
Dokyun (DK) Lee
Kelli Questrom Associate Professor in Information Systems
Dokyun ”DK” Lee, is a Kelli Questrom Chair Associate Professor of Information Systems and Computing & Data Science School at Boston University. He studies the {responsible application, development, and impact} of AI in business with a focus on unstructured data. He founded Business Insights through Text Lab (www.dkBITLAB.com) (PI) and BU Digital Business Institute Generative AI Lab (Co-lead).
Specific interests are:
1) Generative AI (unintended consequence and human-integration frictions)
2) Economics of unstructured data (content extraction, understanding, engineering, marketing)
3) Unintended Consequence of AI in Business
in the context of digital consumer management, platform design, market competition, advertising, human-ai collaboration, innovation, and creativity.
He is a recipient of INFORMS ISS Gordon B David Young Scholar, INFORMS ISS Sandy Slaughter Early Career, CDO Magazine Leading Academic Data Leader, and Marketing Science Insititute Young Scholar Awards. His research has been published in journals such as Management Science, Information Systems Research, MISQ, Journal of Marketing Research, AAAI, AIES, and WWW. His work is supported by organizations such as Adobe, Bosch Institute, Google, Marketing Science Institute, McKinsey & Co, Nvidia, Net Institute, and Prudential Foundation.
DK holds a Bachelor’s degree in Computer Science from Columbia University (Machine Learning Focus), a Master’s degree in Statistics (Master’s Thesis: Johnson-Lindenstrauss Lemma and its Effect on Supervised Learning) from Yale University, and a Ph.D. from the Operation, Information, and Decisions department of the Wharton School (Thesis: Three Essays in Big Data Consumer Analytics in E-Commerce).
Before academia, DK worked at 4 tech start-ups and Blackrock as a quantitative software engineer and at Thomson Reuters as an ML contractor building a natural language processing engine for financial data.
Please contact for Academic-Industry research collaboration, consulting, and speaking inquiries.
Education
Phd, The Wharton School, 2015
MA, Yale University, 2010
BA, Columbia University, 2009
Selected Research Presentations
Lee, D. Take Caution in Using LLMs as Human Surrogates: Scylla Ex Machina, Arizona State University, Arizona State University, 2025
Lee, D. Take Caution in Using LLMs as Human Surrogates: Scylla Ex Machina, New York University, New York University, 2025
Lee, D. Take Caution in Using LLMs as Human Surrogates: Scylla Ex Machina, Conference on Artificial Intelligence, Machine Learning, and Business Analytics, Yale University, 2024
Lee, D. Take Caution in Using LLMs as Human Surrogates: Scylla Ex Machina, Harvard Business School, Harvard Business School, 2024
Lee, D. Take Caution in Using LLMs as Human Surrogates: Scylla Ex Machina, Wharton 2nd Annual Business & Generative AI Workshop, San Francisco, 2024
Lee, D. Generative AI, Human Creativity, and Art, University of Hyderabad, 2024
Lee, D. Generative AI, Human Creativity, and Art, Tel Aviv Unviversity, Tel Aviv Unviversity, 2024
Lee, D. Generative AI, Human Creativity, and Art, University of Arizona, University of Arizona, 2024
Lee, D. Generative AI, Human Creativity, and Art, University of Florida, University of Florida, 2024
Lee, D. Generative AI, Human Creativity, and Art, CCNY Baruch College, 2024
Lee, D. Generative AI, Human Creativity, and Art, Purdue University, Purdue University, 2024
Lee, D. Generative AI, Human Creativity, and Art, Case Western University, 2024
Srinivasan, S. , Jing, C. , Lee, D. , Fournier, S. Do or Do Not, There Is No Try: Firm Response to Sociopolitical Risk Events, Indian Institute of Management Ahmedabad, 2023
Lee, D. Generative AI, Human Creativity, and Art, MIT, 2023
Jing, C. , Lee, D. , Srinivasan, S. , Fournier, S. Do or Do Not, There Is No Try: Firm Response to Sociopolitical Risk Events, BU IMAP, 2023
Lee, D. Generative AI, Human Creativity, and Art, University of Tennessee, Knoxville, 2023
Lee, D. Generative AI, Human Creativity, and Art, UT Dallas, 2023
Lee, D. Generative AI, Human Creativity, and Art, UW Milwaukee, 2023
Srinivasan, S. , Jing, C. , Lee, D. Firm Sociopolitical Performance Radar, ISMS Marketing Science Conference, Miami, FL, 2023
Srinivasan, S. , Jing, c. , Lee, d. , Fournier, s. Do or Do Not, There Is No Try: Firm Response to Sociopolitical Risk Events, EMAC virtual presentation, Odense Denmark, 2023
Lee, D. Digital Marketing Symposium: Relevance and Privacy- Leveraging Personalized Marketing for Responsible Growth, Questrom School, 2023
Lee, D. DBI + Susilo Institute Symposium: The Emerging Impact of AI on Consumer Engagement, Questrom School, 2023
Lee, D. University Invited Seminar: InnoVAE: Generative AI for Understanding Patents and Innovation, American University, 2023
Cheng, Z. , Jin, G. , Leccese, M. , Lee, D. , Wagman, L. Startup Buyout and Patentable Innovation: New Evidence from PatentsView, AEA, 2023
Kim, K. , McCarthy, D. , Lee, D. Deep Learning Methods for Customer Base Analysis: Evidence from 1000 companies over 6 years, WISE, Denmark, 2022
Zhou, E. , Hui, X. , Lee, D. Virtue Signaling Via Image in Second-Hand Markets: Evidence from the GPU Market, WISE, Denmark, 2022
Lee, D. Innovation Information Initiative Technical Working Group Meeting, NBER, 2022
Srinivasan, S. , Jing, C. , Lee, D. , Fournier, S. Managing and Mitigating Sociopolitical Firm Risk Events, Marketing Dynamics Conference, Georgia State University, 2022
Kim, K. , McCarthy, D. , Lee, D. Deep Learning Methods for Customer Base Analysis: Evidence from 1000 companies over 6 years, MARKETING DYNAMICS CONFERENCE, 2022
Lee, D. Human Flourishing and the futures of Intelligence, Stanford, 2022
Kim, K. , McCarthy, D. , Lee, D. Deep Learning Methods for Customer Base Analysis: Evidence from 1000 companies over 6 years, Marketing Strategy Meets Wall Street Conference, 2022
Lee, D. The future of customer analytics, driven by AI, Meta NYC, 2022
Publications
Lee, D., Anandasivam, G., Lee, D., Dongwook, S. (In Press). “Nudging Private Ryan: Mobile Micro-giving under Economic Incentives and Audience Effects”, MIS Quarterly
Manzoor, E., Chen, G., Lee, D., Smith, M. (In Press). “Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online”,
Manzoor, E., Chen, G., Lee, D., Smith, M. (In Press). “Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online”, Management Science
Zhang, S., Lee, D., Singh, P., Srinivasan, K. (In Press). “How Much Is an Image Worth? Airbnb Property Demand Estimation Leveraging Large Scale Image Analytics”, SSRN Electronic Journal
Hsu, P., Lee, D., Tambe, P., Hsu, D. (In Press). “Deep Learning, Text, and Patent Valuation”, SSRN Electronic Journal
Ahn, D., Lee, D., Hosanagar, K. (In Press). “Interpretable Deep Learning Approach to Churn Management”, SSRN Electronic Journal
Burtch, G., He, Q., Hong, Y., Lee, D. (In Press). “Peer Awards Retain New Users and Encourage Exploitation in Users’ Production of Creative UGC”, SSRN Electronic Journal
Lee, D., Hosanagar, K. (In Press). “How Do Product Attributes Moderate the Impact of Recommender Systems?”, SSRN Electronic Journal
Lee, D., Cheng, Z., Mao, C., Manzoor, E. (2024). “Guided Diverse Concept Miner (GDCM): Uncovering Relevant Constructs for Managerial Insights from Text”, Information Systems Research
Burtch, G., Lee, D., Chen, Z. (2024). “The consequences of generative AI for online knowledge communities”, Sci Rep, 14 (1), 10413-10413
Zhou, E., Lee, D. (2024). “Generative artificial intelligence, human creativity, and art.”, PNAS Nexus, 3 (3), pgae052-
Burtch, D., Lee, d., Chen, z. (2024). “Generative AI Degrades Online Communities”, Communications of the ACM, 67 (3), 40-42
Shi, Z., Liu, X., Lee, D., Srinivasan, K. (2023). “How Do Fast-Fashion Copycats Affect the Popularity of Premium Brands? Evidence from Social Media”, Journal of Marketing Research, 60 (6), 1027-1051
Hosanagar, K., Lee, D. (2023). “AI in Personalized Product Recommendations”, Management and Business Review
Lazar, M., Mateja, D., Lifshitz-Assaf, H., Yoo, Y., Ding, M., Nickerson, J., Wolfson, B., Cheng, Z., Lee, D., Tambe, P., Cao, X. (2023). “Innovation in the Digital Age: Expanding the Boundaries of the Creative Process with Generative AI”, Academy of Management Proceedings, 2023 (1)
Zhaoqi, C., Jin, G., Leccese, M., Lee, D., Wagman, L. (2023). “M&A and Innovation: A New Classification of Patents”, American Economic Association. Papers and Proceedings, 113 288-293
Burtch, G., He, Q., Hong, Y., Lee, D. (2022). “How Do Peer Awards Motivate Creative Content? Experimental Evidence from Reddit”, Management Science, 68 (5), 3488-3506
Zhang, S., Lee, D., Singh, P., Srinivasan, K. (2021). “What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features”, Management Science
Zhang, S., Lee, D., Singh, P., Mukhopadhyay, T. (2021). “EXPRESS: Demand Interactions in Sharing Economies: Evidence from a Natural Experiment Involving Airbnb and Uber/Lyft”, Journal of Marketing Research 002224372110621-002224372110621
Wang, W., Zhao, H., Lee, D., Chen, G. (2021). “Machine Learning for Consumers and Markets”, Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining 4165-4166
Lee, D., Hosanagar, K. (2021). “How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages?”, Management Science, 67 (1), 524-546
Proserpio, D., Hauser, J., Liu, X., Amano, T., Burnap, A., Guo, T., Lee, D., Lewis, R., Misra, K., Schwarz, E., Timoshenko, A., Xu, L., Yoganarasimhan, H. (2020). “Soul and machine (learning)”, Marketing Letters, 31 (4), 393-404
Liu, X., Lee, D., Srinivasan, K. (2019). “Large-Scale Cross-Category Analysis of Consumer Review Content on Sales Conversion Leveraging Deep Learning”, Journal of Marketing Research, 56 (6), 918-943
Lee, D., Hosanagar, K. (2019). “How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment”, Information Systems Research, 30 (1), 239-259
Lee, D., Hosanagar, K., Nair, H. (2018). “Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook”, Management Science, 64 (11), 5105-5131
Lee, D., Gopal, A., Lee, D. (2018). “Micro-Giving: On the Use of Mobile Devices and Monetary Subsidies in Charitable Giving”, Academy of Management Proceedings, 2018 (1), 15011-15011
Lee, D., Hosanagar, K. (2016). “When do Recommender Systems Work the Best?”, Proceedings of the 25th International Conference on World Wide Web 85-97
Hosanagar, K., Fleder, D., Lee, D., Buja, A. (2014). “Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation”, Management Science, 60 (4), 805-823