معرفی
Eric B. Zhou is a Lecturer in Information Systems and PhD Candidate in Information Systems at Boston University Questrom School of Business (expected 2026), affiliated with the Digital Business Institute and BIT Lab under advisor Professor Dokyun Lee. He is actively on the 2025-26 academic job market after transitioning from Washington University in St. Louis in 2023.
His educational background includes:
- MS in Business Administration, Washington University in St. Louis Olin Business School (2023)
- MBA, Carnegie Mellon University Tepper School of Business (2021)
- BSBA, Washington University in St. Louis Olin Business School (2018)
Eric's research centers on the co-evolution of human and artificial intelligence, specifically investigating how generative AI augments human creativity rather than displacing it. He examines societal consequences of generative AI and creative market responses through interdisciplinary lenses combining philosophy, psychology, and AI. His methodological toolkit integrates causal inference with deep learning, LLMs, and multimodal analysis to address how AI impacts fundamentally human domains.
His publication trajectory reveals a focused exploration of generative AI's creative impact: early work (2024) established baseline productivity and novelty effects in art markets, while his 2025 Science Advances paper identifies evolutionary patterns from concentrated 'mastermind' breakthroughs to distributed 'hivemind' innovation following open-source model releases. Both studies leverage massive art platform datasets to demonstrate AI's dual role in enhancing aggregate creativity while altering individual novelty patterns.
Research recognition includes:
- Marketing Science Institute grant ($5,000) as Co-PI
- Questrom Outstanding Research Award
- Falling Walls Science Breakthrough nomination (2024)
- WISE Best Student Paper Finalist (2022)
As an educator, Eric teaches IS223: Introduction to Information Systems with emphasis on practical AI integration. Student testimonials consistently praise his ability to make technical concepts accessible through real-world applications and transparent discussions about AI's workplace implications. His teaching philosophy centers on developing critical AI competency as a professional advantage while addressing ethical considerations.
Eric maintains active research collaborations within the BIT Lab and with scholars including Dokyun Lee, Bin Gu, Gordon Burtch, and Daniel Rock, focusing on policy implications for equitable AI-mediated creative markets.
