Comparative constructions form two classes, those that permit direct comparisons (comparisons of measurements as in Seymour is taller than he is wide) and those that only allow indirect comparisons (comparisons of relative positions on separate scales as in Esme is more beautiful than Einstein is intelligent). In contrast with other semantic theories, this paper proposes that the interpretation of the comparative morpheme remains the same whether it appears in sentences that compare individuals directly or indirectly. To develop a unified account, (...) I suggest that all comparisons (whether in terms of height, intelligence or beauty) involve a scale of universal degrees that are isomorphic to the rational (fractional) numbers between 0 and 1. Crucial to a unified treatment, the connection between the individuals being compared and universal degrees involves two steps. First individuals are mapped to a value on a primary scale that ranks individuals with respect to the gradable property (whether it be height, beauty or intelligence). Second, the value on the primary scale is mapped to a universal degree that encodes the value’s relative position on the primary scale. Direct comparison results if measurements such as seven feet participate in the primary scale (as in Seven feet is tall). Otherwise the result is an indirect comparison. (shrink)

This paper discusses comparison classes—sets that relativize the interpretation of gradable adjectives, often specified with for-clauses as in John is smart for a linguist. Such a discussion ultimately lends support to the thesis that scales, degrees, measure functions, and linear orders are grammatically derived from more basic relations between individuals. Three accounts of comparison classes are compared and evaluated. The first proposes that such classes serve as an argument to a function that determines a standard of comparison. The second maintains (...) that these classes restrict the domain of a measure function used to map entities to degrees. The third proposes that these classes limit the kind of individuals that participate in a binary relation; this relation is then used in the construction of a scale and a measure function. It is this third account that is most consistent with the empirical data. It can explain how comparison classes fix a standard of comparison, induce presuppositions concerning the comparative subjects, and induce incommensurability in comparative constructions. (shrink)

Algorithmic systems and predictive analytics play an increasingly important role in various aspects of modern life. Scholarship on the moral ramifications of such systems is in its early stages, and much of it focuses on bias and harm. This paper argues that in understanding the moral salience of algorithmic systems it is essential to understand the relation between algorithms, autonomy, and agency. We draw on several recent cases in criminal sentencing and K–12 teacher evaluation to outline four key ways in (...) which issues of agency, autonomy, and respect for persons can conflict with algorithmic decision-making. Three of these involve failures to treat individual agents with the respect they deserve. The fourth involves distancing oneself from a morally suspect action by attributing one’s decision to take that action to an algorithm, thereby laundering one’s agency. (shrink)

ABSTRACT: So far in this book, we have examined algorithmic decision systems from three autonomy-based perspectives: in terms of what we owe autonomous agents (chapters 3 and 4), in terms of the conditions required for people to act autonomously (chapters 5 and 6), and in terms of the responsibilities of agents (chapter 7). -/- In this chapter we turn to the ways in which autonomy underwrites democratic governance. Political authority, which is to say the ability of a government to exercise (...) power, may be justifiable or not. Whether it is justified and how it can come to be justified is a question of political legitimacy. Political legitimacy is another way in which autonomy and responsibility are linked. This relationship is the basis of the current chapter, and it is important in understanding the moral salience of algorithmic systems. We will draw the connection as follows. We begin, in section 8.1, by describing two uses of technology: crime predicting technology used to drive policing practices and social media technology used to influence elections (including by Cambridge Analytica and by the Internet Research Agency). In section 8.2 we consider several views of legitimacy and argue for a hybrid version of normative legitimacy based on one recently offered by Fabienne Peter. In section 8.3 we will explain that the connection between political legitimacy and autonomy is that legitimacy is grounded in legitimating processes, which are in turn based on autonomy. Algorithmic systems—among them PredPol and the Cambridge Analytica-Facebook-Internet Research Agency amalgam—can hinder that legitimation process and conflict with democratic legitimacy, as we argue in section 8.4. We will conclude by returning to several cases that serve as through-lines to the book: Loomis, Wagner, and Houston Schools. -/- The link below is to an open-access copy of the chapter. (shrink)

ABSTRACT: One important criticism of algorithmic systems is that they lack transparency. Such systems can be opaque because they are complex, protected by patent or trade secret, or deliberately obscure. In the EU, there is a debate about whether the General Data Protection Regulation (GDPR) contains a “right to explanation,” and if so what such a right entails. Our task in this chapter is to address this informational component of algorithmic systems. We argue that information access is integral for respecting (...) autonomy, and transparency policies should be tailored to advance autonomy. -/- To make this argument we distinguish two facets of agency (i.e., capacity to act). The first is practical agency, or the ability to act effectively according to one’s values. The second is what we call cognitive agency, which is the ability to exercise what Pamela Hieronymi calls “evaluative control” (i.e., the ability to control our affective states, such as beliefs, desires, and attitudes). We argue that respecting autonomy requires providing persons sufficient information to exercise evaluative control and properly interpret the world and one’s place in it. We draw this distinction out by considering algorithmic systems used in background checks, and we apply the view to key cases involving risk assessment in criminal justice decisions and K-12 teacher evaluation. -/- The link below is to an open access version of the chapter. (shrink)

Algorithms influence every facet of modern life: criminal justice, education, housing, entertainment, elections, social media, news feeds, work… the list goes on. Delegating important decisions to machines, however, gives rise to deep moral concerns about responsibility, transparency, freedom, fairness, and democracy. Algorithms and Autonomy connects these concerns to the core human value of autonomy in the contexts of algorithmic teacher evaluation, risk assessment in criminal sentencing, predictive policing, background checks, news feeds, ride-sharing platforms, social media, and election interference. Using these (...) case studies, the authors provide a better understanding of machine fairness and algorithmic transparency. They explain why interventions in algorithmic systems are necessary to ensure that algorithms are not used to control citizens' participation in politics and undercut democracy. This title is also available as Open Access on Cambridge Core. (shrink)

When agents insert technological systems into their decision-making processes, they can obscure moral responsibility for the results. This can give rise to a distinct moral wrong, which we call “agency laundering.” At root, agency laundering involves obfuscating one’s moral responsibility by enlisting a technology or process to take some action and letting it forestall others from demanding an account for bad outcomes that result. We argue that the concept of agency laundering helps in understanding important moral problems in a number (...) of recent cases involving automated, or algorithmic, decision-systems. We apply our conception of agency laundering to a series of examples, including Facebook’s automated advertising suggestions, Uber’s driver interfaces, algorithmic evaluation of K-12 teachers, and risk assessment in criminal sentencing. We distinguish agency laundering from several other critiques of information technology, including the so-called “responsibility gap,” “bias laundering,” and masking. (shrink)

New media (highly interactive digital technology for creating, sharing, and consuming information) affords users a great deal of control over their informational diets. As a result, many users of new media unwittingly encapsulate themselves in epistemic bubbles (epistemic structures, such as highly personalized news feeds, that leave relevant sources of information out (Nguyen forthcoming)). Epistemically paternalistic alterations to new media technologies could be made to pop at least some epistemic bubbles. We examine one such alteration that Facebook has made in (...) an effort to fight fake news and conclude that it is morally permissible. We further argue that many epistemically paternalistic policies can (and should) be a perennial part of the internet information environment. (shrink)

This paper examines the practice of using predictive systems to lengthen the prison sentences of convicted persons when the systems forecast a higher likelihood of re-offense or re-arrest. There has been much critical discussion of technologies used for sentencing, including questions of bias and opacity. However, there hasn’t been a discussion of whether this use of predictive systems makes sense in the first place. We argue that it does not by showing that there is no plausible theory of punishment that (...) supports it. (shrink)

This paper has two aims. The first is to explain a type of wrong that arises when agents obscure responsibility for their actions. Call it “agency laundering.” The second is to use the concept of agency laundering to understand the underlying moral issues in a number of recent cases involving algorithmic decision systems. From the Proceedings of the 14th International Conference, iConference 2019, Washington D.C., March 31-April 3, 2019.

In the so-called reverse proportional reading :53, 1997), the truth conditions of statements of the form many/few \\ appear to make reference to the ratio of the individuals that are in the extensions of both \ and \ to the individuals that are in the extension of \. The analysis of such readings is controversial. One prominent approach assumes they are a symptom of many and few making reference to a context dependent standard of comparison. We observe that this initially (...) attractive approach systematically undergenerates, failing to capture pervasive reverse proportionality in environments that remove context dependency of the standard. Instead, we propose that reverse proportionality in such cases can arise from the underspecification of the measure function underlying the meanings of many and few. (shrink)

In the so-called reverse proportional reading :53, 1997), the truth conditions of statements of the form many/few \\ appear to make reference to the ratio of the individuals that are in the extensions of both \ and \ to the individuals that are in the extension of \. The analysis of such readings is controversial. One prominent approach assumes they are a symptom of many and few making reference to a context dependent standard of comparison. We observe that this initially (...) attractive approach systematically undergenerates, failing to capture pervasive reverse proportionality in environments that remove context dependency of the standard. Instead, we propose that reverse proportionality in such cases can arise from the underspecification of the measure function underlying the meanings of many and few. (shrink)

In the so-called reverse proportional reading :53, 1997), the truth conditions of statements of the form many/few \\ appear to make reference to the ratio of the individuals that are in the extensions of both \ and \ to the individuals that are in the extension of \. The analysis of such readings is controversial. One prominent approach assumes they are a symptom of many and few making reference to a context dependent standard of comparison. We observe that this initially (...) attractive approach systematically undergenerates, failing to capture pervasive reverse proportionality in environments that remove context dependency of the standard. Instead, we propose that reverse proportionality in such cases can arise from the underspecification of the measure function underlying the meanings of many and few. (shrink)

We argue that an essential element of understanding the moral salience of algorithmic systems requires an analysis of the relation between algorithms and agency. We outline six key ways in which issues of agency, autonomy, and respect for persons can conflict with algorithmic decision-making.

Psychometrics firms such as Cambridge Analytica (CA) and troll factories such as the Internet Research Agency (IRA) have had a significant effect on democratic politics, through narrow targeting of political advertising (CA) and concerted disinformation campaigns on social media (IRA) (U.S. Department of Justice 2019; Select Committee on Intelligence, United States Senate 2019; DiResta et al. 2019). It is natural to think that such activities manipulate individuals and, hence, are wrong. Yet, as some recent cases illustrate, the moral concerns with (...) these activities cannot be reduced simply to the effects they have on individuals. Rather, we will argue, the wrongness of these activities relates to the threats they present to the legitimacy of political orders. This occurs primarily through a mechanism we call “emergent manipulation,” rather than through the sort of manipulation that involves specific individuals. (shrink)

Computer simulations show that an unstructured neural-network model [Shultz, T. R., & Bale, A. C. (2001). Infancy, 2, 501–536] covers the essential features␣of infant learning of simple grammars in an artificial language [Marcus, G. F., Vijayan, S., Bandi Rao, S., & Vishton, P. M. (1999). Science, 283, 77–80], and generalizes to examples both outside and inside of the range of training sentences. Knowledge-representation analyses confirm that these networks discover that duplicate words in the sentences are nearly identical and that (...) they use this near-identity relation to distinguish sentences that are consistent or inconsistent with a familiar grammar. Recent simulations that were claimed to show that this model did not really learn these grammars [Vilcu, M., & Hadley, R. F. (2005). Minds and Machines, 15, 359–382] confounded syntactic types with speech sounds and did not perform standard statistical tests of results. (shrink)

From Wodehouse to the White House: A Corpus-Assisted Study of Play, Fantasy and Dramatic Incongruity in Comic Writing and Laughter-Talk In this paper I consider two discourse types, one written and literary, the other spoken and semi-conversational, in an attempt to discover if there are any similarities in the ways in which humour is generated in such apparently diverse forms of communication. The first part of the paper is concerned with the explicitly comic prose of P. G. Wodehouse, whilst in (...) the second part of the paper, we investigate the laughter-talk, defined as the talk preceding and provoking, intentionally or otherwise, an episode of laughter, occurring during press briefings held at the White House during the Clinton era and the subsequent Bush administration. Both studies, by employing corpus analysis techniques together with detailed discourse reading, integrate quantitative and qualitative approaches to the respective data sets. (shrink)

ABSTRACTSome political ads used in the 2016 U.S. election evoked feelings colloquially known as being moved to tears. We conceptualise this phenomenon as a positive social emotion that appraises and motivates communal relations, is accompanied by physical sensations, and often labelled metaphorically. We surveyed U.S. voters in the fortnight before the 2016 U.S. election. Selected ads evoked the emotion completely and reliably, but in a partisan fashion: Clinton voters were moved to tears by three selected Clinton ads, and (...) Trump voters were moved to tears by two Trump ads. Viewers were much less moved by ads of the candidate they did not support. Being moved to tears predicted intention to vote for the candidate depicted. We conclude that some contemporary political advertising is able to move its audience to tears, and thereby motivates support. (shrink)

I propose to consider the question, "Can machines think?" This should begin with definitions of the meaning of the terms "machine" and "think." The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous, If the meaning of the words "machine" and "think" are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to (...) the question, "Can machines think?" is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the 'imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart front the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B. We now ask the question, "What will happen when a machine takes the part of A in this game?" Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, "Can machines think?". (shrink)

This chapter spells out in detail how Kant’s thinking about logic during the critical period shapes the account of philosophy that he gives in the Critiques. Tolley explores Kant’s motivations behind his formation of the idea of a new “transcendental” logic, drawing out in particular how he means to differentiate it from the traditional “merely formal” approaches to logic, insofar as transcendental logic investigates not just the basic forms of the activity of thinking but also its basic contents. Kant’s understanding (...) of both of these logics directly factor into the first Critique’s more general project of the critique of reason in particular, as not just a capacity for a certain kind of thinking (inferring), but as a possible source of a priori cognition. (shrink)

Text explaining in accordance to Sanskrit grammar; select usage of words in commentary of Brahmasūtra by Śaṅkarācārya.

A growing amount of media is paid for by its consumers through their very consumption of it. Typically, this new media is web-based and paid for by advertising. It includes the services offered by Facebook, Instagram, Snapchat, and YouTube. We offer an ethical assessment of the attention economy, the market where attention is exchanged for new media. We argue that the assessment has ethical implications for how the attention economy should be regulated. To conduct the assessment, we employ two heuristics (...) for evaluating markets. One is the “harm” criterion, which relates to whether the market tends to engender extremely harmful outcomes for individuals or society as a whole. The other is the “agency” criterion, which relates not to the outcomes of the market, but rather, to whether it somehow reflects or has its source in weakened agency. We argue that the attention economy animates concerns with respect to both criteria and that new media should be subject to the same sort of regulation as other harmful, addictive products. (shrink)

This Element offers a new account of the philosophical significance of logical empiricism that relies on the past forty years of literature reassessing the project. It argues that while logical empiricism was committed to empiricism and did become tied to the trajectory of analytic philosophy, neither empiricism nor logical analysis per se was the deepest philosophical commitment of logical empiricism. That commitment was, rather, securing the scientific status of philosophy, bringing philosophy into a scientific conception of the world.

Why do scientists do experiments? What do their experiments reveal? Scientifically, can we decide what to believe? Is evolution a scientific theory? Such apparently simple questions are brilliantly investigated by celebrated philosopher and professor Alan Musgrave in order to interrogate the worldviews we inhabit - and their consequences. Musgrave brings to these questions an expansive historical knowledge, provoking readers to enter the now-discredited belief-systems of earlier ages in order to compare these with their own beliefs. Discursive, entertaining, and provocative, (...) Secular Sermons contains fourteen essays by Musgrave - New Zealand's leading contemporary philosopher - examining the basic assumptions of science, religion, and mathematics. The book is an insightful introduction to the philosophical thought of Aristotle, Bacon, Copernicus, Galileo, Newton, Herschel, Darwin, and Einstein, among others. It puts modern science in a broader historical perspective and offers an entertaining introduction to the philosophical paradigm of Critical Rationalism. (shrink)

Misunderstanding Science? offers a challenging new perspective on the public understanding of science. In so doing, it also challenges existing ideas of the nature of science and its relationships with society. Its analysis and case presentation are highly relevant to current concerns over the uptake, authority, and effectiveness of science as expressed, for example, in areas such as education, medical/health practice, risk and the environment, technological innovation. Based on several in-depth case-studies, and informed theoretically by the sociology of scientific knowledge, (...) the book shows how the public understanding of science questions raises issues of the epistemic commitments and institutional structures which constitute modern science. It suggests that many of the inadequacies in the social integration and uptake of science might be overcome if modern scientific institutions were more reflexive and open about the implicit normative commitments embedded in scientific cultures. (shrink)

A number of findings in the field of machine learning have given rise to questions about what it means for automated scoring- or decisionmaking systems to be fair. One center of gravity in this discussion is whether such systems ought to satisfy classification parity (which requires parity in accuracy across groups, defined by protected attributes) or calibration (which requires similar predictions to have similar meanings across groups, defined by protected attributes). Central to this discussion are impossibility results, owed to Kleinberg (...) et al. (2016), Chouldechova (2017), and Corbett-Davies et al. (2017), which show that classification parity and calibration are often incompatible. This paper aims to argue that classification parity, calibration, and a newer, interesting measure called counterfactual fairness are unsatisfactory measures of fairness, offer a general diagnosis of the failure of these measures, and sketch an alternative approach to understanding fairness in machine learning. (shrink)

Katrina Forrester’s book poses a problem for any reviewer that, I suspect, will be reflected in the experience of its readers. Unusually, the author is equally.

Prediction-based decisions, which are often made by utilizing the tools of machine learning, influence nearly all facets of modern life. Ethical concerns about this widespread practice have given rise to the field of fair machine learning and a number of fairness measures, mathematically precise definitions of fairness that purport to determine whether a given prediction-based decision system is fair. Following Reuben Binns (2017), we take ‘fairness’ in this context to be a placeholder for a variety of normative egalitarian considerations. We (...) explore a few fairness measures to suss out their egalitarian roots and evaluate them, both as formalizations of egalitarian ideas and as assertions of what fairness demands of predictive systems. We pay special attention to a recent and popular fairness measure, counterfactual fairness, which holds that a prediction about an individual is fair if it is the same in the actual world and any counterfactual world where the individual belongs to a different demographic group (cf. Kusner et al. (2018)). (shrink)

We are all concerned by the environmental threats facing us today. Environmental issues are a major area of concern for policy makers, industrialists and public groups of many different kinds. While science seems central to our understanding of such threats, the statements of scientists are increasingly open to challenge in this area. Meanwhile, citizens may find themselves labelled as "ignorant" in environmental matters. In Citizen Science Alan Irwin provides a much needed route through the fraught relationship between science, the (...) public and the environmental threat. (shrink)

Data-driven, decision-making technologies used in the justice system to inform decisions about bail, parole, and prison sentencing are biased against historically marginalized groups (Angwin, Larson, Mattu, & Kirchner 2016). But these technologies’ judgments—which reproduce patterns of wrongful discrimination embedded in the historical datasets that they are trained on—are well-evidenced. This presents a puzzle: how can we account for the wrong these judgments engender without also indicting morally permissible statistical inferences about persons? I motivate this puzzle and attempt an answer.

We offer an ethical assessment of the market for data used to generate what are sometimes called “consumer scores” (i.e., numerical expressions that are used to describe or predict people’s dispositions and behavior), and we argue that the assessment has ethical implications on how the market for consumer scoring data should be regulated. To conduct the assessment, we employ two heuristics for evaluating markets. One is the “harm” criterion, which relates to whether the market produces serious harms, either for participants (...) in the market, for third parties, or for society as a whole. The other is the “agency” criterion, which relates to whether participants understand the nature and significance of the exchanges they are making, if they can be guaranteed fair representation, or if there is differential need for the market’s good. We argue that consumer scoring data should be subject to the same sort of regulation as the older FICO credit scores. Although the movement in the 1990s that was aimed at regulating the FICO scores was not aimed at restraining a market per se, we argue that the reforms were underwritten by concerns about the same sorts of problems as those outlined by our heuristics. Therefore, consumer data should be subject to the same sort of regulation. (shrink)

Holm (2022) argues that a class of algorithmic fairness measures, that he refers to as the ‘performance parity criteria’, can be understood as applications of John Broome’s Fairness Principle. We argue that the performance parity criteria cannot be read this way. This is because in the relevant context, the Fairness Principle requires the equalization of actual individuals’ individual-level chances of obtaining some good (such as an accurate prediction from a predictive system), but the performance parity criteria do not guarantee any (...) such thing: the measures merely ensure that certain population-level ratios hold. (shrink)

A comprehensive, systematic, and historical collection of essays on Rudolf Carnap's philosophy and legacy, written by leading international experts. This volume provides a redressing of Carnap's place in the history of analytic philosophy, through his approach to metaphysics, values, politics, epistemology and philosophy of science.

How might social theory, public understanding of science and science policy best inform one another? What have been the key features of science-society relations in the modern world? How are we to re-think science-society relations in the context of globalization, hybridity and changing patterns of governance? This topical and unique book draws together the three key perspectives on science-society relations: public understanding of science, scientific and public governance, and social theory. The book presents a series of case studies (including the (...) debates on genetically modified foods and the AIDS movement in the USA) to discuss critically the ways in which social theorists, social scientists, and science policy makers deal with science-society relations. ‘Science' and 'society' combine in many complex ways. Concepts such as citizenship, expertise, governance, democracy and the public need to be re-thought in the context of contemporary concerns with globalization and hybridity. A radical new approach is developed and the notion of ethno-epistemic assemblage is used to articulate a new series of questions for the theorization, empirical study and politics of science-society relations. (shrink)

A conception of recognitional abilities and perceptual-discriminative abilities is deployed to make sense of how perceptual experiences enable us to make cognitive contact with objects and facts. It is argued that accepting the emerging view does not commit us to thinking that perceptual experiences are essentially relational, as they are conceived to be in disjunctivist theories. The discussion explores some implications for the theory of knowledge in general and, in particular, for the issue of how we can shed light on (...) the nature of knowledge is if we do not aim to provide conceptual analyses of knowledge in terms of true belief plus something else. Consideration is also given how we can best make sense of the practical value that knowledge has for us. (shrink)

I advocate a method that strives to interpret important historical figures in philosophy as presenting philosophical systems of thought. This kind of systematic interpretation, as I shall call it, begins with the supposition that the philosophy being interpreted is itself systematic. This sometimes requires recovering the obscured systematicity. Section I gives a positive characterization of systematic interpretations. Section II notes some of the special obstacles that these interpretations must overcome if they are to be successful. Section III gives a brief (...) sketch of how one might systematically approach Locke’s Essay Concerning Human Understanding. That text is a good test case because Locke professes systematicity, but historians have produced daunting arguments for the conclusion that the text fails to present a coherent system. (shrink)

Impermissivists hold that an agent with a given body of evidence has at most one rationally permitted attitude that she should adopt towards any particular proposition. Permissivists deny this, often motivating permissivism by describing scenarios that pump our intuitions that the agent could reasonably take one of several attitudes toward some proposition. We criticize the following impermissivist response: while it seems like any of that range of attitudes is permissible, what is actually required is the single broad attitude that encompasses (...) all of these single attitudes. While this might seem like an easy way to win over permissivists, we argue that this impermissivist response leads to an indefensible epistemology; permissive intuitions are not so easily co-opted. (shrink)