Inspiring, innovative, impactful: Creating a ‘uniquely Emory’ AI education

Sept. 22, 2024

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Ashlee Gardner

Fourth-year Emory student Sana Ansari has been exposed to artificial intelligence since childhood, having grown up in the Bay Area with parents working in Silicon Valley. While she’s always been conscious of the significance of AI and technology, she chose to major in public policy analysis.

Luckily, Ansari is at Emory University, where through the AI.Humanity initiative, students can blend their passions with the cutting-edge field of AI. She is now part of a growing cohort of students pursuing Emory’s new interdisciplinary AI minor.

“I know the AI minor will pair well with my BS degree and better equip me for the job market,” says Ansari. “As technology is progressing, so are debates on policies surrounding AI and its implementation within various fields. From privacy restrictions to its impact on journalism, AI is becoming more and more relevant in the policy realm, so I thought it would be beneficial for me to have the technical background that can further my knowledge of data science and policy.”

Since its inception in 2022, Emory’s AI.Humanity initiative has made substantial progress in advancing artificial intelligence for the benefit of humanity. Advised by the AI.Humanity Advisory Group, Emory has recruited leading AI faculty across seven schools to build on existing expertise and cultivate a robust and growing community of AI scholars. Another cornerstone of the initiative is the expansion of AI educational opportunities. In this, Emory sets itself apart with a distinct mix of expertise in humanities, law, business, health care and ethics.

A uniquely Emory portfolio of educational opportunities has been developed over the past two years aimed at fostering AI literacy across campus, providing students with essential skills needed to excel in a technology-driven world. Coupled with foundational knowledge is an emphasis on the ethical implications and societal impacts of AI and the flexibility to combine AI with other areas of study.

From classes to hands-on research, Emory offers a variety of curricular and cocurricular opportunities. New this fall, the Computer Science department will offer the option of adding a concentration in AI to the existing BS in Computer Science — joining an innovative AI minor program for all undergraduate students launched last year.

“I’m incredibly proud of the educational programs we have developed as part of AI.Humanity. We are providing students with the core skills they would get at a technical institution within the inquiry-driven, interdisciplinary context of a leading liberal arts and research university,” says Ravi V. Bellamkonda, provost and executive vice president for academic affairs. “We may have history majors using AI to analyze historical texts, medical students building AI applications to discover new biomarkers for drug development, or musicians generating a piano sonata with the help of AI tools. Our AI education is inspiring, impactful and uniquely Emory.”

A truly interdisciplinary AI minor

One of the first curricular components of the initiative was a new option for undergraduate study: the AI minor. Launched in spring 2023, the program is open to students in all disciplines who want to complement their major with a fundamental understanding of AI. The AI minor offers a holistic view of AI, from the technology that fuels it to its societal and ethical dimensions.

The program has attracted students eager to gain the core computer science competencies needed for a technical understanding of AI combined with electives from disciplines related to AI both directly and indirectly.

Some examples of available electives are:

Business: Applied Data Analytics with Coding, Data Visualization
Psychology: Neuropsychology and Cognition, Brain and Language
Quantitative Theory and Methods: Data Justice, Game Theory
Philosophy: Existence and Phenomenology, Business Ethics
English: Multimedia Journalism, Digital Rhetoric and Disinformation

Film and media major Sam Cooperman declared an AI minor because of his interest in technology. Before college, Cooperman spent his free time tinkering with coding, creating text-based games and building his own media server.

“Film and media have always been my true passion. A major part of working on a film production is problem solving and pushing the limits of available technology to create something original, unique and exciting,” says Cooperman. “AI is similar — your potential for utilizing AI is also defined by your ability to problem-solve and see old information in a new light. I would never want AI to do most of the work for me when it comes to filmmaking, but it is a valuable tool.”

New academic undergraduate and graduate credentials

Looking to the future, Emory is designing even more ways for students to deepen their understanding and experience of AI and its applications.

This includes the transcriptable concentration in AI that students can now earn as part of their bachelor’s degree in computer science. The BS in Computer Science, AI Concentration permits great flexibility for students and additional, much-desired credentialing without changing any of the requirements for the core curriculum.

The AI concentration, among the nation’s first, was driven by demand from students and employers.

“The AI concentration was developed to provide in-depth and focused AI education to undergraduates. Through a program of study that selects AI and AI-related upper-class courses (including newly developed classes), computer science majors can specialize in AI, while building on the core curriculum. The AI concentration, among the nation’s first, was driven by demand from students and employers,” says Vaidy Sunderam, Samuel Candler Dobbs Professor and chair in the Department of Computer Science.

Innovative interdisciplinary master’s programs are also on the horizon. These “AI + X” programs will combine foundational coursework in computer science and AI concepts with specialized fields like business, public health and economics.

“The Emory Computer Science Department offers a unique set of educational opportunities that connect to the liberal arts curriculum, economics, business and health care disciplines, complementing core programs in technical computer science. This spectrum of educational programs comprises a prominent technology presence at Emory, while preparing students for computer science and AI-centric advances in various other disciplines,” says Sunderam.

Experiential AI learning opportunities

In fall 2023, Emory’s Center for AI Learning opened its doors and welcomed students, faculty and staff intent on learning about AI and applying it to their research, work and personal lives. Among its other functions, the center serves as a hub that coordinates both curricular and cocurricular experiential learning projects for students. These experiences give students the opportunity to apply AI concepts from class while developing project management, teambuilding and client service skills. In its first year, the center matched 179 students with experiential learning projects and plans to increase that number next year.

Applied math and statistics major Tom Suo wishes to pursue a career related to AI, possibly as a machine learning engineer. He encourages students interested in AI to take full advantage of the opportunities provided by the center, especially the chance to work with faculty on groundbreaking research.

“This summer I participated in the AI.Xperience summer program that was offered by the center. We got to work with professors conducting research on cutting-edge AI technology and presented our research at a showcase event,” says Suo. “The experience gave me a more realistic understanding of how AI functions and shed some light on the ‘black box’ of AI models. I encourage students interested in AI to take full advantage of the center’s programs.”

Collaborative and personalized AI education

For students looking to study AI in the context of other disciplines, Emory provides the ideal environment — a top tier university with highly ranking schools specializing in liberal arts, law, medicine and business.

“Emory is known for its liberal arts,” says Suo, who began his undergraduate program at Oxford College. “I believe this educational philosophy lives on in the many academic pursuits that are available at Emory.”

Beyond the flexibility to study both film and AI, Cooperman values the close-knit and personal approach to AI education at Emory.

“Emory enables you to have a much closer connection to both your fellow students and professors. AI can be a very competitive field, but it is at its best when it is collaborative, and Emory’s smaller size makes it an incredibly collaborative environment. In my experience, professors are easy to reach out of class, are passionate about what they do and the classes are full of students looking to work together to solve important problems,” says Cooperman.

A suite of new AI courses

A growing number of AI faculty and academic programs has resulted in a more robust course catalog for students interested in AI. In the past two years, 13 undergraduate and graduate AI-focused computer science courses have been unveiled. These new courses in the Department of Computer Science join more than 30 interdisciplinary courses related to AI and machine learning.

Fundamentals, modern concepts, and practices in artificial intelligence including computational decision making, knowledge-based agents, propositional logic, search, heuristics and machine learning.

Understanding ethical and societal concerns introduced by computing and AI into human life, including privacy, online influence and disinformation, information ownership and responsibility and fairness and bias in computer and AI technologies such as facial recognition and robotic systems.

Machine learning techniques and their use in solving problems from multiple real-world domains. Topics covered include data analytics, regression, classification, clustering, decision trees and neural networks using Python libraries. Focuses on applications and use rather than algorithms or theory.

This course guides students in developing the ability to conduct high-quality research in artificial intelligence. Throughout the course, students will work on team projects, write research papers (both individually and in groups), peer-review papers from others and give public presentations.

In this course, students 1) will become acquainted with fundamental theories in perceptual psychology that drive visualization design, 2) will be introduced to basic principles of human-computer interaction which inform evaluation of interactive visualizations and 3) will use D3 to develop interactive visualizations.

Computer vision concerns computing scene properties from digital images. Rendering, feature detection, image formation, motion estimation, mosaics, 3D shape reconstruction, face recognition and related topics are covered.

Exploration into the fundamentals of text processing techniques and their integration with modern neural network architectures. Emphasis is placed on a range of neural networks from multilayer perceptrons to attention mechanisms and transformers. Topics include text classification, neural networks and transformer for text processing.

Core concepts of deep neural networks, including the backpropagation algorithm for training neural networks, as well as specific operations such as convolution, word embeddings and recurrent neural networks using textbook examples in image and text analysis. The Tensorflow deep learning framework will be used as the basis for implementation.

This course includes theories of visualization, basic principles of human-computer interaction to inform design and evaluation of visualizations and skills for interactive visualizations with D3 and Tableau.

Advanced topics in computer vision including geometry of image formation, radiometry, light fields, color, linear filters, sampling and multiscale image representations, neural architectures for vision, probabilistic models of images and generative image models.

Focuses on the computational, algorithmic and modeling challenges of large graphs. Topics include representation learning and GNNs algorithms for the web, reasoning over knowledge graphs, influence maximization, disease outbreak detection and social network analysis.

Advanced topics in deep learning, including convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization and case studies in several domains. Students work on case studies from health care, autonomous driving, sign language reading, music generation and natural language processing.

Discussion topics include but are not limited to different design frameworks, tools and methods, studies of science & technology (STS), socio-technical systems, AI+HCI, physical/tangible computing, ubiquitous computing, social computing, augmented and virtual reality, technology and well-being, intersectional computing and accessibility. Over the semester, students will develop an in-depth understanding of the social implications of technology on humanity and the world around us.

Emory's focus on innovative, interdisciplinary AI education is fostering a new generation of leaders with a comprehensive understanding of AI, from its technical foundations to its ethical and societal implications. As the AI.Humanity initiave expands its mission to improve human health, generate economic value and advance social justice, more academic opportunities are being developed.

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