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Summary

What should we expect and demand of experts, given the authority vested in them and the gravity of decisions in areas such as science and technology policy? Risk-management is not a value-free science, and experts are not immune from damaging bias, from vested interests, or from error in their projections of benefits and risks in the application of science and technology to the real world. The concept of inductive risk concerns the seriousness of potential errors and accidents, or more generally of ‘getting it wrong’ in any inductive context of inquiry. The study of inductive risk involves the interplay between applied science/technology and different kinds of values (epistemic, but also moral, social, economic, etc.). This involves how risks are calculated and assigned, but also more generally how decisions are, and ought to be made. It can involve the relationships between scientific experts, business interests, policy-makers, and citizen stakeholders in decisions and policy-making that carries risk for those affected. The study of inductive risk as defined by leading authors in this area shares with science studies, broadly construed, that science is a legitimate and pressing site of debate as long as its implications are relevant to the public, and to public policy-making.

Key works

The roles of values in expertise has been a question of great concern at least since The Public and its Problems, Dewey 1927. Expertise may be vitally important for effective public decision-making, yet experts need to be held responsible to the epistemic authority they wield, and to specific risks of the policies and decisions they advise. Inductive risk is a concept first applied in an article “Science and Human Values” by Hempel 1965 which helps encapsulate a great deal of debate about the relationship between epistemic and non-epistemic values in science. Hempel allowed that because no evidence can establish a hypothesis with certainty, the acceptance of a hypothesis “carries with it the ‘inductive risk’” (92) that it may turn out to be incorrect. While articulating inductive risk as the risk of error in accepting or rejecting a hypothesis, Hempel’s view largely aligned with others including Levi (1962) and McMullen (1983), that value judgments attached to various outcomes or “utilities” in the application of science may be of practical and moral concern, but are not part of science proper: “the scientist is not called upon to make value judgments in their regard as part of his scientific work” (8). This view contrast with that of Richard Rudner (1953), that scientists qua scientists make value judgments. The insulation of scientific research from social values came under criticism from many in the latter half of the twentieth-century, as the “value-free” conception of science and scientific objectivity. Numerous post-positivist and feminist thinkers urged a re-thinking of that conception and of the cognitive/social value distinction (Rooney 1992; Longino 1990; Machamer and Douglas 1999; Intemann 2005; Mayo and Spanos (eds.) 2009; Elliott and Richards (eds.) 2017)). In an early paper in what would become voluminous work on inductive risk, “Inductive Risk and Values in Science”, Douglas 2000 argues that non-epistemic consequences of error “can and should be considered in the internal stages of science: choice of methodology, characterization of data, and interpretation of results” (559).  Since inductive risk arises whenever knowledge is inductively based, and there are often clear or potentially important consequences of getting it wrong, discussions of inductive risk become a hub for concerns with technology policy. In the article “Science, Values, and Citizens”, Douglas 2017 maintains that in societally relevant areas of science, a focus on inductive risk "opens the door to social and ethical values in the assessment of what counts as sufficient evidence for a claim” (93). Stephen John (2015) defends disentangling and excluding non-epistemic values in science; the argument from inductive risk does not undercut a rightly-conceived value-free conception of science. While the entanglements and attempted disentanglements of science and social values remains a matter of vigorous debate, numerous authors presently utilize the concept of inductive risk not only in regard to policy procedures, but also in articulating the different avenues for legitimate contestation of scientific claims, and in stimulating timely and more robust, multi-directional conversations over science and values.

[BROKEN REFERENCE: HEMSAHw]#DOUIRA
Introductions

Biddle, J.B. and Kukla, R. (2017), The Geography of Epistemic Risk. In Exploring Inductive Risk: Case Studies of Values in Science, K.C. Elliott and T. Richards (eds.). Oxford: Oxford university Press.

Douglas, H. (2009), Science, Policy, and the Value-Free Ideal. University of Pittsburgh Press, Pittsburg PA.

Elliott, Kevin C. (2013), Douglas on Values: From Indirect Roles to Multiple Goals, Studies in History and Philosophy of Science Part A 44 (3), 375-383.

Intemann, K. (2005), Feminism, Underdetermination, and Values in Science, Philosophy of Science, 72, 1001-1012.

Machamer, P. and Osbeck, L. (2004), The Social in the Epistemic. In Machamer, P. and Wolters, G. (eds.) Values, Science and Objectivity. University of Pittsburgh Press.

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  1. Risk-Limited Indulgent Permissivism.Guy Axtell - manuscript
    This paper argues for a view described as risk-limited indulgent permissivism. This term may be new to the epistemology of disagreement literature, but the general position denoted has many examples. The paper argues for the need for an epistemology for domains of controversial views (morals, philosophy, politics, and religion), and for the advantages of endorsing a risk-limited indulgent permissivism across these domains. It takes a double-edge approach in articulating for the advantages of interpersonal belief permissivism that is yet risk-limited: Advantages (...)
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  2. Problems of Religious Luck, chapter 2: The New Problem of Religious Luck.Guy Axtell - manuscript
    One main kind of etiological challenge to the well-foundedness of someone’s belief is the consideration that if you had a different education/upbringing, you would very likely accept different beliefs than you actually do. Although a person’s religious identity and attendant religious beliefs are usually the ones singled out as targets of such “contingency” or “epistemic location” arguments, it is clear that a person’s place and time has a conditioning effect in all domains of controversial views, and over all of what (...)
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  3. Problems of Religious Luck, Ch. 4: "We Are All of the Common Herd: Montaigne and the Psychology of our 'Importunate Presumptions'".Guy Axtell - forthcoming - In Problems of Religious Luck: Assessing the Limits of Reasonable Religious Disagreement.
    As we have seen in the transition form Part I to Part II of this book, the inductive riskiness of doxastic methods applied in testimonial uptake or prescribed as exemplary of religious faith, helpfully operationalizes the broader social scientific, philosophical, moral, and theological interest that people may have with problems of religious luck. Accordingly, we will now speak less about luck, but more about the manner in which highly risky cognitive strategies are correlated with psychological studies of bias studies and (...)
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  4. Problems of Religious Luck, Ch. 5: "Scaling the ‘Brick Wall’: Measuring and Censuring Strongly Fideistic Religious Orientation".Guy Axtell - forthcoming - In Problems of Religious Luck: Assessing the Limits of Reasonable Religious Disagreement.
    This chapter sharpens the book’s criticism of exclusivist responsible to religious multiplicity, firstly through close critical attention to arguments which religious exclusivists provide, and secondly through the introduction of several new, formal arguments / dilemmas. Self-described ‘post-liberals’ like Paul Griffiths bid philosophers to accept exclusivist attitudes and beliefs as just one among other aspects of religious identity. They bid us to normalize the discourse Griffiths refers to as “polemical apologetics,” and to view its acceptance as the only viable form of (...)
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  5. Problems of Religious Luck, Chapter 6: The Pattern Stops Here?Guy Axtell - forthcoming - In Problems of Religious Luck: Assessing the Limits of Reasonable Religious Disagreement.
    This book has argued that problems of religious luck, especially when operationalized into concerns about doxastic risk and responsibility, can be of shared interest to theologians, philosophers, and psychologists. We have pointed out counter-inductive thinking as a key feature of fideistic models of faith, and examined the implications of this point both for the social scientific study of fundamentalism, and for philosophers’ and theologians’ normative concerns with the reasonableness of a) exclusivist attitudes to religious multiplicity, and b) theologically-cast but bias-mirroring (...)
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  6. Problems of Religious Luck, Chapter 3: "Enemy in the Mirror: The Need for Comparative Fundamentalism".Guy Axtell - forthcoming - In Problems of Religious Luck: Assessing the Limits of Reasonable Religious Disagreement.
    Measures of inductive risk and of safety-principle violation help us to operationalize concerns about theological assertions or a sort which, as we saw in Part I, aggravate or intensify problems of religious luck. Our overall focus in Part II will remain on a) responses to religious multiplicity, and b) sharply asymmetrical religious trait-ascriptions to religious insiders and outsiders. But in Part II formal markers of inductive norm violation will supply an empirically-based manner of distinguishing strong from moderate fideism. As we (...)
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  7. Risk and Precaution.Stephen John - forthcoming - Public Health Ethics: Key Concepts and Issues in Policy and Practice:67--84.
  8. Are Algorithms Value-Free? Feminist Theoretical Virtues in Machine Learning.Gabbrielle Johnson - forthcoming - Journal Moral Philosophy.
    As inductive decision-making procedures, the inferences made by machine learning programs are subject to underdetermination by evidence and bear inductive risk. One strategy for overcoming these challenges is guided by a presumption in philosophy of science that inductive inferences can and should be value-free. Applied to machine learning programs, the strategy assumes that the influence of values is restricted to data and decision outcomes, thereby omitting internal value-laden design choice points. In this paper, I apply arguments from feminist philosophy of (...)
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  9. Kevin C. Elliott. A Tapestry of Values: An Introduction to Values in Science. [REVIEW]David Montminy & François Papale - forthcoming - Hopos: The Journal of the International Society for the History of Philosophy of Science.
  10. Kevin C. Elliott and Ted Richards , Exploring Inductive Risk. Case Studies of Values in Science.Federica Russo - forthcoming - Hopos: The Journal of the International Society for the History of Philosophy of Science.
  11. Inductive Risk and Values in Composite Outcome Measures.Roger Stanev - forthcoming - In Kevin Elliot & Ted Richards (eds.), Exploring Inductive Risk. Oxford University Press.
    The use of composite outcomes is becoming widespread in clinical trials. By combining individual outcome measures into a composite, researchers claim a composite can increase statistical precision and trial efficiency, expediting the trial by reducing sample size and cost, and consequently enabling researchers to answer questions that could not otherwise be answered. Another rationale given for using a composite is that it provides a measure of the net effect of the intervention that is more patient-relevant than any single outcome measure. (...)
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  12. Inductive Risk, Understanding, and Opaque Machine Learning Models.Emily Sullivan - forthcoming - Philosophy of Science:1-13.
    Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this paper, I argue that non-epistemic values give shape to the ML opacity problem even if we keep researcher interests fixed. Treating ML models as an instance of doing model-based science to explain and understand phenomena reveals that there is (i) an external opacity problem, where the presence of inductive risk imposes higher standards on externally validating models, and (ii) an internal opacity (...)
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  13. On Predicting Recidivism: Epistemic Risk, Tradeoffs, and Values in Machine Learning.Justin B. Biddle - 2022 - Canadian Journal of Philosophy 52 (3):321-341.
    Recent scholarship in philosophy of science and technology has shown that scientific and technological decision making are laden with values, including values of a social, political, and/or ethical character. This paper examines the role of value judgments in the design of machine-learning systems generally and in recidivism-prediction algorithms specifically. Drawing on work on inductive and epistemic risk, the paper argues that ML systems are value laden in ways similar to human decision making, because the development and design of ML systems (...)
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  14. Clinical Decisions Using AI Must Consider Patient Values.Jonathan Birch, Kathleen A. Creel, Abhinav K. Jha & Anya Plutynski - 2022 - Nature Medicine 28:229–232.
    Built-in decision thresholds for AI diagnostics are ethically problematic, as patients may differ in their attitudes about the risk of false-positive and false-negative results, which will require that clinicians assess patient values.
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  15. Engaging with science, values, and society: introduction.Ingo Brigandt - 2022 - Canadian Journal of Philosophy 52 (3):223–226.
    Philosophical work on science and values has come to engage with the concerns of society and of stakeholders affected by science and policy, leading to socially relevant philosophy of science and socially engaged philosophy of science. This special issue showcases instances of socially relevant philosophy of science, featuring contributions on a diversity of topics by Janet Kourany, Andrew Schroeder, Alison Wylie, Kristen Intemann, Joyce Havstad, Justin Biddle, Kevin Elliott, and Ingo Brigandt.
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  16. Inductive risk: does it really refute value-freedom?Markus Dressel - 2022 - Theoria 37 (2):181-207.
    The argument from inductive risk is considered to be one of the strongest challenges for value-free science. A great part of its appeal lies in the idea that even an ideal epistemic agent—the “perfect scientist” or “scientist qua scientist”—cannot escape inductive risk. In this paper, I scrutinize this ambition by stipulating an idealized Bayesian decision setting. I argue that inductive risk does not show that the “perfect scientist” must, descriptively speaking, make non-epistemic value-judgements, at least not in a way that (...)
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  17. Inconvenient Truth and Inductive Risk in Covid-19 Science.Eli I. Lichtenstein - 2022 - Philosophy of Medicine 3 (1):1-25.
    To clarify the proper role of values in science, focusing on controversial expert responses to Covid-19, this article examines the status of (in)convenient hypotheses. Polarizing cases like health experts downplaying mask efficacy to save resources for healthcare workers, or scientists dismissing “accidental lab leak” hypotheses in view of potential xenophobia, plausibly involve modifying evidential standards for (in)convenient claims. Societies could accept that scientists handle (in)convenient claims just like nonscientists, and give experts less political power. Or societies could hold scientists to (...)
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  18. William James on Risk, Efficacy, and Evidentialism.P. D. Magnus - 2022 - Episteme 19 (1):146-158.
    William James’ argument against William Clifford in The Will to Believe is often understood in terms of doxastic efficacy, the power of belief to influence an outcome. Although that is one strand of James’ argument, there is another which is driven by ampliative risk. The second strand of James’ argument, when applied to scientific cases, is tantamount to what is now called the Argument from Inductive Risk. Either strand of James’ argument is sufficient to rebut Clifford's strong evidentialism and show (...)
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  19. The scope of inductive risk.P. D. Magnus - 2022 - Metaphilosophy 53 (1):17-24.
    The Argument from Inductive Risk (AIR) is taken to show that values are inevitably involved in making judgements or forming beliefs. After reviewing this conclusion, I pose cases which are prima facie counterexamples: the unreflective application of conventions, use of black-boxed instruments, reliance on opaque algorithms, and unskilled observation reports. These cases are counterexamples to the AIR posed in ethical terms as a matter of personal values. Nevertheless, it need not be understood in those terms. The values which load a (...)
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  20. Reading the Cold War through Outer Space: The Past and Future of Outer Space.Yang Immanuel Pachankis - 2022 - International Journal of Scientific and Engineering Research 13 (6):826-829.
    The article takes a history based technical analysis on the governing activities by outer space laws. It outlined the spirit of the outer space law and treaty by the scientific development of the earth’s orbits & solar objects’ orbits. It focuses on the contamination of outer space by human activities in large scale structure with concluding scientific evidence. It analyzed geopolitical conflicts in terms of satellite technologies. They are analyzed based on the utility-science dichotomy, and the subject(s) that ultimately benefit (...)
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  21. When Do Non-Epistemic Values Play an Epistemically Illegitimate Role in Science? How to Solve One Half of the New Demarcation Problem.Alexander Reutlinger - 2022 - Studies in the History and Philosophy of Science 92:152-161.
    Solving the “new demarcation problem” requires a distinction between epistemically legitimate and illegitimate roles for non-epistemic values in science. This paper addresses one ‘half’ (i.e. a sub-problem) of the new demarcation problem articulated by the Gretchenfrage: What makes the role of a non-epistemic value in science epistemically illegitimate? I will argue for the Explaining Epistemic Errors (EEE) account, according to which the epistemically illegitimate role of a non-epistemic value is defined via an explanatory claim: the fact that an epistemic agent (...)
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  22. Thinking about Values in Science: Ethical versus Political Approaches.S. Andrew Schroeder - 2022 - Canadian Journal of Philosophy 52 (3):246-255.
    Philosophers of science now broadly agree that doing good science involves making non-epistemic value judgments. I call attention to two very different normative standards which can be used to evaluate such judgments: standards grounded in ethics and standards grounded in political philosophy. Though this distinction has not previously been highlighted, I show that the values in science literature contain arguments of each type. I conclude by explaining why this distinction is important. Seeking to determine whether some value-laden determination meets substantive (...)
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  23. Public Trust in Science: Exploring the Idiosyncrasy-Free Ideal.Marion Boulicault & S. Andrew Schroeder - 2021 - In Kevin Vallier & Michael Weber (eds.), Social Trust. Routledge.
    What makes science trustworthy to the public? This chapter examines one proposed answer: the trustworthiness of science is based at least in part on its independence from the idiosyncratic values, interests, and ideas of individual scientists. That is, science is trustworthy to the extent that following the scientific process would result in the same conclusions, regardless of the particular scientists involved. We analyze this "idiosyncrasy-free ideal" for science by looking at philosophical debates about inductive risk, focusing on two recent proposals (...)
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  24. The Descriptive, the Normative, and the Entanglement of Values in Science.Matthew J. Brown - 2021 - In Heather Douglas & Ted Richards (eds.), Science, Values, and Democracy: The 2016 Descartes Lectures. Tempe, AZ, and Washington, DC: Consortium for Science, Policy & Outcomes, Arizona State University. pp. 51-65.
    Heather Douglas has helped to set the standard for twenty-first century discussions in philosophy of science on the topics of values in science and science in democracy. Douglas’s work has been part of a movement to bring the question of values in science back to center of the field and to focus especially on policy-relevant science. This first chapter, on the pervasive entanglement of science and values, includes an improved and definitive statement of the argument from inductive risk, which she (...)
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  25. Inductive risk in macroeconomics: Natural Rate Theory, monetary policy, and the Great Canadian Slump.Gabriele Contessa - 2021 - Economics and Philosophy 37 (3):353-375.
    This paper has two goals. The first is to fill a gap in the literature on inductive risk by exploring the relevance of the notion of inductive risk to macroeconomics and monetary policy. The second goal is to draw some general lessons about inductive risk from the case discussed. The most important of these lessons is that the notion of inductive risk is no less relevant to the relationship between the proximate and distal goals of policy than it is to (...)
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  26. On the mitigation of inductive risk.Gabriele Contessa - 2021 - European Journal for Philosophy of Science 11 (3):1-14.
    The last couple of decades have witnessed a renewed interest in the notion of inductive risk among philosophers of science. However, while it is possible to find a number of suggestions about the mitigation of inductive risk in the literature, so far these suggestions have been mostly relegated to vague marginal remarks. This paper aims to lay the groundwork for a more systematic discussion of the mitigation of inductive risk. In particular, I consider two approaches to the mitigation of inductive (...)
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  27. Wishful Intelligibility, Black Boxes, and Epidemiological Explanation.Marina DiMarco - 2021 - Philosophy of Science 88 (5):824-834.
    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 (...)
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  28. How strong is the argument from inductive risk?Tobias Henschen - 2021 - European Journal for Philosophy of Science 11 (3):1-23.
    The argument from inductive risk, as developed by Rudner and others, famously concludes that the scientist qua scientist makes value judgments. The paper aims to show that trust in the soundness of the argument is overrated – that philosophers who endorse its conclusion fail to refute two of the most important objections that have been raised to its soundness: Jeffrey’s objection that the genuine task of the scientist is to assign probabilities to hypotheses, and Levi’s objection that the argument is (...)
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  29. Well-ordered science and public trust in science.Gürol Irzik & Faik Kurtulmus - 2021 - Synthese 198 (Suppl 19):4731-4748.
    Building, restoring and maintaining well-placed trust between scientists and the public is a difficult yet crucial social task requiring the successful cooperation of various social actors and institutions. Kitcher’s takes up this challenge in the context of liberal democratic societies by extending his ideal model of “well-ordered science” that he had originally formulated in his. However, Kitcher nowhere offers an explicit account of what it means for the public to invest epistemic trust in science. Yet in order to understand how (...)
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  30. Objectivity in Science.Stephen John - 2021 - Cambridge University Press.
    Objectivity is a key concept both in how we talk about science in everyday life and in the philosophy of science. This Element explores various ways in which recent philosophers of science have thought about the nature, value and achievability of objectivity. The first section explains the general trend in recent philosophy of science away from a notion of objectivity as a 'view from nowhere' to a focus on the relationship between objectivity and trust. Section 2 discusses the relationship between (...)
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  31. The epistemic consequences of pragmatic value-laden scientific inference.Adam P. Kubiak & Paweł Kawalec - 2021 - European Journal for Philosophy of Science 11 (2):1-26.
    In this work, we explore the epistemic import of the value-ladenness of Neyman-Pearson’s Theory of Testing Hypotheses by reconstructing and extending Daniel Steel’s argument for the legitimate influence of pragmatic values on scientific inference. We focus on how to properly understand N-P’s pragmatic value-ladenness and the epistemic reliability of N-P. We develop an account of the twofold influence of pragmatic values on N-P’s epistemic reliability and replicability. We refer to these two distinguished aspects as “direct” and “indirect”. We discuss the (...)
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  32. Call for Written evidence - Risk Assessment and Risk Planning.Marie Oldfield - 2021 - UK Government Risk Enquiry.
  33. Well-Founded Belief and the Contingencies of Epistemic Location.Guy Axtell - 2020 - In Patrick Bondy & J. Adam Carter (eds.), Well Founded Belief: New Essays on the Epistemic Basing Relation. London: Routledge. pp. 275-304.
    A growing number of philosophers are concerned with the epistemic status of culturally nurtured beliefs, beliefs found especially in domains of morals, politics, philosophy, and religion. Plausibly, worries about the deep impact of cultural contingencies on beliefs in these domains of controversial views is a question about well-foundedness: Does it defeat well-foundedness if the agent is rationally convinced that she would take her own reasons for belief as insufficiently well-founded, or would take her own belief as biased, had she been (...)
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  34. Science and Moral Imagination: A New Ideal for Values in Science.Matthew J. Brown - 2020 - Pittsburgh: University of Pittsburgh Press.
    The idea that science is or should be value-free, and that values are or should be formed independently of science, has been under fire by philosophers of science for decades. Science and Moral Imagination directly challenges the idea that science and values cannot and should not influence each other. Matthew J. Brown argues that science and values mutually influence and implicate one another, that the influence of values on science is pervasive and must be responsibly managed, and that science can (...)
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  35. Enzyme classification and the entanglement of values and epistemic standards.Stijn Conix - 2020 - Studies in History and Philosophy of Science Part A 84:37-45.
    This paper investigates the case of enzyme classification to evaluate different ideals for regulating values in science. I show that epistemic and non-epistemic considerations are inevitably and untraceably entangled in enzyme classification, and argue that this has significant implications for the two main kinds of views on values in science, namely, Epistemic Priority Views and Joint Satisfaction Views. More precisely, I argue that the case of enzyme classification poses a problem for the usability and descriptive accuracy of these two views. (...)
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  36. Integrating Heather Douglas’ Inductive Risk Framework with an Account of Scientific Evidence: Why and How?O. Çağlar Dede - 2020 - Perspectives on Science 28 (6):737-763.
    I examine how Heather Douglas’ account of values in science applies to the assessment of actual cases of scientific practice. I focus on the case of applied toxicologists’ acceptance of molecular evidence-gathering methods and evidential sources. I demonstrate that a set of social and institutional processes plays a philosophically significant role in changing toxicologists’ inductive risk judgments about different kinds of evidence. I suggest that Douglas’ inductive risk framework can be integrated with a suitable account of evidence, such as Helen (...)
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  37. Are Experts Representative of Non-Experts? Elective Modernism, Aspects of Representation, and the Argument from Inductive Risk.Jaana Eigi - 2020 - Perspectives on Science 28 (4):459-481.
    The approach to expert communities and political representation of non-experts in Harry Collins and Robert Evans’ elective modernism reflects the conviction that experts are not representative of ordinary citizens. I use an analysis of aspects of representation and the argument from inductive risk to argue that experts can be seen as representative of non-experts, when we understand representation as resemblance based on shared social perspectives and acknowledge the inevitable involvement of such perspectives in decisions under inductive risk. This, in turn, (...)
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  38. Relevance and risk: How the relevant alternatives framework models the epistemology of risk.Georgi Gardiner - 2020 - Synthese 199 (1-2):481-511.
    The epistemology of risk examines how risks bear on epistemic properties. A common framework for examining the epistemology of risk holds that strength of evidential support is best modelled as numerical probability given the available evidence. In this essay I develop and motivate a rival ‘relevant alternatives’ framework for theorising about the epistemology of risk. I describe three loci for thinking about the epistemology of risk. The first locus concerns consequences of relying on a belief for action, where those consequences (...)
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  39. Algorithmic bias: on the implicit biases of social technology.Gabbrielle M. Johnson - 2020 - Synthese 198 (10):9941-9961.
    Often machine learning programs inherit social patterns reflected in their training data without any directed effort by programmers to include such biases. Computer scientists call this algorithmic bias. This paper explores the relationship between machine bias and human cognitive bias. In it, I argue similarities between algorithmic and cognitive biases indicate a disconcerting sense in which sources of bias emerge out of seemingly innocuous patterns of information processing. The emergent nature of this bias obscures the existence of the bias itself, (...)
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  40. Defending a Risk Account of Scientific Objectivity.Inkeri Koskinen - 2020 - British Journal for the Philosophy of Science 71 (4):1187-1207.
    When discussing scientific objectivity, many philosophers of science have recently focused on accounts that can be applied in practice when assessing the objectivity of something. It has become clear that in different contexts, objectivity is realized in different ways, and the many senses of objectivity recognized in the recent literature seem to be conceptually distinct. I argue that these diverse ‘applicable’ senses of scientific objectivity have more in common than has thus far been recognized. I combine arguments from philosophical discussions (...)
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  41. Trust and Distributed Epistemic Labor‎.Boaz Miller & Ori Freiman - 2020 - In Judith Simon (ed.), The Routledge Handbook on Trust and Philosophy. New York: Routledge. pp. ‎341-353‎.
    This chapter explores properties that bind individuals, knowledge, and communities, together. Section ‎‎1 introduces Hardwig’s argument from trust in others’ testimonies as entailing that trust is the glue ‎that binds individuals into communities. Section 2 asks “what grounds trust?” by exploring assessment ‎of collaborators’ explanatory responsiveness, formal indicators such as affiliation and credibility, ‎appreciation of peers’ tacit knowledge, game-theoretical considerations, and the role moral character ‎of peers, social biases, and social values play in grounding trust. Section 3 deals with establishing (...)
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  42. Catastrophic risk.H. Orri Stefánsson - 2020 - Philosophy Compass 15 (11):1-11.
    Catastrophic risk raises questions that are not only of practical importance, but also of great philosophical interest, such as how to define catastrophe and what distinguishes catastrophic outcomes from non-catastrophic ones. Catastrophic risk also raises questions about how to rationally respond to such risks. How to rationally respond arguably partly depends on the severity of the uncertainty, for instance, whether quantitative probabilistic information is available, or whether only comparative likelihood information is available, or neither type of information. Finally, catastrophic risk (...)
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  43. Risk Assessment of Biological Asset Mortgage Loans of China’s New Agricultural Business Entities.Shuzhen Zhu, Yutao Chen & Wenwen Wang - 2020 - Complexity 2020:1-12.
    The large-scale proliferation of China’s new type of agricultural entities has given rise to a higher demand for funds. Farmers have insufficient effective collateral, which makes it difficult for them to obtain sufficient loans. Chinese financial institutions have developed a biological asset mortgage loan business to cope with this situation. China has not considered biological mortgages but has been using real estate and asset mortgage models with strong realizability. This innovative financial business has achieved positive results since it was attempted, (...)
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  44. An Inductive Risk Account of the Ethics of Belief.Guy Axtell - 2019 - Philosophy. The Journal of the Higher School of Economic 3 (3):146-171.
    From what norms does the ethics of belief derive its oughts, its attributions of virtues and vices, responsibilities and irresponsibilities, its permissioning and censuring? Since my inductive risk account is inspired by pragmatism, and this method understands epistemology as the theory of inquiry, the paper will try to explain what the aims and tasks are for an ethics of belief, or project of guidance, which best fits with this understanding of epistemology. More specifically, this chapter approaches the ethics of belief (...)
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  45. Problems of Religious Luck: Assessing the Limits of Reasonable Religious Disagreement.Guy Axtell - 2019 - Lanham, MD, USA & London, UK: Lexington Books/Rowman & Littlefield.
    To speak of being religious lucky certainly sounds odd. But then, so does “My faith holds value in God’s plan, while yours does not.” This book argues that these two concerns — with the concept of religious luck and with asymmetric or sharply differential ascriptions of religious value — are inextricably connected. It argues that religious luck attributions can profitably be studied from a number of directions, not just theological, but also social scientific and philosophical. There is a strong tendency (...)
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  46. Book ReviewsKevin C. Elliott and Ted Richards (eds.), Exploring Inductive Risk: Case Studies of Values in Science (Oxford: Oxford University Press, 2017), 312 pages. isbn: 9780190467715/9780190467722. Hardback/Paperback: $99.00/$39.95. [REVIEW]Zina B. Ward - 2019 - Journal of Moral Philosophy 16 (6):769-772.
  47. Risk and Values in Science: A Peircean View.Daniele Chiffi & Ahti-Veikko Pietarinen - 2019 - Axiomathes 29 (4):329-346.
    Scientific evidence and scientific values under risk and uncertainty are strictly connected from the point of view of Peirce’s pragmaticism. In addition, economy and statistics play a key role in both choosing and testing hypotheses. Hence we may show also the connection between the methodology of the economy of research and statistical frequentism, both originating from pragmaticism. The connection is drawn by the regulative principles of synechism, tychism and uberty. These principles are values that have both epistemic and non-epistemic dimension. (...)
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  48. Ethics of the scientist qua policy advisor: inductive risk, uncertainty, and catastrophe in climate economics.David Frank - 2019 - Synthese:3123-3138.
    This paper discusses ethical issues surrounding Integrated Assessment Models (IAMs) of the economic effects of climate change, and how climate economists acting as policy advisors ought to represent the uncertain possibility of catastrophe. Some climate economists, especially Martin Weitzman, have argued for a precautionary approach where avoiding catastrophe should structure climate economists’ welfare analysis. This paper details ethical arguments that justify this approach, showing how Weitzman’s “fat tail” probabilities of climate catastrophe pose ethical problems for widely used IAMs. The main (...)
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  49. What Is Epistemic Public Trust in Science?Gürol Irzik & Faik Kurtulmus - 2019 - British Journal for the Philosophy of Science 70 (4):1145-1166.
    We provide an analysis of the public's having warranted epistemic trust in science, that is, the conditions under which the public may be said to have well-placed trust in the scientists as providers of information. We distinguish between basic and enhanced epistemic trust in science and provide necessary conditions for both. We then present the controversy regarding the connection between autism and measles–mumps–rubella vaccination as a case study to illustrate our analysis. The realization of warranted epistemic public trust in science (...)
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  50. The Politics of Certainty: The Precautionary Principle, Inductive Risk and Procedural Fairness.Stephen John - 2019 - Ethics, Policy and Environment 22 (1):21-33.
    This paper re-interprets the precautionary principle as a ‘social epistemic rule’. First, it argues that sometimes policy-makers should act on claims which have not been scientifically established....
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