on the grounds that it is founded upon superior principles. In his (...) ‘Excellency and Grounds of the Mechanical Hypothesis’, Boyle claims that the principles of the corpuscular philosophy are more intelligible, more parsimonious, ontologically primary, simpler and more comprehensive than those of its rivals. On grounds of comparative plausibility then, according to Boyle, the corpuscular philosophy is eminently preferable to its rivals. The final section of the chapter traces the legacy of Boyle’s appraisal of the epistemic status of the corpuscular philosophy in the writings of many of his compatriots from the mid-1660s to the Cyclopedia of Ephraim Chambers of 1728. (shrink)

Teleological explanations (TEs) account for the existence or properties of an entity in terms of a function: we have hearts because they pump blood, and telephones for communication. While many teleological explanations seem appropriate, others are clearly not warranted-for example, that rain exists for plants to grow. Five experiments explore the theoretical commitments that underlie teleological explanations. With the analysis of [Wright, L. (1976). Teleological Explanations. Berkeley, CA: University of California Press] from philosophy as a point of departure, we examine (...) in Experiment 1 whether teleological explanations are interpreted causally, and confirm that TEs are only accepted when the function invoked in the explanation played a causal role in bringing about what is being explained. However, we also find that playing a causal role is not sufficient for all participants to accept TEs. Experiment 2 shows that this is not because participants fail to appreciate the causal structure of the scenarios used as stimuli. In Experiments 3-5 we show that the additional requirement for TE acceptance is that the process by which the function played a causal role must be general in the sense of conforming to a predictable pattern. These findings motivate a proposal, Explanation for Export, which suggests that a psychological function of explanation is to highlight information likely to subserve future prediction and intervention. We relate our proposal to normative accounts of explanation from philosophy of science, as well as to claims from psychology and artificial intelligence. (shrink)

This essay argues that, despite the failure of demarcation criteria for separating science from non-science, the mathematics of design and design-theoretic inferences nonetheless satisfy all the criteria of various competing theories of scientific explanation.

Explanation-Aware Computing: Papers from the 2007 AAAI Workshop, Association for the Advancement of Artificial Intelligence, Technical Report WS-07-06, Menlo Park California, AAAI Press, 2007, 1-9.

Commentators standardly ascribe to Spinoza a belief in an exceptionless conceptual closure of mental and physical realms: no intention can allow us to understand a bodily movement, no bodily injury can make intelligible a sensation of pain. This counterintuitive doctrine, most often now referred to as Spinoza's 'attribute barrier', has weighty repercussions for his views on intelligibility, nature of the mind, identity, and causality. I argue against the standard reading of the doctrine, by showing that it produces an inconsistent (...) epistemological picture, contradicting Spinoza's theory of mind and his commitment to universal intelligibility. The alternative account I propose is also philosophically more compelling and plausible as an account of thought in its essential intentionality. (shrink)

In trying to make sense out of our behavior, we reach a point at which we stop talking about what we did and start talking about what we wish we had done, about what we mean to do next. But we think we are still talking about our motives and intentions in what we did. How do we know when we cross the line between finding out what actually happened and ascribing to a situation what we think ought to have (...) happened?This is a serious question, precisely because we usually do not know the difference between what we do and what we imagine that we do. For since all action is governed by our conception of “how we would have it” and “what we would bring about,” we can always honestly claim to have meant what we did for the best. We frequently find ourselves in the situation in which we don't know why we did what we did, but by casting about, we can always turn up a purpose for which our action must have been meant - a purpose which we now perceive.The reasons we ascribe to our actions, like our excuses, are governed by the demands made on us now, rather than by the factual content of what we did. Thus the behavior of reason-giving or excusing is meant to satisfy the social situation in which we presently find ourselves: the demand for explanation, the need to be “in the right,” the need to reinforce our convictions. The verbal account of what we did is thus literally about (as representing and serving) where we are now rather than what we did then.Our verbal account is about the context of social obligation in which we have to explain ourselves, not about the behavior we claim to interpret. This is why, proverbially, we will give any excuse which will satisfy the accuser and why “understanding” i.e. inventing reasons for our conduct, is no corrective. The addict, alcoholic, neurotic and criminal recidivist are frequently rational and even persuasive in giving reasons for what they do. And we wonder why if they understand their problems so well they can't do something about them. The problem is that the habitué doesn't understand his behavior at all. He is simply trained to give a certain after the fact explanation as a conditioned response to his habitual behavior. What he “understands” is not what makes him go back to the pill, the bottle or to crime, but what to tell people each time after he does. Naturally, when the habit-triggering occasion arises, it is never that reason - the stated one - which leads to repetition, but some new, special crisis, difficulty or impulse.Bluntly stated, our reasons and justifications have little or nothing to do with our actual behavior. We continue to suppose that we intend to do this or that immediately before we do it. But insofar as this intention is expressed it is a separate verbal act having its own conditions and consequences; insofar as it is unexpressed (and in general) intention is disclosed only through conduct. It is only the powerful social convention of justification that supports the illusion that verbal expressions are causal antecedents of acts.Two conclusions follow. First, the “sense” of our activity is either evident in the activity or else it is nonexistent, since not yet discovered meaning is meaning not yet achieved. Second, our verbal justifications are acts having a peculiar sense of their own. They express the relation of our convictions and objectives to the convictions and objectives of those to whom our explanations are addressed. Here is where, in the process of making sense of our activity, the crossover from discovery to invention occurs. This is why we may never discover the extent to which our justifications are inventions superimposed on the conduct they are supposed to represent. Insofar as our justification satisfies those to whom it is addressed, (including ourselves) it is right. But we take this rightness, which is actually the the compatibility of our values and objectives, to be the rightness of the act in question. The reasons we give for our actions make great sense, but despite our invincible “rightness” our actions, taken in themselves, make no more sense.What are our options? They are either to put ourselves in the power of those to whom we explain ourselves, or to take responsibility for our own nonsense. Take our conduct out of the medium of talk - of habitual justification - in which it is suspended and sustained, and what is it? Whatever has become of the “importance” of our appointments, our meetings, our appearances, our obligations, our consistency? Experience, not persuasion and reasoning, is the corrective. Only the direct experience of futility is powerful enough to break our addiction to justification. (shrink)

Explanation and understanding are intimately connected notions, but the nature of that connection has generally not been considered a topic worthy of serious philosophical investigation. Most authors have avoided making reference to the notion of understanding in their accounts of explanation because they fear that any mention of the epistemic states of the individuals involved compromises the objectivity of explanation. Understanding is a pragmatic notion, they argue, and pragmatics should be kept at a safe distance from the (...) universal features of explanation. My main contention in this dissertation is that there is a sense in which it is meaningful and useful to talk about objective understanding, and that to characterize this notion it is necessary to formulate an account of objective explanation that makes reference to the beliefs and epistemic goals of the participants in a cognitive enterprise. ;My account of explanation is based on the belief-doubt model of inquiry first proposed by Peirce. Using the tools provided by decision theory, and the models of belief revision developed by Isaac Levi and by Alchourron, Gardenfors, and Makinson, I analyze the objective and pragmatic conditions that a piece of information must fulfill to be both explanatory and epistemically useful to an inquiring agent. The objective basis for an explanation is provided by the relation of probabilistic relevance that the fact described by the explanans bares to the fact described by the explanandum. But an explanation is much more than its foundation. As an epistemological notion, a potential explanation can only be a bona fide explanation if it becomes part of inquiry, that is, if an agent or a group of agents can see any value in it for their cognitive purposes. I provide a way to evaluate an explanation in terms of its credibility, its content, and its explanatory value. I argue that although an objective measure of the credibility and content of an explanation can be established, in many cases a complete determination of its explanatory value will ultimately depend on the interests and goals of the individual inquirers. (shrink)

In this paper I critically examine the notion of explanation used in Artificial Intelligence in general, and in the theory of belief revision in particular. I focus on two of the best known accounts in the literature: Pagnucco’s abductive expansion functions and Gärdenfors’ counterfactual analysis. I argue that both accounts are at odds with the way in which this notion has historically been understood in philosophy. They are also at odds with the explanatory strategies used in actual scientific practice. (...) At the end of the paper I outline the desiderata for an epistemologically motivated, scientifically informed belief revision model for explanation. (shrink)

Here is my thesis (and the outline of this paper). Increasingly secret, complex and inscrutable computational systems are being used to intensify existing power relations, and to create new ones (Section II). To be all-things-considered morally permissible, new, or newly intense, power relations must in general meet standards of procedural legitimacy and proper authority (Section III). Legitimacy and authority constitutively depend, in turn, on a publicity requirement: reasonably competent members of the political community in which power is being exercised must (...) be able to determine that power is being exercised legitimately and with proper authority (Section IV). The publicity requirement can be satisfied only if the powerful can explain their decision-making—including the computational tools that they use to support it—to members of their political community. Section V applies these ideas to opaque computational systems. Section VI addresses objections; Section VII concludes. (shrink)

Many philosophers of science believe that empirical psychology can contribute little to the philosophical investigation of explanations. They take this to be shown by the fact that certain explanations fail to elicit any relevant psychological events (e.g., familiarity, insight, intelligibility, etc.). We report results from a study suggesting that, at least among those with extensive science training, a capacity to render an event intelligible is considered a requirement for explanation. We also investigate for whom explanations must be capable (...) of rendering events intelligible and whether or not accuracy is also viewed as a requirement. (shrink)

Much of the philosophical discussion of explanations has centered around two broad conceptions of what sorts of ‘things’ explanations are – namely, the descriptive and ontic conceptions. Defenders of each argue that scientific psychology has at best little to contribute to the study of explanations. These anti-psychologistic arguments come in two main varieties, the metaphysical and the epistemic. Both varieties trace back to Hempel and recur in the more recent writings of prominent mechanists. The metaphysical arguments attempt to combat psychologism (...) about explanation by doubly dissociating explanations themselves from the commonly associated phenomenology of explanation. The epistemic arguments attempt to combat psychologism by doubly dissociating the good-making features of explanations from the CAPE. I focus on the metaphysical arguments here, for only they directly concern the nature of, as opposed to the evaluation conditions for, explanations. The metaphysical arguments are all shown to equivocate over ‘explanation’, and thus they are no threat to the proposal that sometimes explanations just are psychological events. Such arguments do, nonetheless, gesture towards something important – namely, that the CAPE is neither necessary nor sufficient for explanation in any sense. Similar considerations lead another latter-day mechanist to conclude that no phenomenology of any sort is essential for explanation. What all of these thinkers overlook, however, is that there is another important phenomenological correlate of explanation – namely, finding a happening intelligible or understanding how or why-possibly – and it may well be of the very essence of explanation, at least in the psychological sense. I propose a psychomechanistic theory of intelligibility that accounts for how we can, through finite means, make boundless, endlessly qualified inferences about the implications of our explanations. In closing I note that, although finding a happening intelligible does sometimes engender an unjustified confidence in correctness, we should not overlook how attaining this state does at least put us in a kind of epistemic base camp. I also hint at how intelligibility could turn out to be the ultimate source of the descriptive and ontic conceptions of explanation. (shrink)

Epidemiological explanation often has a “black box” character, meaning the intermediate steps between cause and effect are unknown. Filling in black boxes is thought to improve causal inferences by making them intelligible. I argue that adding information about intermediate causes to a black box explanation is an unreliable guide to pragmatic intelligibility because it may mislead us about the stability of a cause. I diagnose a problem that I call wishful intelligibility, which occurs when scientists misjudge (...) the limitations of certain features of an explanation. Wishful intelligibility gives us a new reason to prefer black box explanations in some contexts. (shrink)

Complexity and life as we know it depend crucially on the laws and constants of nature as well as the boundary conditions, which seem at least partly “fine-tuned.” That deserves an explanation: Why are they the way they are? This essay discusses and systematizes the main options for answering these foundational questions. Fine-tuning might just be an illusion, or a result of irreducible chance, or nonexistent because nature could not have been otherwise (which might be shown within a fundamental (...) theory if some constants or laws could be reduced to boundary conditions or boundary conditions to laws), or it might be a product of selection: either observational selection (weak anthropic principle) within a vast multiverse of many different realizations of physical parameters, or a kind of cosmological natural selection making the measured parameter values quite likely within a multiverse of many different values, or even a teleological or intentional selection or a coevolutionary development, depending on a more or less goal-directed participatory contribution of life and intelligence. In contrast to observational selection, which is not predictive, an observer-independent selection mechanism must generate unequal reproduction rates of universes, a peaked probability distribution, or another kind of differential frequency, resulting in a stronger explanatory power. The hypothesis of Cosmological Artificial Selection (CAS) even suggests that our universe may be a vast computer simulation or could have been created and transcended by one. If so, this would be a far-reaching answer – within a naturalistic framework! – of fundamental questions such as: Why did the big bang and fine-tunings occur, what is the role of intelligence in the universe, and how can it escape cosmic doomsday? This essay critically discusses some of the premises and implications of CAS and related problems, both with the proposal itself and its possible physical realization: Does CAS deserve to be considered as a convincing explanation of cosmic fine-tuning? Is life incidental, or does CAS revalue it? And are life and intelligence ultimately doomed, or might CAS rescue them? (shrink)

To give a causal explanation is to give information about causal history. But a vast amount of causal history lies behind anything that happens, far too much to be included in any intelligible explanation. This is the Problem of Limitation for explanatory information. To cope with this problem, explanations must select for what is relevant to and adequate for answering particular inquiries. In the present paper this idea is used in order to distinguish two kinds of causal (...) class='Hi'>explanation, on the grounds of systematic differences in their conditions of relevance and adequacy. It is further argued that these two forms of causal explanation are interdependent and their interaction provides an instrument through which causal knowledge is acquired and enhanced. What we understand causation in the world to be is neither unconditioned regularity, nor counterfactual dependence, but the sum of correct answers to explanatory inquiries of these two interdependent kinds. (shrink)

Monetary Intelligence theory asserts that individuals apply their money attitude to frame critical concerns in the context and strategically select certain options to achieve financial goals and ultimate happiness. This study explores the bright side of Monetary Intelligence and behavioral economics, frames money attitude in the context of pay and life satisfaction, and controls money at the macro-level and micro-level. We theorize: Managers with low love of money motive but high stewardship behavior will have high subjective well-being: pay satisfaction and (...) quality of life. Data collected from 6586 managers in 32 cultures across six continents support our theory. Interestingly, GDP per capita is related to life satisfaction, but not to pay satisfaction. Individual income is related to both life and pay satisfaction. Neither GDP nor income is related to Happiness. Our theoretical model across three GDP groups offers new discoveries: In high GDP entities, “high income” not only reduces aspirations—“Rich, Motivator, and Power,” but also promotes stewardship behavior—“Budget, Give/Donate, and Contribute” and appreciation of “Achievement.” After controlling income, we demonstrate the bright side of Monetary Intelligence: Low love of money motive but high stewardship behavior define Monetary Intelligence. “Good apples enjoy good quality of life in good barrels.” This notion adds another explanation to managers’ low magnitude of dishonesty in entities with high Corruption Perceptions Index. In low GDP entities, high income is related to poor Budgeting skills and escalated Happiness. These managers experience equal satisfaction with pay and life. We add a new vocabulary to the conversation of monetary intelligence, income, GDP, happiness, subjective well-being, good and bad apples and barrels, corruption, and behavioral ethics. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...) by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

Among the many tensions in Leibniz’s philosophical system is his tendency to invoke both mechanistic and teleological explanations. Jonathan Bennett, typicalof recent Leibniz commentators, attempts to relieve this difficulty by arguing that teleology for Leibniz is theological posturing and philosophically thin; such a doctrine does not serve to explain the relationship between teleology and mechanism. I argue that Leibniz’s appeal to final causality is both inextricably grounded in his wider metaphysic and helpful in understanding the preconditions for causality in general. (...) To this end I defend the two following claims: 1) It is in part Leibniz’s theory of contingency, and not exclusively theological concerns, that leads him to conclude that the laws of nature must admit of teleological explanations. 2) The finality of the laws of nature, coupled with one of Leibniz’s most promising arguments against occasionalism, are together sufficient to show that teleology must play a role in explanations of the activity of all genuine substances. (shrink)

Among the many tensions in Leibniz’s philosophical system is his tendency to invoke both mechanistic and teleological explanations. Jonathan Bennett, typicalof recent Leibniz commentators, attempts to relieve this difficulty by arguing that teleology for Leibniz is theological posturing and philosophically thin; such a doctrine does not serve to explain the relationship between teleology and mechanism. I argue that Leibniz’s appeal to final causality is both inextricably grounded in his wider metaphysic and helpful in understanding the preconditions for causality in general. (...) To this end I defend the two following claims: 1) It is in part Leibniz’s theory of contingency, and not exclusively theological concerns, that leads him to conclude that the laws of nature must admit of teleological explanations. 2) The finality of the laws of nature, coupled with one of Leibniz’s most promising arguments against occasionalism, are together sufficient to show that teleology must play a role in explanations of the activity of all genuine substances. (shrink)

Jeong Jae-gyu (鄭載圭, 1843-1911) was a scholar in the late Joseon Dynasty who contributed to the solidification and formation of the Nosa school (蘆沙學派) through the publication of Nosajib (蘆沙集) and active lecture activities based on the independent acceptance of his teacher, Ki Jeong-jin (奇正鎭). He explained the concept of intelligence based on the definitions of Shen Gui-bao (沈貴珤), an early scholar of the Yuan Dynasty, and even though the volume was not large, he presented a deep analysis and a (...) unique interpretation. Few Joseon Neo-Confucian scholars had explained the concept of intelligence based on Shen Gui-bao, so his attempts are unique. Shen Gui-bao explained, “the Intelligence includes the axis of change in the real world where the heavenly principles are inherent and has a mirror to judge the conflicts of human affairs”. Hu Bing-wen (胡炳文) used the explanation to justify his concept of intelligence. However, since intelligence is a principle, and the “axis of change in the real world” is also a principle, an unreasonable proposition of ‘principle includes principle’ can be established according to Shen Gui-bao’s definitions. Therefore, Kim Chang-hyeop (金昌協) and others criticized Shen Gui-bao, saying that such a proposition cannot be accepted. However, in the 19th century, Lee Hang-ro (李恒老) and Lee Jin-sang (李震相) showed a positive attitude toward Shen Gui-bao’s definitions. Jeong Jae-gyu, who partially accepted the influence of Lee Jin-sang, reaffirmed the fundamental position of intelligence through the phrase “Intelligence includes the axis of change in the real world”, and emphasized that intelligence is the basis for both moral judgment and the principle of perception. Furthermore, in the Neo-Confucian system, intelligence corresponds to a quiet virtue, so Jung Jae-gyu’s emphasis on it might lead to a theory of cultivation centered on solitude (靜), which can be confirmed in questions and answers shared with Ki Jung-jin, his writings, and poems. (shrink)

A key theme in the historiographical work of Machamer has been the ways that motion is made intelligible through explanatory means of natural motion and models of the simple machines such as the lever and pendulum. One way of spelling out the explanatory value of these strategies is through the concept of equilibrium. Natural motion and simple machines allow the simplification of complex problems in terms of self-evident, intelligible equilibrium conditions. This chapter connects the theme of equilibrium and natural motion (...) across Machamer’s work on mechanisms and mechanical explanation, on Aristotle, Galileo, Descartes and Newton, and on the pendulum and mental models. Just as equilibrium can be found within science, it also becomes a model of intelligibility for doing history and philosophy of science: a normative but objective representation of the important properties of science. (shrink)

In exploring the nature of psychological explanation, this book looks at how psychologists theorize about the human ability to calculate, to speak a language and the like. It shows how good theorizing explains or tries to explain such abilities as perception and cognition. It recasts the familiar explanations of "intelligence" and "cognitive capacity" as put forward by philosophers such as Fodor, Dennett, and others in terms of a theory of explanation that makes established doctrine more intelligible to professionals (...) and their students.In particular, the book shows that vestigial adherence to the positivists' D-N model has distorted the view of philosophers of science about what psychologists (and biologists) do and has masked the real nature of explanation. Major sections in the book cover Analysis and Subsumption; Functional Analysis; Understanding Cognitive Capacities; and Historical Reflections.Robert Cummins is Associate Professor of Philosophy at the University of Illinois, Chicago Circle. A Bradford Book. (shrink)

In Aristotle's teleological view of the world, natural things come to be and are present for the sake of some function or end. Whereas much of recent scholarship has focused on uncovering the physical underpinnings of Aristotle's teleology and its contrasts with his notions of chance and necessity, this book examines Aristotle's use of the theory of natural teleology in producing explanations of natural phenomena. Close analyses of Aristotle's natural treatises and his Posterior Analytics show what methods are used for (...) the discovery of functions or ends that figure in teleological explanations, how these explanations are structured, and how well they work in making sense of phenomena. The book will be valuable for all who are interested in Aristotle's natural science, his philosophy of science, and his biology. (shrink)

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast (...) to the right to explanation of specific automated decisions claimed elsewhere, the GDPR only mandates that data subjects receive meaningful, but properly limited, information (Articles 13-15) about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems, what we term a ‘right to be informed’. Further, the ambiguity and limited scope of the ‘right not to be subject to automated decision-making’ contained in Article 22 (from which the alleged ‘right to explanation’ stems) raises questions over the protection actually afforded to data subjects. These problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless. We propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018. (shrink)

Review of Henk de Regt's "Understanding Scientific Understanding".

In books such as The World Within the World and The Anthropic Cosmological Principle, astronomer John Barrow has emerged as a leading writer on our efforts to understand the universe. Timothy Ferris, writing in The Times Literary Supplement of London, described him as "a temperate and accomplished humanist, scientist, and philosopher of science--a man out to make a contribution, not a show." Now Barrow offers the general reader another fascinating look at modern physics, as he explores the quest for a (...) single, unifying theory that will unlock nature's secrets. Theories of Everything is more than a history of science, more than a popular report on recent research and discoveries. Barrow provides a reflective, intelligent commentary on what a true Theory of Everything would be--its ingredients, its limitations, and what it could tell us about the universe. Never before, he writes, have physicists been so confident and so eager in the hunt for this "cosmic Rosetta Stone," as he calls it: "a single all-embracing picture of all the laws of nature from which the inevitability of all things seen must follow with unimpeachable logic." He lays out eight essential ingredients for a Theory of Everything and then explores each in turn, tracing how our knowledge has developed and how scientific discovery relates to our changing philosophy and religious thought in each area. Some of these ingredients are obvious--the laws of nature must be explained, for example, as well as its organizing principles--but others may be surprising, such as broken symmetries and selection biases. A Theory of Everything must account for the fact that the universe is "messy and complicated," he tells us, and for the limitations imposed by the questions we ask and the information we can obtain. The key lies in the remarkable capacity of mathematics to express the fundamental workings of the physical world--a language that the human mind is uniquely equipped to understand and manipulate. Barrow examines what mathematics actually is and describes how it makes the universe intelligible and provides a path to the underlying coherence in nature--which has led, in fact, to arguments that the universe itself is a vast computer. Yet even the most complete theory, even the most comprehensive mathematical explanation, cannot account for the uncomputable varieties of human experience and thought. "No non-poetic account of reality," he writes, "can be complete." In a field where the authorities converse in equations and mathematical notations, John Barrow speaks with the voice of thoughtful and knowledgeable humanist. Written with eloquence and expertise, Theories of Everything establishes a new perspective on humanity's efforts to explain the universe. (shrink)