Matthew Groh
Assistant Professor of Management and Organizations
Assistant Professor in the Department of Computer Science (CS), McCormick School of Engineering (Courtesy)
Matt Groh is an Assistant Professor of Management and Organizations. His research examines the dynamics of human-AI collaboration in deepfake detection, medical diagnosis, and empathic communication.
Professor Groh's research has been published in Science, Proceedings on National Academy of Science (PNAS), Nature Medicine, Nature Communications, NeurIPS, Computer Supported Collaborative Work (CSCW), Affective Computing and Intelligence Interactions (ACII), and Communications of the ACM among other journals and conferences. His work has been featured in the popular press including The New York Times, Wall Street Journal, Science, Scientific American, NPR, Le Monde, Aeon, and Fast Company.
Professor Groh received his BA from Middlebury College with a major in economics and minors in mathematics and Arabic and received his MA and PhD in Media Arts and Sciences from MIT.
- Human-AI Collaboration
- Computational Social Science
- Applied Machine Learning
- Affective Computing
- Generative AI
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BA, 2010, Economics with minors in Mathematic and Arabic, Middlebury College
MA, 2019, Media Arts and Science, MIT
PhD, 2023, Media Arts and Science, MIT -
Assistant Professor, Management & Organizations, Kellogg School of Management, Northwestern University, 2023-present
Assistant Professor, Computer Science (by courtesy), McCormick School of Engineering, Northwestern University, 2024-present -
Sidney J. Levy Teaching Award
Human & Machine Intelligence (MORSX-950-0)
This course focuses on the fundamentals of what artificial intelligence is, how it is applied in business, and why it is heralded as the next industrial revolution. This course requires no prior technical knowledge, starting with an examination of what machine learning and artificial intelligence is, how it functions, and where it excels. We progress to building AI models, exploring potential benefits and pitfalls of AI in comparison to traditional decision-making and how the two are complementary, and discussing best-practices on implementation at organizations. We cover both the historical origins of AI---including how IBM's Deep Blue and Google's AlphaGo beat Chess and Go Grandmasters--as well as modern applications across a broad range of business sectors and applications. This course is a lecture-based course with case-based discussions, group activities and projects, and a final individual assignment. The overarching goal for the course is to enable you to confidently lead data science and design teams, know the expansiveness and limits of AI, and be capable of applying human and machine thought partnerships to grow businesses or disrupt Grand Masters in any field.
Human and Machine Intelligence (MORS-950-0)
Artificial intelligence (AI) is a transformative technology and a modern day equivalent to fire in the early stages of human civilization. It is a tool that can be used to solve complex problems, make predictions, automate tasks, and enhance productivity. But like fire, it has a dual nature and has potential for both good and bad outcomes. This course requires no prior technical knowledge and is designed for people who want to lead and manage the deployment of AI systems in the real-world whether at a startup or a large organization. The goal of the course is to build intuition and understanding of what AI is, how machine learning works, where these tools tend to succeed and fail, and how to navigate the ethical implications of these tools. We will explore a wide range of business applications, examine tools ranging from ChatGPT and Midjourney to DeepBlue and AlphaGo to the Twitter and TikTok recommendation systems to many more, and discuss best practices for managing teams of humans assisted by these tools. This course is a lecture-based course with case-based discussions, individual assignments, a midterm, and a final group project. By the end, you should be an expert at identifying promising use-cases, understanding current limitations, and recognizing potential pitfalls of AI such that you are capable of applying human and machine thought partnerships to grow new businesses and disrupt Grand Masters in any field.
Human and Machine Intelligence (AIML-950-5)
Building upon the foundational knowledge and insights in AIML901-MORS, this course examines opportunities in business where AI intersects with organizational behavior, leadership, and business strategy. The goal of the course is to equip future leaders with the frameworks to identify and evaluate AI opportunities, manage AI-driven products, navigate ethical dilemmas, and lead teams of both human and machine intelligence. We will explore a wide range of business applications emerging from the capabilities and limitations of AI systems including ChatGPT, Gemini, Claude, IBM Watson, Netflix and Tiktok’s recommender systems, and AI systems for recognizing and responding to emotion. This course is an interactive lecture and case-based course with one individual assignment, one quiz, and a final group project that have both individual and group elements. This course is based on the second five weeks of Professor Groh’s 2024 and 2025 Human and Machine Intelligence MORS950 course, and it’s continually updated with the latest science and industry insights. Past guest speakers include product managers at OpenAI, Deepmind, Anthropic, Mindtrip, Paypal, and Spotify. By the end, you should be an expert at identifying promising business use-cases of frontier AI technologies and evaluating AI’s current limitations such that you can apply human and machine thought partnerships to grow new businesses and disrupt Grand Masters in any field.
AI Foundations for Managers (AIML-901MO-5)
Artificial intelligence (AI) is a transformative technology and a modern day equivalent to fire in the early stages of human civilization. Organizations can use AI to solve complex problems, automate tasks, make predictions, and even boost human creativity. However, like fire, AI also carries significant risks when misused. This course requires no prior technical knowledge and is designed for students who want to lead and consult on the deployment of AI systems in organizations, manage data science and design teams, or build and invest in AI companies. The goal of the course is to build intuition for what AI can do, how machine learning works, where these tools tend to succeed and fail, and how to navigate their ethical implications. We will explore a wide range of business applications emerging from the capabilities and limitations of AI systems including ChatGPT, Gemini, Claude, Midjourney, Alphazero, and more. This course is an interactive lecture-based course with two individual assignments, two quizzes, and a final. The course is based on the first five weeks of Professor Groh’s 2024 and 2025 Human and Machine Intelligence MORS950 course, and it’s continually updated with the latest science and industry insights. By the end, you should have the foundations for understanding AI as a manager and be equipped for AIML950, which offers a five week case-based and project-based deep dive into how to identify and evaluate AI opportunities to drive innovation and strategic decision making within your organization.