This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases on machine learning algorithms to do this work. In this article, I draw a distinction between three forms of opacity: opacity as intentional corporate or state (...) secrecy, opacity as technical illiteracy, and an opacity that arises from the characteristics of machine learning algorithms and the scale required to apply them usefully. The analysis in this article gets inside the algorithms themselves. I cite existing literatures in computer science, known industry practices, and do some testing and manipulation of code as a form of lightweight code audit. I argue that recognizing the distinct forms of opacity that may be coming into play in a given application is a key to determining which of a variety of technical and non-technical solutions could help to prevent harm. (shrink)

We argue that mechanistic models elaborated by machine learning cannot be explanatory by discussing the relation between mechanistic models, explanation and the notion of intelligibility of models. We show that the ability of biologists to understand the model that they work with severely constrains their capacity of turning the model into an explanatory model. The more a mechanistic model is complex, the less explanatory it will be. Since machine learning increases its performances when more components are added, then it generates (...) models which are not intelligible, and hence not explanatory. (shrink)

Ernest Sosa's A Virtue Epistemology, Vol. I is arguably the single-most important monograph to be published in analytic epistemology in the last ten years. Sosa, the first in the field to employ the notion of intellectual virtue – in his ground-breaking ‘The Raft and the Pyramid’– is the leading proponent of reliabilist versions of virtue epistemology. In A Virtue Epistemology, he deftly defends an externalist account of animal knowledge as apt belief, argues for a distinction between animal and reflective knowledge, (...) contends that rational intuition is an intellectual virtue ; and offers responses to dream scepticism, the problem of the criterion and the value problem. Nearly all of these arguments are new, albeit consistent with Sosa's earlier work; that is, consistent with two notable exceptions. First, c ontra Sosa's ‘Replies’ in Ernest Sosa and His Critics, A Virtue Epistemology explicitly contends that safety is not required for animal knowledge. Second, unlike Sosa's Knowledge in Perspective, which arguably construes the intellectual virtues as merely instrumentally valuable, A Virtue Epistemology explicitly contends that the intellectual virtues are instrumentally and constitutively valuable. Best read in conjunction with the above monographs and Epistemic Justification, A Virtue Epistemology is mandatory reading for epistemologists and graduate students in the field. It will rightly set the standard for debates in analytic epistemology for years to come.I will summarize and raise objections to two key conclusions that are unique to A Virtue Epistemology: the ‘kaleidoscope-perceiver’ has animal knowledge but lacks reflective knowledge; unlike the k-perceiver, the ordinary perceiver has reflective knowledge. My objections …. (shrink)

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...) affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms. (shrink)

A wide-ranging study of the central concepts in epistemology - belief, truth and knowledge. Professor Armstrong offers a dispositional account of general beliefs and of knowledge of general propositions. Belief about particular matters of fact are described as structures in the mind of the believer which represent or 'map' reality, while general beliefs are dispositions to extend the 'map' or introduce casual relations between portions of the map according to general rules. 'Knowledge' denotes the reliability of such beliefs as representations (...) of reality. Within this framework Professor Armstrong offers a distinctive account of many of the main questions in general epistemology - the relations between beliefs and language, the notions of proposition, concept and idea, the analysis of truth, the varieties of knowledge, and the way in which beleifs and knowledge are supported by reasons. The book as a whole if offered as a contribution to a naturalistic account of man. (shrink)

As Aristotle stated, scientific explanation is based on deductive argument--yet, Wesley C. Salmon points out, not all deductive arguments are qualified explanations. The validity of the explanation must itself be examined. _Four Decades of Scientific Explanation_ provides a comprehensive account of the developments in scientific explanation that transpired in the last four decades of the twentieth century. It continues to stand as the most comprehensive treatment of the writings on the subject during these years. Building on the historic 1948 essay (...) by Carl G. Hempel and Paul Oppenheim, "Studies in the Logic of Explanation,” which introduced the deductive-nomological model on which most work on scientific explanation was based for the following four decades, Salmon goes beyond this model's inherent basis of describing empirical knowledge to tells us “not only _what,_ but also _why_.” Salmon examines the predominant models in chronological order and describes their development, refinement, and criticism or rejection. _Four Decades of Scientific Explanation_ underscores the need for a consensus of approach and ongoing evaluations of methodology in scientific explanation, with the goal of providing a better understanding of natural phenomena. (shrink)

Knowledge and its Limits presents a systematic new conception of knowledge as a kind of mental stage sensitive to the knower's environment. It makes a major contribution to the debate between externalist and internalist philosophies of mind, and breaks radically with the epistemological tradition of analyzing knowledge in terms of true belief. The theory casts new light on such philosophical problems as scepticism, evidence, probability and assertion, realism and anti-realism, and the limits of what can be known. The arguments are (...) illustrated by rigorous models based on epistemic logic and probability theory. The result is a new way of doing epistemology and a notable contribution to the philosophy of mind. (shrink)

The paper investigates the ethics of information transparency (henceforth transparency). It argues that transparency is not an ethical principle in itself but a pro-ethical condition for enabling or impairing other ethical practices or principles. A new definition of transparency is offered in order to take into account the dynamics of information production and the differences between data and information. It is then argued that the proposed definition provides a better understanding of what sort of information should be disclosed and what (...) sort of information should be used in order to implement and make effective the ethical practices and principles to which an organisation is committed. The concepts of “heterogeneous organisation” and “autonomous computational artefact” are further defined in order to clarify the ethical implications of the technology used in implementing information transparency. It is argued that explicit ethical designs, which describe how ethical principles are embedded into the practice of software design, would represent valuable information that could be disclosed by organisations in order to support their ethical standing. (shrink)

Evidence-based medicine (EBM) has thus far failed to adequately account for the appropriate incorporation of other potential warrants for medical decision making into clinical practice. In particular, EBM has struggled with the value and integration of other kinds of medical knowledge, such as those derived from clinical experience or based on pathophysiologic rationale. The general priority given to empirical evidence derived from clinical research in all EBM approaches is not epistemically tenable. A casuistic alternative to EBM approaches recognizes that five (...) distinct topics, 1) empirical evidence, 2) experiential evidence, 3) pathophysiologic rationale, 4) patient goals and values, and 5) system features are potentially relevant to any clinical decision. No single topic has a general priority over any other and the relative importance of a topic will depend upon the circumstances of the particular case. The skilled clinician must weigh these potentially conflicting evidentiary and non-evidentiary warrants for action, employing both practical and theoretical reasoning, in order to arrive at the best choice for an individual patient. (shrink)

Ernest Sosa presents a new approach to the problems of knowledge and scepticism. He argues for two levels of knowledge, the animal and the reflective, each viewed as a distinctive human accomplishment. Sosa's virtue epistemology illuminates different varieties of scepticism, the nature and status of intuitions, and epistemic normativity.

We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...) explored. (shrink)

What modal relation must a fact bear to a belief in order for this belief to constitute knowledge of that fact? Externalists have proposed various answers, including some that combine externalism with contextualism. We shall find that various forms of externalism share a modal conception of “sensitivity” open to serious objections. Fortunately, the undeniable intuitive attractiveness of this conception can be explained through an easily confused but far preferable notion of “safety.” The denouement of our reflections, finally, will be to (...) show how replacing sensitivity with safety makes it possible to defend plain Moorean common sense against the spurious advantages over it claimed by skeptical, tracking, relevant-alternative, and contextualist accounts. (shrink)

The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...) argument for scientific realism akin to the argument that convinced twentieth-century physical scientists of the existence of atoms and molecules. To do justice to such notions as irreducibly statistical laws and statistical explanation, he offers a novel account of physical randomness. The transition from the "reviewed view" of scientific explanation to the causal/mechanical model requires fundamental rethinking of basic explanatory concepts. (shrink)

This is a short essay that presents what I take to be the main questions regarding the epistemology of disagreement.

If the decades of the forties through the sixties were dominated by discussion of Hempel's “covering law“ explication of explanation, that of the seventies was preoccupied with Salmon's “statistical relevance” conception, which emerged as the principal alternative to Hempel's enormously influential account. Readers of Wesley C. Salmon's Scientific Explanation and the Causal Structure of the World, therefore, ought to find it refreshing to discover that its author has not remained content with a facile defense of his previous investigations; on the (...) contrary, Salmon offers an original account of different kinds of explications, advances additional criticisms of various alternative theories, and elaborates a novel “two-tiered“ analysis of explanation that tacitly depends upon a “two-tiered” account of homogeneity. Indeed, if the considerations that follow are correct, Salmon has not merely refined his statistical relevance account but has actually abandoned it in favor of a “causal/mechanistic“ construction. This striking development suggests that the theory of explanation is likely to remain as lively an arena of debate in the eighties as it has been in the past. (shrink)

My aim in this paper is to develop and defend a novel answer to a question that has recently generated a considerable amount of controversy. The question concerns the normative significance of peer disagreement. Suppose that you and I have been exposed to the same evidence and arguments that bear on some proposition: there is no relevant consideration which is available to you but not to me, or vice versa. For the sake of concreteness, we might picture.

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. This (...) is a distinction between aspects of the same model. In molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analysing the discovery and characterization of restriction–modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in the cognitive disposition of the modeller towards the model: a modeller will look at a model as a ‘model of’ if interested in its explanatory force, or as a ‘model for’ if interested in the material manipulations it can possibly afford. (shrink)

To explain the phenomena in the world of our experience, to answer the question “why?” rather than only the question “what?”, is one of the foremost objectives of all rational inquiry; and especially, scientific research in its various branches strives to go beyond a mere description of its subject matter by providing an explanation of the phenomena it investigates. While there is rather general agreement about this chief objective of science, there exists considerable difference of opinion as to the function (...) and the essential characteristics of scientific explanation. In the present essay, an attempt will be made to shed some light on these issues by means of an elementary survey of the basic pattern of scientific explanation and a subsequent more rigorous analysis of the concept of law and of the logical structure of explanatory arguments. (shrink)

Mainstream epistemology is a highly theoretical and abstract enterprise. Traditional epistemologists rarely present their deliberations as critical to the practical problems of life, unless one supposes—as Hume, for example, did not—that skeptical worries should trouble us in our everyday affairs. But some issues in epistemology are both theoretically interesting and practically quite pressing. That holds of the problem to be discussed here: how laypersons should evaluate the testimony of experts and decide which of two or more rival experts is most (...) credible. It is of practical importance because in a complex, highly specialized world people are constantly confronted with situations in which, as comparative novices, they must turn to putative experts for intellectual guidance or assistance. It is of theoretical interest because the appropriate epistemic considerations are far from transparent; and it is not clear how far the problems lead to insurmountable skeptical quandaries. This paper does not argue for flat-out skepticism in this domain; nor, on the other hand, does it purport to resolve all pressures in the direction of skepticism. It is an exploratory paper, which tries to identify problems and examine some possible solutions, not to establish those solutions definitively. (shrink)

Since Edmund L. Gettier reminded us recently of a certain important inadequacy of the traditional analysis of "S knows that p," several attempts have been made to correct that analysis. In this paper I shall offer still another analysis (or a sketch of an analysis) of "S knows that p," one which will avert Gettier's problem. My concern will be with knowledge of empirical propositions only, since I think that the traditional analysis is adequate for knowledge of nonempirical truths.

Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...) required of an adequate mechanistic model. Mechanistic models are explanatory. (shrink)

How Doctors Think defines the nature and importance of clinical judgment. Although physicians make use of science, this book argues that medicine is not itself a science but rather an interpretive practice that relies on clinical reasoning. A physician looks at the patient's history along with the presenting physical signs and symptoms and juxtaposes these with clinical experience and empirical studies to construct a tentative account of the illness. How Doctors Think is divided into four parts. Part one introduces the (...) concept of medicine as a practice rather than a science; part two discusses the idea of causation; part three delves into the process of forming clinical judgment; and part four considers clinical judgment within the uncertain nature of medicine itself. In How Doctors Think, Montgomery contends that assuming medicine is strictly a science can have adverse side effects, and suggests reducing these by recognizing the vital role of clinical judgment. (shrink)