AI Courses Offered

AI Courses

Departments across the University offer many related courses. Here are some examples:

Commonly Taught Course Descriptions

CDT 30750 Generative AI in the Wild

Taught by Ranjodh Singh Dhaliwal and John Behrens

Generative AI is a form of computing in which computer systems generate media such as text, images, sound, video, or combinations based on prompts or other information provided to the computer. These systems, including, but are not limited to, ChatGPT, Midjourney & DALLE, have been evolving rapidly and have led to extreme excitement, confusion, and fear. This course provides a survey of how to understand and use a number of these tools including explorations in prompt engineering as well as addressing issues from across the liberal arts including artistic, economic, social/psychological, educational and legal concerns and opportunities.

CDT 40711 The Future of Labor

Taught by Yong Lee

The new wave of technologies, e.g., robotics and AI will have long-lasting impacts on the labor market. Jobs will be displaced, new tasks will be created, different skills will be demanded, and new management practices will emerge. These new technologies may benefit workers unevenly, potentially increasing inequality. At the same time, new demographic challenges driven by aging will have large impacts on labor. How will these forces affect the future of labor and how should we prepare for changes in the labor market? The goal of this course is to provide students with a framework for analyzing how new technologies like robotics and AI will affect the labor market drawing largely from the economics literature. Students will analyze and describe the literature on these topics and understand the different methodologies used in the literature. Ultimately, students will build perspectives on how AI and robotics could affect jobs, occupations, the future of work, income distribution and social institutions. Students will also build perspectives on education, training, and redistribution policies that can help mitigate the labor market disruptions created by technological change. Students will collect and analyze data that can provide insights on the future of labor.

CDT 33698 AI for Good

Taught by Georgina Curto Rex

Traditional strategies to fight against poverty, inequality and climate change have proved ineffective in the last decades. New and creative solutions are required where cutting-edge technological innovation and multidisciplinary work serve the common good. In this course, you will explore the state of the art in AI business development and its ethical implications in relation to current global societal and environmental challenges. You will reflect on your individual role in society and develop critical thinking about the current socio-technical value system. Our readings will include original works of philosophers, economists and computer scientists as well as examples of state-of-the-art AI supported business and institutional projects. As a result of the readings and class discussions, you will acquire well-informed understanding about the implications of the AI Trustworthy principle of justice and fairness, including non-discrimination and avoidance of unfair bias. You will become aware of the potential for AI to contribute, if well managed, towards fairer and more sustainable societies as well as the dangers it entails to widen inequalities and aggravate the discrimination suffered by vulnerable communities. This is a hands-on course where you will be ideating and planning projects for the social good. I will accompany you in the development of business plans where ethics is the driver and AI is the key instrument. I will help you define your project idea in line with the United Nations Sustainable Development Goals (UN SDGs). Therefore, your projects will be designed to work towards mitigating poverty, reducing gender and race inequality, combating climate change, improving the sustainability of cities and communities, ensuring affordable and clean energy, achieving responsible consumption and production, improving the quality of education, providing better health and well-being services, ensuring decent work and economic growth or promoting peaceful and inclusive societies. The goal of the course is to encourage and support you, as new entrepreneurs and future leaders, to work in multidisciplinary teams and develop interdisciplinary skills, being able to take advantage of new technology to create and manage projects for ethics in action.

CDT 30560 AI in the 21st Century

Taught by Kate Marshall

According to several popular narratives, Artificial Intelligence is either about to be the most transformational influence on human culture since the Industrial Revolution, or an over-hyped set of diffuse technologies and systems with only superficial relation to each other. In this course, students will consider AI from several different disciplinary perspectives in order to make sense of both the narratives and the science surrounding it. These perspectives include computer science, the history of technology, philosophy, AI ethics, and science fiction. By taking up these different perspectives, students will develop vocabularies for talking about AI and, importantly, for thinking about its future.

CDT 30614 AI Auditing: An Introduction

Taught by Cam Kormylo and Ju Yeon Jung

As artificial intelligence (AI) grows increasingly pervasive in society, it is essential that we develop an understanding of how AI systems work. A vital part of this understanding is a careful consideration of various risks (e.g., the presence of bias, a lack of transparency, regulatory compliance) when AI systems are designed and deployed in real-world settings. To understand and address these concerns, this course introduces students to the fundamentals of AI auditing — the practice of evaluating and improving the ethics of AI systems. Through a combination of interactive discussions and semi-technical lab sessions, students will develop an auditing “toolkit”. This toolkit includes both theoretical and technical concepts, especially relevant for the increasingly interdisciplinary teams of the modern workforce. Students will work on group case assignments as “audit committees” that reflect the needs of a variety of stakeholders (e.g., developers, managers, investors, users). Groups will identify and discuss potential concerns or risks associated with AI systems as well as develop recommendations to address them. Overall, the course aims to provide an interdisciplinary and hands-on introduction to AI auditing, allowing students to gain insights into the opportunities and challenges associated with the design and deployment of AI systems that minimize societal risk and increase their effectiveness.


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