Courses

AD 32600 - Physical Computing

Introduction to electronics and computer vision for artists. Students learn to create expressive audiovisual systems that can respond to events in the physical world (movement, light/temperature change, sound, touch, etc.) through custom interfaces.

ANTH 30800 - Critical Data Studies

Critical Data Studies (CDS), is an interdisciplinary field that addresses the ethical, legal, socio-cultural, epistemological and political aspects of data science, big data and digital infrastructure. This course focuses on current topics in critical data studies scholarship. Particular emphasis will be given to democratic and participatory approaches to algorithm design and responsible data management, curation and dissemination. Students will develop tools and methods to help scholars think critically and identify issues of concern to Local Communities. This is a research and writing intensive course.

ANTH 52300 - GIS for Humanities and Social Science Research

This course will introduce you to the skills of spatial thinking, basic functions of Geographic Information Systems (GIS), and spatial research methods that are relevant to humanities, social science and related fields. The course will start with an introduction to basic GIS concepts and technology, then move onto GIS applications in the research process, including research design, data collection, management, visualization and basic spatial analysis techniques. Practical work will be completed using ArcGIS Pro software.

ENGL 32001 - Rhetoric, Artificial Intelligence, And Technology

This course examines the relationships between rhetoric and generative artificial intelligence (AI) using classical and contemporary rhetorical theory. While exploring how AI can support writing, students will gain insights into the challenges posed by AI, including issues of ethics, freedom, privacy and sustainability. Includes application of rhetorical principles to the design and critique of new technologies.

ENGL 33200 - Games And User Experience (UX)

This course connects gamers and their experiences with games by developing ways to harvest gaming experiences for the improvement of games. We aim to prepare you to better understand gaming experiences, use those understandings to improve games in development, and be able to think and write critically about those experiences.

HIST 28400 - The Computer Age From Babbage To The Blockchain

In this course we will explore the history of computing-from the pre-electronic days through the computer’s ascent in the twentieth century to the various electronic computing and communications technologies that surround us today. This course will investigate why there was a desire to create computing machines in the first place, the economic and political arrangements that brought computers into existence, the debates over what computers could (and should) be used for, the development of the IT profession and the gradual shift from computers being room-sized specialty machines to everyday objects that people carry around in their pockets.

HIST 30701 - History Of Artificial Intelligence: Minds And Machines

This course examines the long history of efforts in automating human cognition. Historically, the attempts to automate human cognitive functions - from the mere reckoning of numbers to complex decision-making have been entangled with heated debates about what counts as good, proper, and desirable thinking; whose thinking machines should emulate; and whether the thinking of some humans is inferior to that of machines. In this course, we will examine how the invention of calculating machines - analogue and then digital - has developed in tandem with philosophical and scientific theories of human thinking and intelligence. In their turn, the latter developed as a response to changing social, political and economic currents.

HIST 30705 - History Of Data: How Data Became Big

This course offers a long history of Big Data. The first module focuses on how states collected data from the 16th to 19th centuries. Here we will focus on mortality bills, census, statistics and accounting tables. In the second model, we will pay special attention to data collection and privacy in the 20th century. In the third module, students will explore how previous developments in data collection were applied to the new developments in analog and digital computing. The final weeks of the course will focus on present-day artificial intelligence, big data, their technical limitations and the ways they often amplify, exploit and contribute to a wide array of social problems.

LC 26300 - Introduction to Computational Linguistics

This course introduces computational linguistics, covering both theoretical and engineering topics. Students gain an understanding of the essential characteristics and differences between computational linguistics, natural language processing, machine learning and artificial intelligence. No previous programming background is required.

PHIL 25501 - Introduction To Cognitive Science: Minds, Brains, And Machines

This will provide an introduction to foundational topics in the philosophy of mind. We will consider the relationship between the mind and the body, and the mental to the physical more generally. We’ll ask, and look at some candidate answers to, questions like “What is a mind, and what are its component parts? How does a mind work? How are minds related to brains, and to the physical bodies that they seem to animate and control? How do minds represent the world around them? What is a self? What is the nature of consciousness and subjective experience? Could other animals, aliens, computers, robots or other types of entities have minds, or be conscious? How would we know? How can empirical efforts like the cognitive sciences help shed light on these questions? Could scientific theories of the mind supplant our intuitive conceptions of the mind? If so, what would be the implications?”

PHIL 25601 - Philosophy And Artificial Intelligence

Just what is it to be artificially intelligent and what will be AIs impact on our future? This course tackles these questions using an interdisciplinary and historically anchored approach beginning with the development of AI to arrive at a more holistic, socially- and ethically-ensconced account of what it means to be artificially intelligent. Will AI agents change the nature of work? Can they be used to regulate individuals and their opportunities through automated algorithms and sorting software? What are the human and environmental costs of a full-throated adoption of AI? This class will arm you with the philosophical and historical background to begin to devise and weigh the creative opportunities and challenges posed by this future. We’ll first consider traditional questions and issues in the philosophy of computation, epistemology, ethics and justice before turning to home onto a series of specific challenges that may include issues of AI in equity, AI and the law, AI and gender, AI and labor, AI and policy, the future of AI and whether we can even design ‘ethical’ AI.

PHIL 30000 - Philosophy Of AI: Foundations And Theoretical Issues

This class will examine some of the underlying philosophical questions and issues that arise when we think carefully about the nature of machines that are meant to model our own minds and replicate intelligence. Topics will include the nature of computation, intelligence, deep learning and mind design. While no technical background is assumed, some readings will include technical elements.

PHIL 31400 - Philosophy Of Artificial Intelligence: Ethical, Social, And Political Issues

This course introduces students to the fundamentals of ethical, social, and political analysis of AI. By developing critical thinking, argumentative and philosophical skills, students will engage with questions surrounding the development, risks, responsibilities of and surrounding AI. Students will learn the tools necessary to address these issues through reasoned argument and reflection.

POL 22800 - Data Science And Public Policy

This course is an introduction to the politics and policies of data science and “big data.” Students will gain an understanding of how public policy is made, including the role of data in policymaking; learn about whether and what policies govern the use of data in various applications (such as autonomous vehicles, ownership of health care data, etc.); and explore the ethical, legal and social implications of data science and big data.

POL 50601 - Data, Machine Learning, And Artificial Intelligence For The Public Sector

This course examines how machine learning algorithms and tools related to artificial intelligence can be used to advance our understanding in public sector domains. Students will develop a comprehensive understanding of how to apply AI and various machine learning algorithms, focusing on practical applications and hands-on experience. It provides an overview public sector data sources and addresses ethical and privacy issues associated with this type of data. 

POL 52601 - Technology, AI, and Ethics in Public Policy and Public Administration

This course examines the transformation of government operations through emerging technologies like artificial intelligence and automated decision systems. Students analyze governance strategies, policies and administrative procedures to promote responsible technology use in government. Through case studies and research projects, participants identify best practices for implementing and auditing AI systems in public sector contexts.

POL 52701 - Local to Global Governance of Data, AI, and Emerging Technology

This course introduces students to the institutions and governing systems at the subnational, national, supranational, and international levels that regulate emerging technology, AI and data. Focusing on laws, standards and best practices, students will examine comparative case studies of regulation of big tech in differing governing environments. Students will explore how social, economic and political factors shape differences in technology regulation across the globe.

POL 52801 - Organizational Governance Of Technology And AI

This course examines the impact of technology policy on organizations and their organizational governance strategies for AI and technology. It explores the incentives, strategies and activities of the private and non-profit sector in governing AI, as well as the relationship between the private, public and non-governmental sectors.

POL 55101 - Governance Auditing For AI - Sociotechnical Frameworks And Practices

Credit Hours: 3.00. Governance auditing of AI involves examining the sociotechnical systems that shape AI’s design, deployment and impact at the levels of individual AI systems, teams and broader organizations. This course equips students with the skills to better understand and evaluate AI systems, their organizational context and associated governance mechanisms through applying common industry and government frameworks. 

SOC 38100 - Data And Society

We are currently witnessing amazing technological innovations brought about by the production, accumulation and analysis of unimaginable amounts of data. These technologies are disrupting industries, creating new classes of wealthy and poor and providing novel opportunities for social control and resistance. This course will look at how the increasing centrality of data is changing our world. Among the questions we will answer: What’s so big about Big Data? How intelligent is artificial intelligence? Why does everyone want my data? Will there still be jobs when I graduate?