Spring

Logic is, and always has been, a branch of philosophy. Why? What is logic? In this course we will explore the nature of logic, and how it relates to thought; to reasoning; to ordinary language; to mathematics; and to philosophy. We will read texts on the subject of logic by Aristotle, Kant, Hegel, Frege, Russell, Wittgenstein, Quine, Black, Prior, Gödel, Kripke, Dummett, Boolos, Putnam, Benacerraf, Harman, Williamson, Priest, and others. The course will be completely non-technical: we will be trying to make philosophical sense of logic. (B)

Preparing papers to submit to journals for review and revising papers in response to the feedback received from journal editors and referees is an essential part of professional academic life, and students applying for academic positions with no publications to their name are at a disadvantage in today’s highly competitive job market. The Department of Philosophy has therefore instituted the Paper Revision and Publication Workshop to provide our graduate students with support and assistance to prepare papers to submit for publication in academic philosophy journals. The workshop was designed with the following three aims in mind:

1. to provide students with a basic understanding of the various steps involved in publishing in academic journals and to create a forum in which students can solicit concrete advice from faculty members about the publishing process;

2. to direct and actively encourage students to submit at least one paper to a journal for review on a timeline that would allow accepted submissions to be listed as publications on a student’s CV by the time they go on the academic job market; and

3. to create and foster a departmental culture in which the continued revision of work with the ultimate aim of publication in academic journals is viewed as an essential aspect of the professional training of our graduate students and in which both faculty and students work together to establish more ambitious norms for publishing while in graduate school.

Course begins in late Spring quarter and continues in the Autumn quarter.

Advanced Study: Philosophy

An exploration of some of the central questions in metaethics, moral theory, and applied ethics. These questions include the following: are there objective moral truths, as there are (as it seems) objective scientific truths? If so, how can we come to know these truths? Should we make the world as good as we can, or are there moral constraints on what we can do that are not a function of the consequences of our actions? Is the best life a maximally moral life? What distribution of goods in a society satisfies the demands of justice? Can beliefs and desires be immoral, or only actions? What is “moral luck”? What is courage? (A)

Most of us seek to be reasonably good people leading what we take to be successful and satisfying lives. There is a mountain of evidence suggesting that most of us fail to live up to our own standards. Worse, we often fail to mark our own failures in ways that could help us improve ourselves. The context in which we try to live good lives is shaped by the vicissitudes of the global economy. The global economy is obviously of interest to those of us studying economics or planning on careers in business. Aspiring entrepreneurs or corporate leaders have clear stakes in understanding practical wisdom in the economic sphere. But anyone who relies upon her pay - or someone else's - to cover her living expenses has some interest in economic life.

In this course, we will bring work in neo-Aristotelian ethics and neo-classical economics into conversation with empirical work from behavioral economics and behavioral ethics, to read, write, talk, and think about cultivating wisdom in our economic dealings. While our focus will be on business, the kinds of problems we will consider, and the ways of addressing these, occur in ordinary life more generally - at home, in academic settings, and in our efforts to participate in the daily production and reproduction of sound modes of social interaction. (A)

Recent developments in artificial intelligence have brought about a radical reconceptualization of our idea of knowledge work. The model of the laboratory scientist, whose task is to conduct elaborate experiments that probe, in minute detail, the correctness of a theoretical hypothesis, is gradually giving way to that of the data scientist, whose concern is to wrangle massive datasets in an effort to extract from them reliable predictions with only a minimal theoretical guidance. In this course, we will explore some of the epistemological implications of this AI-driven shift in our conception of knowledge and the work that goes into acquiring it. Focusing on applications of artificial intelligence that utilize feed-forward deep neural networks for statistical inference, we will investigate what the shift to "big data" means for our philosophical theories of induction. Are the learning algorithms employed in the training of deep neural networks really "theory free"? If so, why should we trust that their predictions are reliable? How do neural networks purport to solve the curve-fitting problem and Goodman's new riddle of induction, without giving weight to theoretical virtues such as simplicity? Without a background of causal knowledge to structure their inferences, how do neural networks distinguish between causation and mere correlation, and if they cannot, why should we allow their predictions to serve as inputs to a theory of rational decision making? (B) (II)

Animals are in trouble all over the world.  Intelligent sentient beings suffer countless injustices at human hands: the cruelties of the factory farming industry, poaching and trophy hunting, assaults on the habitats of many creatures, and innumerable other instances of cruelty and neglect.  Human domination is everywhere: in the seas, where marine mammals die from ingesting plastic, from entanglement with fishing lines, and from lethal harpooning; in the skies, where migratory birds die in large numbers from air pollution and collisions with buildings; and, obviously, on the land, where the habitats of many large mammals have been destroyed almost beyond repair.  Addressing these large problems requires dedicated work and effort. But it also requires a good normative theory to direct our efforts. 

This class is theoretical and philosophical.  Because all good theorizing requires scientific knowledge, we will be reading a good deal of current science about animal abilities and animal lives.  But the focus will be on normative theory.  We will study four theories currently directing practical efforts in animal welfare: the anthropocentric theory of the Non-Human Rights Project; the Utilitarian theory of Jeremy Bentham, J. S. Mill, and Peter Singer; the Kantian theory of Christine Korsgaard; and an approach using the Capabilities Approach, recently developed by Martha Nussbaum.  We will then study legal implications and current legal problems, in both domestic and international law.