Courses

This seminar will survey historical and modern developments in machine intelligence from fields
such as psychology, neuroscience, and computer science, and from approaches such as
cybernetics, artificial intelligence, machine learning, robotics, connectionism, neural networks,
and deep learning. The emphasis is on the conceptual understanding of topics. The course does
not include, nor require a background in, computer programming and statistics. The overall goal
is for students to become informed consumers of applications of artificial intelligence.

Why do we feel the way we do, how do we understand ourselves and others, and how does this relate to our social relationships?  Why does all of this sometimes leave us feeling anxious, depressed, lonely and isolated?  And when that happens, what we can do about it?  In this seminar, we will tackle these questions using an integrative approach that blends social psychology, clinical psychology and neuroscience to uncover how our emotions and social interactions sometimes work well and sometimes falter.  To do this, we will examine human behavior at multiple levels, connecting our social and emotional lives (what we experience and how we act) to cognitive processes (how our minds process information) and underlying neural mechanisms (what's happening in the brain).  As the semester unfolds, we start by building an understanding of where our emotions come from, how we can manage them, how we make sense of other people and how we can form positive connections with them.  This knowledge provides a foundation for taking the next step - understanding what happens when things go awry and we end up with momentary - or long-lasting - bouts of anxiety, depression, loneliness and other clinical conditions.  We end by considering what may be everyone’s life goal - the pursuit of happiness - and how everything we have learned can foster that pursuit through personal actions, social connections and psychotherapeutic support.  The overarching goal is to build a nuanced understanding of how and why we think and feel the way we do – about ourselves and others – that can inform both scientific and personal explorations of what “wellbeing” and “mental health” means.

Prerequisites

Equivalents of an introductory Psychology course and one more advanced lecture, lab or seminar course in Psychology or a related discipline (and/or the instructor's permission).


This course is meant to provide an introduction to regression and applied statistics for the social sciences, with a strong emphasis on utilizing the Python software language to perform the key tasks in the data analysis workflow. Topics to be covered include various data structures, basic descriptive statistics, regression models, multiple regression analysis, interactions, polynomials, Gauss-Markov assumptions and asymptotics, heteroskedasticity and diagnostics, data visualization, models for binary outcomes, models for ordered data, first difference analysis, factor analysis, and cluster analysis. Through a variety of lab assignments, students will be able to generate and interpret quantitative data in helpful and provocative ways. Only relatively basic mathematics skills are assumed, but some more advanced math will be introduced as needed. A previous introductory statistics course that includes linear regression is helpful, but not required.

Social scientists need to engage with natural language processing (NLP) approaches that are found in computer science, engineering, AI, tech and in industry. This course will provide an overview of natural language processing as it is applied in a number of domains. The goal is to gain familiarity with a number of critical topics and techniques that use text as data, and then to see how those NLP techniques can be used to produce social science research and insights. This course will be hands-on, with several large-scale exercises. The course will start with an introduction to Python and associated key NLP packages and github. The course will then cover topics like language modeling; part of speech tagging; parsing; information extraction; tokenizing; topic modeling; machine translation; sentiment analysis; summarization; supervised machine learning; and hidden Markov models. Prerequisites are basic probability and statistics, basic linear algebra and calculus. The course will use Python, and so if students have programmed in at least one software language, that will make it easier to keep up with the course.

Artificial intelligence (AI) and generative AI – like ChatGPT, MidJourney, and Gemini – are poised to change the world for everyone. It is critical that students understand (and utilize) this new technology at several levels. In this class – through readings and a dozen hands-on activities – students will come to deeply understand AI. Specifically, students will construct (using Python) some of the basic building-blocks of AI, like machine learning (like recommendation systems), natural language processing (like word embeddings) and chatbots. They will test out AI’s capabilities and refine prompts in real-world settings, whether in art, video, writing or Internet-of-Things. They will learn about how generative AI fits into the history of technology adoption and the diffusion of innovation, answering questions like: Will AI be able to replace whole jobs? And if so, when? They will use the lenses of psychology and economics to explore the impact of AI in people’s lives, including in the context of algorithmic fairness, regulation and intellectual property. They will be pushed to take human creativity in new directions, augmented by AI’s “weirdness.” Lastly, students will be pushed to further develop their own uniquely-human skills – like in critical thinking and empathy – in response to the power of generative AI to mimic humans. As best-selling author Seth Stephen-Davidowitz has recently (Dec. 2023) written, “So far, [my newest book] has higher ratings than either of my previous two books -- even though it was written in 1/36th of the time, thanks to AI. AI is wild!" By the end of this class, students will feel empowered technically and philosophically to handle all new generative AI developments. There are no specific prerequisites for this class.

This course offers students an opportunity to expand their curriculum beyond the established course offerings. Interested parties must consult with the QMSS Program Director before adding the class. This course may be taken for 2-4 points.

This course is designed as an introduction to the Islamic religion, both in its pre-modern and modern manifestations. The semester begins with a survey of the central elements that unite a diverse community of Muslim peoples from a variety of geographical and cultural backgrounds. This includes a look at the Prophet and the Qur'an and the ways in which both were actualized in the development of ritual, jurisprudence, theology, and sufism/mysticism. The course then shifts to the modern period, examining the impact of colonization and the rise of liberal secularism on the Muslim world. The tension between traditional Sunni and Shi'i systems of authority and movements for 'modernization' and/or 'reform' feature prominently in these readings. Topics range from intellectual attempts at societal/religious reform (e.g. Islamic Revivalism, Modernism, Progressivism) and political re-interpretations of traditional Islamic motifs (e.g. Third-Worldism and Jihadist discourse) to efforts at accommodating scientific and technological innovations (e.g. evolution, bioethics ). The class ends by examining the efforts of American and European Muslim communities to carve out distinct spheres of identity in the larger global Muslim community ( umma) through expressions of popular culture (e.g. Hip-Hop).

This course is designed as an introduction to the Islamic religion, both in its pre-modern and modern manifestations. The semester begins with a survey of the central elements that unite a diverse community of Muslim peoples from a variety of geographical and cultural backgrounds. This includes a look at the Prophet and the Qur'an and the ways in which both were actualized in the development of ritual, jurisprudence, theology, and sufism/mysticism. The course then shifts to the modern period, examining the impact of colonization and the rise of liberal secularism on the Muslim world. The tension between traditional Sunni and Shi'i systems of authority and movements for 'modernization' and/or 'reform' feature prominently in these readings. Topics range from intellectual attempts at societal/religious reform (e.g. Islamic Revivalism, Modernism, Progressivism) and political re-interpretations of traditional Islamic motifs (e.g. Third-Worldism and Jihadist discourse) to efforts at accommodating scientific and technological innovations (e.g. evolution, bioethics ). The class ends by examining the efforts of American and European Muslim communities to carve out distinct spheres of identity in the larger global Muslim community ( umma) through expressions of popular culture (e.g. Hip-Hop).

What is the source of truth and authority? What is the origin of the world and how does that determine the social order? Who ought to rule, why, and how? What are the standards for measuring justice and injustice? What is our relationship to the environment around us and how should its resources be distributed among people? How do we relate to those who are different from us, and what does it mean to be a community in the first place? Historically, the answers to these questions that have been described as “religious” and “political” have been the restricted to a specific tradition of Western European Christianity and its secular afterlives. However, these are questions that every society asks, in order to be a society in the first place. This course analyzes how indigenous peoples in the Americas asked and answered these questions through the first three centuries of Western European imperial rule. At the same time, this course pushes students to question what gets categorized as uniquely “indigenous” thought, how, and why.

How did European-Christians justify the colonization of the Americas? Did these justifications vary between different European empires, and between the Protestant and Catholic faiths, and if so, how? Do these justifications remain in effect in modern jurisprudence and ministries? This class explores these questions by introducing students to the Doctrine of Discovery. The Doctrine of Discovery is the defining legal rationale for European Colonization in the Western Hemisphere. The Doctrine has its origins in a body of ecclesiastic, legal, and philosophical texts dating to the late-fifteenth century, and was summarized by Chief Justice John Marshall of the United States Supreme Court, in the final, unanimous decision the judiciary issued on the 1823 case Johnson v. M’Intosh. Students will be introduced to the major, primary texts that make up the Doctrine, as well as contemporary critical studies of these texts and the Doctrine in general.