Interdepartmental Electives

Last offered Spring 2023

The philosophy of mind has been one of the most active areas of philosophical inquiry over the last century. Whether the mind can be fully understood within a scientific framework has taken on an exciting urgency. In this course we will investigate the the broad topics of consciousness and thought by surveying the many approaches to mind that yield the contemporary debates. [ more ]

PHIL 216 / ENVI 216 SEM Philosophy of Animals

Last offered Spring 2021

Animals are and always have been part of human life. To name just a few ways: We treat animals as companions, as food, as objects of wonder in the wild, as resources to be harvested, as testing grounds for science, and as religious sacrifice. The abstract philosophical question before us is, what are animals such that they can be all these things? In this course we aim to engage that abstract question through two more focused projects. Firstly, we will try to understand the mental lives of non-human animals. Secondly, we will try to make sense of the moral dimensions of our relationship to animals. Throughout we will aim to fuse a rigorous scientific perspective with more humanistic themes and philosophical inquiry. Topics include sentience, animal cognition, language in non-human animals, empathy and evolution, the history of domestication, animal rights, cross-cultural views on animals, arguments against and for vegetarianism and veganism, the morality of zoos, hunting and fishing, and pets and happiness. [ more ]

Last offered Fall 2023

The sentence "Every cookie is chocolate chip and three of them are oatmeal raisin" is a perfectly grammatical sentence of English, but it's self-contradictory. What does it take to realize this fact? One must grasp the meanings of the various parts of the sentence. In particular, one must grasp that "three of them" picks out a subset of the group picked out by "every cookie", and that there's no such thing as a cookie that is both chocolate chip and oatmeal raisin. There two ways to understand "Many students took every class". According to one, there is a single group of students that had their hands extremely full this semester. According to the other, every class was well-populated, potentially by different groups. The reason for this is that there are two underlying structures that the original sentence can realize. This course serves as an introduction to formal methods in the scientific study of language. Our goal will be to characterize phenomena like those above with logical and mathematical precision. The focus will be on model-theoretic semantics, the sub-field of linguistics that studies meanings. Along the way we will discuss principles of syntax, the sub-field that studies sentence structures, and pragmatics, the sub-field that studies inferences of non-literal content. This is a formal course, but no prior logical or mathematical background will be expected. Starting from scratch, students will learn the building blocks of current-day linguistic research. This introduction will be of use to students interested in language from a variety of perspectives, including philosophy, cognitive science, and computer science. [ more ]

Last offered Fall 2022

This course examines some of the central questions raised by the study of the consciousness: the place of intentionality, the role of emotions, the relation with the body, the nature of subjectivity, the scope of reflexivity, the nature of perceptual presence, etc. In confronting these difficult questions, we do not proceed purely theoretically but consider the contributions of various observation-based traditions, from Buddhist psychology and meditative practices to phenomenology to neurosciences. We begin by examining some of the central concepts of Buddhist psychology, its treatment of the mind as a selfless stream of consciousness, its examination of the variety of mental factors and its accounts of the relation between cognition and affects. We also introduce the practice of meditation as a way to observe the mind and raise questions concerning the place of its study in the mind-sciences. We pursue this reflection by examining the views of James, Husserl, Sartre and Merleau-Ponty, particularly as they concern the methods for the study of the mind and the relation between consciousness, reflexivity and the body. In this way, we develop a rich array of analytical tools and observational practices to further our understanding of the mind. But we also question the value of these tools based on first person approaches by relating them to the third person studies of the mind. In this way, we come to appreciate the importance of considering the biology on which mental processes are based and the light that this approach throws on the nature of consciousness. We conclude by considering the relation between first and third person studies of the mind, focusing on the concept of the embodied mind as a fruitful bridge between these different traditions. [ more ]

Last offered Spring 2024

Humans are constantly making decisions: big and small, conscious and unconscious. This seminar will explore different aspects of the decision-making process, including (1) the algorithms for decision-making, (2) the neurological basis of decision-making and (3) the psychological, social, and physiological factors that influence our decision-making. We will examine how scientific approaches can help us understand complex social issues related to decision making. For example: how can stereotypes be understood as a failure in belief updating; how does confirmation bias lead to partisanship; and how to think of xenophobia from the "explore-exploit trade-off" perspective? In this course, we will explore how the brain and its neural networks contribute to these phenomena. The laboratory component of the course will introduce the research tools for studying different aspects of decision-making, including experimental paradigms, computational models and methods of analysis. Students will apply these tools to collaboratively design and conduct behavioral experiments and will analyze neural recording data to understand the relationship between neural activity and decision-making behaviors. Over the course of the semester, students will have the opportunity to develop skills in computer programming to better understand computational models and data analysis. [ more ]

PSYC 322 SEM Concepts: Mind, Brain, and Culture

Last offered Spring 2020

Every time we see something as a kind of thing, every time that we decide that an object is a cup rather than a glass, when we recognize a picture of a familiar face as a picture of ourselves, or even when we understand speech, we are employing categories. Most categorization decisions are automatic and unconscious, and therefore have the illusion of simplicity. The complexity of these decisions, however, becomes apparent when we attempt to build machines to do what humans perform so effortlessly. What are the systems in place that allow us this extraordinary ability to segment the world? Are they universal? How does conceptual knowledge differ across cultural groups? How do concepts affect our perception? How do the categories of experts differ from the categories of novices? Do children have the same kind of conceptual knowledge as adults? How are categories represented in the brain? In this course, we explore various empirical findings from cognitive psychology, cognitive neuroscience, and anthropology that address these questions. [ more ]

PSYC 324 TUT Great Debates in Cognition

Last offered Spring 2018

The field of cognition is filled with controversies about how the mind really works. For example, is there sufficient evidence for a system in vision that can become aware of things without actually "seeing" them? Is it necessary to assume that babies come into the world armed with innate linguistic knowledge? Are humans inherently rational? Can we make inference about the mind using neuroimaging? These debates, and others that we will consider, help fuel scientific discovery in cognition in interesting ways. In this class, we will consider some of these contemporary debates, weigh evidence on both sides, and discuss the implications for what we know about the mind. [ more ]

PHIL 331 TUT Contemporary Epistemology

Last offered Fall 2012

Epistemology is one of the core areas of philosophical reflection. In this course, we will study the literature in contemporary philosophy on the nature of knowledge and rational belief. Epistemologists seek answers to the following kinds of questions: When is it rational to have a particular belief? What is knowledge (as opposed to mere opinion)? In order to be justified in holding a belief, must someone know (or believe) that she is justified in holding that belief? What, if anything, justifies our scientific knowledge? These questions are typically asked within a framework where the overarching goal is attaining truth and avoiding falsity. Beyond this common ground, however, epistemologists are much divided. Some maintain that these issues are solely the provinces of philosophy, using traditional a priori methods. Others maintain that these questions will only yield to methods that incorporate our broader insight into the nature of the world including, perhaps, feminist thought or science. Both stances face severe difficulties. Further, even where there is agreement as to the proper way of answering epistemological questions, there is a stunning variety of possible answers to each question. [ more ]

Last offered Spring 2023

Artificial Intelligence (AI) has become part of everyday life, but what is it, and how does it work? This course introduces theories and computational techniques that serve as a foundation for the study of artificial intelligence. Potential topics include the following: Problem solving by search, Logic, Planning, Constraint satisfaction problems, Reasoning under uncertainty, Probabilistic graphical models, and Automated Learning. [ more ]

Last offered Fall 2023

Machine learning is a field that derives from artificial intelligence and statistics, and is concerned with the design and analysis of computer algorithms that "learn" automatically through the use of data. Computer algorithms are capable of discerning subtle patterns and structure in the data that would be practically impossible for a human to find. As a result, real-world decisions, such as treatment options and loan approvals, are being increasingly automated based on predictions or factual knowledge derived from such algorithms. This course explores topics in supervised learning (e.g., random forests and neural networks), unsupervised learning (e.g., k-means clustering and expectation maximization), and possibly reinforcement learning (e.g., Q-learning and temporal difference learning.) It will also introduce methods for the evaluation of learning algorithms (with an emphasis on analysis of generalizability and robustness of the algorithms to distribution/environmental shift), as well as topics in computational learning theory and ethics. [ more ]

Last offered Spring 2024

Artificial intelligence (AI) is already transforming society and every industry today. In order to ensure that AI serves the collective needs of humanity, we as computer scientists must guide AI so that it has a positive impact on the human experience. This course is an introduction to harnessing the power of AI so that it benefits people and communities. We will cover a number of general topics such as: agency and initiative, AI and ethics, bias and transparency, confidence and errors, human augmentation and amplification, trust and explainability, and mixed-initiative systems. We explore these topics via readings and projects across the AI spectrum, including: dialog and speech-controlled systems, computer vision, data science, recommender systems, text summarization, and UI personalization, among others. [ more ]

Last offered Spring 2024

Does X cause Y? If so, how? And what is the strength of this causal relation? Seeking answers to such causal (as opposed to associational) questions is a fundamental human endeavor; the answers we find can be used to support decision-making in various settings such as healthcare and public policy. But how does one tease apart causation from association--early in our statistical education we are taught that "correlation does not imply causation." In this course, we will re-examine this phrase and learn how to reason with confidence about the validity of causal conclusions drawn from messy real-world data. We will cover core topics in causal inference including causal graphical models, unsupervised learning of the structure of these models, expression of causal quantities as functions of observed data, and robust/efficient estimation of these quantities using statistical and machine learning methods. Concepts in the course will be contextualized via regular case studies. [ more ]

PHIL 388 TUT Consciousness

Last offered Spring 2019

The nature of consciousness remains a fundamental mystery of the universe. Our internal, felt experience--what chocolate tastes like to oneself, what it is like to see the color red, or, more broadly, what it is like to have a first person, waking perspective at all--resists explanation in any terms other than the conscious experience itself in spite of centuries of intense effort by philosophers and, more recently, by scientists. As a result, some prominent researchers propose that the existence of consciousness requires a revision of basic physics, while others (seemingly desperately) deny that consciousness exists at all. Those positions remain extreme, but the challenge that consciousness poses is dramatic. It is at the same time the most intimately known fact of our humanity and science's most elusive puzzle. In this tutorial we will read the contemporary literature on consciousness. We will concentrate both on making precise the philosophical problem of consciousness and on understanding the role of the relevant neuroscientific and cognitive research. Tutorial partners will have an opportunity to spend the end of the semester working on a special topic of their choosing including, for instance, consciousness and free will, pain and anesthesia, consciousness and artificial intelligence, or disorders of consciousness. [ more ]

Last offered Spring 2023

It'd be perfectly natural to say "I might've left the stove on", then check the stove, then say "I didn't leave the stove on". But perform those exact same steps in a different order--check the stove, say "I didn't leave the stove on", then say "I might've left the stove on"--and something's gone quite wrong. Conversation is dynamic--the back and forth exchange of information is a process that grows and adapts to the surrounding context. The order in which you say things matters, and it matters for what you communicate what actions you take and what events happen around you. In this course, we will investigate dynamic communicative phenomena and discuss competing theoretical explanations about how they're interpreted. Of particular interest will be the extent to which discourse dynamics are built into the meanings of linguistic expressions vs. the extent to which they're consequences of our rational cognition. Is a sentence's relation to previously uttered sentences similar to its relation to extra-linguistic events? How much inference goes into interpreting what's said? In pursuing the answers to these questions, we will discuss both classic and contemporary theories from philosophy and linguistics. [ more ]