ALS: C. Buckner

Cameron Buckner, Department of Philosophy, University of Houston

The new DoGMA of Empiricism: Deep Learning and Domain-General Faculties

Abstract: Deep learning is a research area in computer science that has over the last ten years produced a series of transformative breakthroughs in artificial intelligence—creating systems that can recognize complex objects in natural photographs as well or better than humans, defeat human grandmasters in strategy games such as chess, Go, shoji, or Starcraft II, create “deepfake” images or bodies of text that are sometimes indistinguishable from those produced by humans, and predict how proteins will fold more accurately than human microbiologists who have devoted their lives to the task. In this talk, I argue that these achievements were inspired by and in turn vindicate a moderately empiricist approach to cognition. However, this particular form of moderate empiricism has not been carefully articulated and defended in the computer science it has inspired. This has allowed deep learning’s rationalist critics—such as Gary Marcus, Melanie Mitchell, and Judea Pearl, as well as (in the previous generation of neural network criticism) Steven Pinker, Jerry Fodor, and Zenon Pylyshyn—to define the rules of the debate on their own terms. In this talk, I rebut this caricature by explicating the empiricism which undergirds most of these achievements. In particular, I interpret them in terms of a Domain-General Modular Architecture (DoGMA) for cognition centered on active, general-purpose, innate faculties like perception, memory, imagination, attention, and empathy. This empiricism echoes not the “radical” forms associated with behaviorism and logical positivism, but rather the more plausible forms defended by empiricist-leaning faculty psychologists such as Aristotle, Ibn Sina (Avicenna), John Locke, George Berkeley, David Hume, Adam Smith, and Sophie De Grouchy. If the debate between rationalism and empiricism is to remain a useful framework for critique of deep learning—even for rationalists who might still think it ultimately wrong-headed—we must stop framing it as a sequel to the oft-recited fable in which the valiant young Chomsky vanquished the dark lord Skinner, and see it instead as a novel empirical exploration of the most ambitious ideas offered by historical faculty empiricists.

To attend this lecture via Zoom please visit: https://pitt.zoom.us/webinar/register/WN_M_dQJZZaRS6oK371bkcE1A

Please Note: Non-Pitt individuals who want to attend our in-person talks must send an email in advance to Shoshi Burd-Baugh (shoshi.burdbaugh@pitt.edu) requesting Guest Building Access, or you will not be able to enter the Cathedral of Learning.

ALS: C. Lee

Carole Lee, Department of Philosophy, University of Washington

Institutional Racism in Science: Black-White Disparities in NIH Grant Review

Abstract: In the wake of the Black Lives Matter movement and disproportionately deadly impact of COVID-19 on communities of color, researchers have called for an end to institutional racism in scientific education, publishing, and funding. In this talk, I’ll discuss the challenge of institutional racism for canonical theories of the social structure of science, present recent research on Black-white disparities in funding and peer review scores for applicants submitting to the National Institutes of Health’s oldest and most commonly used funding mechanism (the R01 grant), and discuss some implications of this work on alternative proposals for funding science.

This lecture is an online only event, registration through Zoom is required. Register at: https://pitt.zoom.us/webinar/register/WN_nbEmUpYBS32h0cfC1hLvNw

ALS: E. Tal

Eran Tal, Department of Philosophy, McGill University

Measurement Outcomes as Best Predictors

Abstract: I argue for a view of measurement that treats measurement results (‘outcomes’) as predictors of patterns in data. The data in question may be records of instrument indications, such as thermometer readings, or future data, such as records of health outcomes. Not every predictor of a data pattern is a measurement outcome. Rather, successful measurement produces the best predictors in accordance with specific epistemic and practical criteria. Variations in these criteria account for differences among measurement approaches in the sciences. The best-predictor view clarifies, among other things, the justification for using measurement outcomes as evidence and the possibility of evaluating measurement accuracy.

Please note this talk has been moved online. Zoom registration here: https://pitt.zoom.us/webinar/register/WN_JfM_2QFyTvGd-ZOSFUrFYQ

ALS: C. Fine

Cordelia Fine, School of Historical and Philosophical Studies, University of Melbourne

Fairly Criticised or Dangerously Politicised? Conflicts in Sex/Gender Science

Conflicts in the Neuroscience of Sex Differences in the Human Brain

Investigations of sex differences in the human brain take place on politically sensitive terrain. While some scholars express concern that gendered biases and stereotypes remain embedded in scientific research, others are alarmed about the politicization of science. This talk sets out three kinds of conflicts that can arise in the neuroscience of sex differences: academic freedom versus gender equality; frameworks, background assumptions, and dominant methodologies; and inductive risk and social values. The boundaries between fair criticism and politicization are explored for each kind of conflict, pointing to ways in which the academic community can facilitate fair criticism while protecting against politicization.

Please Note: Non-Pitt individuals who want to attend our in-person talks must send an email in advance to Katie Labuda (kathleenlabuda@pitt.edu) requesting Guest Building Access, or you will not be able to enter the Cathedral of Learning.

If you prefer to watch on Zoom, please register here: https://pitt.zoom.us/webinar/register/WN_orNWpmHEQG-cIjfWWsj_2A

Cordelia Fine is a Professor in the School of Historical & Philosophical Studies at the University of Melbourne. She is the author of Delusions of Gender (a Guardian and London Evening Standard Book of the Year, a Washington Post Best Non-Fiction Book of the Year pick) and Testosterone Rex (winner of the Royal Society Science Book prize). Cordelia was also the recipient of the 2018 Edinburgh Medal, for her work in challenging gender bias in science and for her contributions to public debates about gender equality. Cordelia writes regularly for the popular media on the topic of gender, including for the New York Times, Financial Times, Guardian, Scientific American and Wall Street Journal.

ALS: J. Weatherall

Adolf Grünbaum 2022 Memorial Lecture

James Owen Weatherall, Department of Logic and Philosophy of Science, UC Irvine

The Philosophy Behind Dark Matter

Abstract: According to the Standard Model of Cosmology, more than 80% of the total matter in the universe is “dark”: it does not emit or reflect light, and so its presence and properties can be inferred, at least thus far, only through its gravitational influences. The inference from astrophysical and cosmological observations to the existence of dark matter has attracted considerable scrutiny from philosophers and philosophically-minded physicists, many of whom have argued that the case for dark matter is weaker than astrophysicists often suggest. Such authors tend to emphasize that there are plausible theoretical alternatives to dark matter available, suggesting that dark matter should be viewed as a tentative hypothesis whose status within the astrophysics and cosmology communities is not supported by the available evidence. In this talk, I will assess the current state of evidence for dark matter and argue that today, the case for dark matter is extremely strong — comparable to, or stronger than, the case for many other “unobservable” entities in 20th and 21st century physics. But as I will discuss, astrophysicists appear to have accepted dark matter as the most plausible hypothesis long before the most convincing contemporary evidence became available — suggesting that in an earlier phase of research, during the 1980s and 1990s, the sort of underdetermination noted by philosophers may have obtained after all. I will argue that physicists’ preference for dark matter during this period was influenced by their widespread commitment to certain views that might be thought of as a “philosophy of science”, concerning explanation, the nature of scientific theories, and principles of action and reaction (or cause and effect). I will then suggest that, in light of subsequent evidence, these philosophical commitments led physicists in the right direction, and address whether they can be expected to do so in other contemporary cases where the evidential situation is less clear.

If you prefer to watch on Zoom, please register here: https://pitt.zoom.us/webinar/register/WN_gGSpyfFNSwSmAgq0Qp_ifg

ALS: S. Green

Sara Green, University of Copenhagen

Philosophy of Science as Visioneering Assessment: The Case of Precision Medicine

ABSTRACT: Biomedical science is not only driven by theoretical achievements and technological developments, but also by visions for the future of medicine and society in general. By “visioneering”, I refer to the communication of visions by influential proponents within a given scientific field. While the visions are formulated in response to societal problems, visioneering is performative in the sense that promises for the future also shape political expectations and priorities. Since visioneering considers imageries of a not-yet realized future, the topic may be considered outside the scope of traditional philosophy of science analysis. Yet, insofar as such visions rest on identifiable epistemic and normative assumptions, philosophy of science has much to contribute to a critical assessment of science-based promises for the future. I highlight the method of visioneering assessment through an analysis of the epistemic and normative assumptions underlying current visions of precision medicine. Precision medicine capitalizes on technologies for genome sequencing and the increasing availability of digitalized health data. Precision medicine is expected to improve health outcomes and lower health care costs through predictions of disease development and treatment response for individual patients. I uncover the assumptions underlying the vision of precision and examine these in relation to existing evidence for the benefit and challenges of the proposed individualized strategies.

Due to COVID travel limitations, this Lecture will be held online on Zoom. Register here: https://pitt.zoom.us/webinar/register/WN_zJLKwI1FR-2H4VBGVgobuQ

ALS: L. Vesterlund

Lise Vesterlund, Andrew W. Mellon Professor of Economics, University of Pittsburgh

Gender Differences in Task Allocations: Cause and Effect

Women and men are shown to hold different work assignments, with women spending less time on work that advances their careers (promotable work) and more time on work that is unlikely to affect career advancement (non-promotable work). The talk reports on gender differences in behavior in settings involving competition and volunteering as contributing to differences in work assignments and explores the impact such differences have on compensation.

You have the option to attend in person, watch a YouTube livestream, or watch through Zoom.

The Zoom registration link is: https://pitt.zoom.us/webinar/register/WN_SQavqsIwQ9yUNzwHSQgcEg

ALS: J. Ioannidis

John Ioannidis
Stanford University

Reproducible and Useful Research: Changing Research Practices

ABSTRACT: Multiple lines of evidence suggest that a substantial segment of published research yields results that are not credible and that among the results that are credible a large share are not useful. The lecture will assess the scope of this evidence, it will present an appraisal of the current status across diverse scientific fields and will focus on solutions that have been proposed to enhance the credibility and usefulness of the research effort. Many of these solutions are already effective and have improved the performance of multiple scientific fields while others are more speculative, and they require careful testing before their adoption.

Zoom Registration Link: https://pitt.zoom.us/webinar/register/WN_ay_sN6T6QqC21Wv4O__W-Q

CANCELLED – ALS: S. Ruphy

THIS TALK HAS BEEN CANCELLED DUE TO COVID-19 CONCERNS

Science Policies and the Unpredictability of Scientific Inquiry

Stephanie Ruphy, University Jean Moulin

Abstract: What is the appropriate mode of setting the research agenda? The autonomy of science as regards the choice of its priorities is often defended on the ground that limiting scientists’ freedom to follow their curiosity hampers the epistemic fecundity of science. At the core of this traditional defence of scientific autonomy lies the ‘unpredictability argument’. In a nutshell: the development and the results of a research program being unpredictable, setting external (often utilitarian) goals is deemed counterproductive and vain: one should not attempt to predict the unpredictable. In this talk I will first challenge this argument by showing that a scientific inquiry whose agenda is set externally may actually favor the occurrence of the unexpected. Once epistemological room is made for external, interest-based guiding of scientific inquiry, I will discuss what kind of political constraints is legitimate on the setting of the research agenda.

ALS: Wayne Wu

Does Anyone Know What Attention Is?

Wayne Wu, Carnegie Mellon University

Center for the Neural Basis of Cognition

ABSTRACT: Despite debate and confusion in the empirical and philosophical literature, we have always known the answer: attention is selection for the guidance of behavior. I situate this proposal in light of a venerable schema for explanation of psychological capacities due to David Marr. I shall thereby present a concise, clear and up-to-date statement of a theory of attention as selection for guidance of action and explicate its empirical and philosophical implications. Accordingly, I argue for the following claims, among others: that the science of attention already endorses the claim that attention is selection for action, that this provides the correct computational theory for attention, that attention is present in every action, that every instance of attention is for the guidance of action, that attention is not a cause but an effect, and that there is no evidence for attention as necessary for conscious awareness.