The problem of the reality and nature of novelty in the universe has long engaged the attention of philosophers. “There is nothing new under the sun” is one ancient weighty utterance. On the other hand, “you cannot step twice into the same river”, said Heraclitus, for in the interval between your first and second steps, the river has changed and you have changed. One recent attempt to analyze this problem and other affiliated problems, is the theory of emergence.

The ever-increasing application of algorithms to decision-making in a range of social contexts has prompted demands for algorithmic accountability. Accountable decision-makers must provide their decision-subjects with justifications for their automated system’s outputs, but what kinds of broader principles should we expect such justifications to appeal to? Drawing from political philosophy, I present an account of algorithmic accountability in terms of the democratic ideal of ‘public reason’. I argue that situating demands for algorithmic accountability within this justificatory framework enables us to (...) better articulate their purpose and assess the adequacy of efforts toward them. (shrink)

Kim’s causal exclusion argument purports to demonstrate that the non-reductive physicalist must treat mental properties (and macro-level properties in general) as causally inert. A number of authors have attempted to resist Kim’s conclusion by utilizing the conceptual resources of Woodward’s interventionist conception of causation. The viability of these responses has been challenged by Gebharter, who argues that the causal exclusion argument is vindicated by the theory of causal Bayesian networks (CBNs). Since the interventionist conception of causation relies crucially on CBNs (...) for its foundations, Gebharter’s argument appears to cast significant doubt on interventionism’s anti-reductionist credentials. In the present article, we both (1) demonstrate that Gebharter’s CBN-theoretic formulation of the exclusion argument relies on some unmotivated and philosophically significant assumptions (especially regarding the relationship between CBNs and the metaphysics of causal relevance), and (2) use Bayesian networks to develop a general theory of causal inference for multi-level systems that can serve as the foundation for an anti-reductionist interventionist account of causation.1. (shrink)

Platonism is the most pervasive philosophy of mathematics. Indeed, it can be argued that an inarticulate, half-conscious Platonism is nearly universal among mathematicians. The basic idea is that mathematical entities exist outside space and time, outside thought and matter, in an abstract realm. In the more eloquent words of Edward Everett, a distinguished nineteenth-century American scholar, "in pure mathematics we contemplate absolute truths which existed in the divine mind before the morning stars sang together, and which will continue to exist (...) there when the last of their radiant host shall have fallen from heaven." In What is Mathematics, Really?, renowned mathematician Rueben Hersh takes these eloquent words and this pervasive philosophy to task, in a subversive attack on traditional philosophies of mathematics, most notably, Platonism and formalism. Virtually all philosophers of mathematics treat it as isolated, timeless, ahistorical, inhuman. Hersh argues the contrary, that mathematics must be understood as a human activity, a social phenomenon, part of human culture, historically evolved, and intelligible only in a social context. Mathematical objects are created by humans, not arbitrarily, but from activity with existing mathematical objects, and from the needs of science and daily life. Hersh pulls the screen back to reveal mathematics as seen by professionals, debunking many mathematical myths, and demonstrating how the "humanist" idea of the nature of mathematics more closely resembles how mathematicians actually work. At the heart of the book is a fascinating historical account of the mainstream of philosophy--ranging from Pythagoras, Plato, Descartes, Spinoza, and Kant, to Bertrand Russell, David Hilbert, Rudolph Carnap, and Willard V.O. Quine--followed by the mavericks who saw mathematics as a human artifact, including Aristotle, Locke, Hume, Mill, Peirce, Dewey, and Lakatos. In his epilogue, Hersh reveals that this is no mere armchair debate, of little consequence to the outside world. He contends that Platonism and elitism fit well together, that Platonism in fact is used to justify the claim that "some people just can't learn math." The humanist philosophy, on the other hand, links mathematics with geople, with society, and with history. It fits with liberal anti-elitism and its historical striving for universal literacy, universal higher education, and universal access to knowledge and culture. Thus Hersh's argument has educational and political ramifications. Written by the co-author of The Mathematical Experience, which won the American Book Award in 1983, this volume reflects an insider's view of mathematical life, based on twenty years of doing research on advanced mathematical problems, thirty-five years of teaching graduates and undergraduates, and many long hours of listening, talking to, and reading philosophers. A clearly written and highly iconoclastic book, it is sure to be hotly debated by anyone with a passionate interest in mathematics or the philosophy of science. (shrink)

Part IV. About the author -- An amusing elementary example -- Annotated research bibliography -- Curriculum vitae -- List of articles -- Index -- Back Cover.

Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining and fairness, accountability and transparency machine learning, their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data on sensitive attributes such as gender, ethnicity, sexuality or disability needed to diagnose and mitigate emergent indirect discrimination-by-proxy, such (...) as redlining. Such organisations might also lack the knowledge and capacity to identify and manage fairness issues that are emergent properties of complex sociotechnical systems. This paper presents and discusses three potential approaches to deal with such knowledge and information deficits in the context of fairer machine learning. Trusted third parties could selectively store data necessary for performing discrimination discovery and incorporating fairness constraints into model-building in a privacy-preserving manner. Collaborative online platforms would allow diverse organisations to record, share and access contextual and experiential knowledge to promote fairness in machine learning systems. Finally, unsupervised learning and pedagogically interpretable algorithms might allow fairness hypotheses to be built for further selective testing and exploration. Real-world fairness challenges in machine learning are not abstract, constrained optimisation problems, but are institutionally and contextually grounded. Computational fairness tools are useful, but must be researched and developed in and with the messy contexts that will shape their deployment, rather than just for imagined situations. Not doing so risks real, near-term algorithmic harm. (shrink)

"This new collection of essays edited by Reuben Hersh contains frank facts and opinions from leading mathematicians, philosophers, sociologists, cognitive ...

McGee argues that it is sometimes reasonable to accept both x and x-> without accepting y->z, and that modus ponens is therefore invalid for natural language indicative conditionals. Here, we examine McGee's counterexamples from a Bayesian perspective. We argue that the counterexamples are genuine insofar as the joint acceptance of x and x-> at time t does not generally imply constraints on the acceptability of y->z at t, but we use the distance-based approach to Bayesian learning to show that applications (...) of modus ponens are nevertheless guaranteed to be successful in an important sense. Roughly, if an agent becomes convinced of the premises of a modus ponens argument, then she should likewise become convinced of the argument's conclusion. Thus we take McGee's counterexamples to disentangle and reveal two distinct ways in which arguments can convince. Any general theory of argumentation must take stock of both. (shrink)

Although excess blood collection has characterized U.S. national disasters, most dramatically in the case of September 11, periodic shortages of blood have recurred for decades. In response, I propose a new model of medical philanthropy, one that specifically uses charitable contributions to health care as blood donation incentives. I explain how the surge in blood donations following 9/11 was both transient and disaster-specific, failing to foster a greater continuing commitment to donate blood. This underscores the importance of considering blood donation (...) incentives. I defend charitable incentives as an alternative to financial incentives, which I contend would further extend neoliberal market values into health care. I explain my model's potential appeal to private foundations or public–private partnerships as a means for expanding both the pool of blood donors and the prosocial benefit of each act of blood donation. Finally I link my analysis to the empirical literature on blood donation incentives. (shrink)

Jim Joyce has argued that David Lewis’s formulation of causal decision theory is inadequate because it fails to apply to the “small world” decisions that people face in real life. Meanwhile, several authors have argued that causal decision theory should be developed such that it integrates the interventionist approach to causal modeling because of the expressive power afforded by the language of causal models, but, as of now, there has been little work towards this end. In this paper, I propose (...) a variant of Lewis’s causal decision theory that is intended to meet both of these demands. Specifically, I argue that Lewis’s causal decision theory can be rendered applicable to small world decisions if one analyzes his dependency hypotheses as causal hypotheses that depend on the interventionist causal modeling framework for their semantics. I then argue that this interventionist variant of Lewis’s causal decision theory is preferable to interventionist causal decision theories that purportedly generalize Lewis’s through the use of conditional probabilities. This is because Lewisian interventionist decision theory captures the causal decision theorist’s conviction that any correlation between what the agent does and cannot cause should be irrelevant to the agent’s choice, while purported generalizations do not. (shrink)

ArgumentDuring the second quarter of the nineteenth century, an argument raged about the identity of a small freshwater fish: was the parr a distinct species, or merely the young of the salmon? This “Parr Controversy” concerned both fishermen and ichthyologists. A central protagonist in the controversy was a man of ambiguous social and scientific status: a gamekeeper from Scotland named John Shaw. This paper examines Shaw’s heterogeneous practices and the reception of his claims by naturalists as he struggled to find (...) a footing on the “gradient of attributed competence” (Rudwick 1985). The case demonstrates the context-specific nature of expert-lay boundaries and identities and explores a range of material and linguistic resources available for negotiating them. Arguing for a view of Shaw’s trajectory as simultaneously one of being a “practical man” and of becoming a naturalist, the paper explores both the permeability of social hierarchies in knowledge production and their effective role in the regulation of competency. (shrink)

Name der Zeitschrift: Semiotica Jahrgang: 2014 Heft: 202 Seiten: 395-424.

Some revisionary ontologies are highly parsimonious: they posit far fewer entities than what we quantify over in ordinary discourse. The most radical examples are minimal ontologies, on which physical simples are the only things that exist. Highly parsimonious ontologies, and especially minimal ones, face the challenge of either accounting for the truth of our ordinary quantificational discourse, or paraphrasing such discourse away. Common strategies for addressing this challenge include classical reduction, paraphrase nihilism, and a distinction between ontological and existence commitments. (...) I argue, however, that these strategies are either implausible or fail to provide truth conditions consistent with minimal or parsimonious ontologies. I then discuss, defend, and suggest ways to strengthen an alternative framework for reduction, on which the sentences of reducing theories ground those of reducible theories. Relative to the other options for defending minimal ontology, a strengthened grounding-reductive approach can provide more defensible truth conditions for minimal ontology, better preserve scientific realist intuitions, set a more attainable standard for reduction, and allow our existence commitments to be more responsive to empirical evidence and scientific expertise. As a result, I argue that minimal ontology becomes more defensible—though not certain—on a grounding-reductive framework. But even if minimal ontology were wrong, the grounding-reductive framework makes other parsimonious but non-minimal ontologies more plausible. (shrink)

A particularly influential thesis about epistemic axiology is veritism: that true belief is the only basic, or fully non-derivative, epistemic value. One recent argument against veritism claims that the naturalness or joint-carvingness of beliefs is also a basic epistemic value. The basic epistemic value of naturalness is held to explain intuitions that true, natural beliefs have greater epistemic value than similar but unnatural beliefs. I argue that epistemic significance, rather than naturalness, can best explain any variations in the value of (...) natural versus unnatural beliefs. Against claims that significance itself undermines veritism, I defend an account of significance that explains why the epistemic value of significance derives entirely from the value of truth. The account also shows how significance can be grounded in multiple features, while still deriving all its value from that of truth. As a result, the epistemic value of natural beliefs offers little reason to abandon veritism, in the absence of stronger arguments favoring the basic epistemic value of naturalness. (shrink)

Much discussion of the ethics of algorithms has focused on harms to autonomy—especially harms stemming from manipulation. Nonetheless, although manipulation can often be harmful, we suggest that in certain contexts it may not impair autonomy. To fully assess the impact of algorithm design on autonomy, we argue for a need to move beyond a focus on manipulation towards a multidimensional account of autonomy itself. Drawing on the autonomy literature and recent data ethics, we propose a novel account which takes autonomy (...) to supervene on three distinct but related elements: agency, authenticity and individual control over decision-making. By distinguishing autonomy from control, the account can explain the variable effects of manipulation on user autonomy within algorithm-driven systems. In particular, it can explain why improving user control may improve autonomy in some contexts, while in other contexts—such as in some kinds of newsfeeds—certain algorithm designs that instead _reduce_ user control may nevertheless improve autonomy. As a result, the account can accommodate the sometimes convoluted interplay between control, autonomy, manipulation, and commercial versus prosocial design goals. (shrink)

The study of social change has neglected the dynamics motivating individuals to join mass movements. Particularly obscure is how apathetic people are transformed into social activists. Considering this problem the author suggests three stages of development through which the individual progresses in attaining a higher level of personal and social maturity. The first stage - dreaming -emerges when the individual aspires to change while wishing to avoid the risks involved. The second - the illusion of power - occurs when the (...) hunger for power and the fear of it are mediated. The third - real power - is promoted by the yearning for self-respect and social acceptance and is manifested by competence in gaining supremacy and actual experience in struggle. As a consequence of this process the individual advances from a subjective self-image to perceiving himself as a social being; society is humanized by the greater participation of individuals. (shrink)

There is no profession where social change receives more approbation and less application than psychiatry. It is considered salubrious for patients and clinicians alike. This zeal for the innovative has produced an amazing proliferation of therapies. Beyond this psychiatry even preempts a trailblazing role among the behavioral sciences for its evolutionary approach. Freud's social side has been resurrected and now it is acknowledged that the founding father devoted considerable attention to the social aspects of psychoanalysis. That this tendency is alive (...) and prospering is inferred from the emergence of psychohistory, which may even replace community psychiatry—whose lustre has faded —as an example. However, before the profession is crowned with laurel, it might be well to determine whether this appraisal is apparent or real. A more critical analysis seems to indicate that psychiatry has incorporated social influences—up to a point. At first the social component was given consideration. (shrink)

Meek and Glymour use the graphical approach to causal modeling to argue that one and the same norm of rational choice can be used to deliver both causal-decision-theoretic verdicts and evidential-decision-theoretic verdicts. Specifically, they argue that if an agent maximizes conditional expected utility, then the agent will follow the causal decision theorist’s advice when she represents herself as intervening, and will follow the evidential decision theorist’s advice when she represents herself as not intervening. Since Meek and Glymour take no stand (...) on whether agents should represent themselves as intervening, they provide more general advice than standard causal decision theorists and evidential decision theorists. But I argue here that even Meek and Glymour’s advice is not sufficiently general. This is because their advice is not sensitive to the distinct ways in which agents can fail to intervene, and there are decision-making contexts in which agents can reasonably have non-extreme confidence that they are intervening. I then show that the most natural extension of Meek and Glymour’s framework fails, but offer a generalization of my “Interventionist Decision Theory” that does not suffer from the same problems. (shrink)

There are cases of ineffable learning — i. e., cases where an agent learns something, but becomes certain of nothing that she can express — where it is rational to update by Jeffrey conditionalization. But there are likewise cases of ineffable learning where updating by Jeffrey conditionalization is irrational. In this paper, we first characterize a novel class of cases where it is irrational to update by Jeffrey conditionalization. Then we use the d-separation criterion to develop a causal understanding of (...) when and when not to Jeffrey conditionalize that bars updating by Jeffrey conditionalization in these cases. Finally, we reflect on how the possibility of so-called “unfaithful” causal systems bears on the normative force of the causal updating norm that we advocate. (shrink)

It is explained that, in the sense of the sociologist Erving Goffman, mathematics has a front and a back. Four pervasive myths about mathematics are stated. Acceptance of these myths is related to whether one is located in the front or the back.

There are two distinct meanings to ‘mathematical proof’. The connection between them is an unsolved problem. The first step in attacking it is noticing that it is an unsolved problem.

G.A. Cohen’s value conservatism entails that we ought to preserve some existing sources of value in lieu of more valuable replacements, thereby repudiating maximizing consequentialism. Cohen motivates value conservatism through illustrative cases. The consequentialist, however, can explain many Cohen-style cases by taking extrinsic properties, such as historical significance, to be sources of final value. Nevertheless, it may be intuitive that there’s stronger reason to preserve than to promote certain sources of value, especially historically significant things. This motivates an argument that (...) the weights of our reasons to preserve such things are especially strong relative to the amounts of value they bear. The value conservative can then explain these intuitions in non-consequentialist terms. There may be reason to preserve historically significant things as a matter of recognition respect for a cultural and historical heritage, or because it is virtuous to cultivate the right kind of connection with such a heritage. (shrink)