About the Event
The most valuable companies in the world create value for their customers through data, networks, and algorithms. But most of that value is consumed in the developed world. Is the digital era only going to benefit first-world countries?
Rem Koning, Mary V. and Mark A. Stevens Associate Professor of Business Administration, and Tarun Khanna, Jorge Paulo Lemann Professor at the Harvard Business School, presented new work on the impact of data and AI on entrepreneurship and innovation in emerging and developing markets, based on their latest research conducted at their Tech for All Lab at the Digital Data Design (D^3) Institute at Harvard University. Professor Koning presented a field experiment the lab has completed on the uneven impacts of generative AI advice on entrepreneurial performance in Kenya (paper title, link, and abstract below). Professor Khanna discussed the lab's emergent research on digital public goods like IndiaStack in driving entrepreneurship and growth for all.
The Tech for All lab's research agenda aims to promote digital accessibility by focusing on:
- Identifying the frictions that drive wedges between technologies and sub-populations who should be using these.
- How start-ups and incumbents can develop tech-enabled strategies to benefit the underserved and create value for the firm.
- The impact of data and digitization on firm strategy, the workforce, and society.
- How technology can be used to identify “lost talent” that existing labor markets overlook.
- What types of consumers benefit from innovation and how companies can build innovation pipelines that are more inclusive.
Free admission, RSVP required.
About Rem Koning and Tarun Khanna
Rem Koning is the Mary V. and Mark A. Stevens Associate Professor of Business Administration at Harvard Business School. His work explores the drivers of entrepreneurial progress and inclusive innovation. He is the co-director of the Tech for All lab at The Digital, Data, and Design (D^3) Institute at Harvard, where he leads a group of interdisciplinary researchers studying how the rate and direction of science, technology, and startups can be accelerated and shifted to better benefit women, minority groups, and people in emerging and developing countries.
He co-leads the Conference on Field Experiments in Strategy (CFXS), is an associate editor for Management Science, and is an invited researcher at J-PAL's Science for Progress Initiative (SfPI). He teaches a new semester-length second-year elective course at HBS, Strategy for Entrepreneurs (SFE), that blends case discussion and hands-on exercises to help students discover and test startup ideas that the market has missed.
Tarun Khanna is the Jorge Paulo Lemann Professor at the Harvard Business School and Director of Harvard University's Lakshmi Mittal & Family South Asia Institute. For over 25 years, he has studied entrepreneurship as a means of economic development. He currently teaches courses related to creativity in emerging economies. Over ~600,000 students in over 200 countries have taken an online version of the course, Entrepreneurship in Emerging Economies, now one of Harvard's most popular. A recent book, Trust, and an earlier one, Billions of Entrepreneurs, chronicle creative ventures in China, India and beyond.
There is a growing belief that scalable and low-cost AI assistance can improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it hard to generalize from recent studies showing that generative AI improves performance on well-defined writing tasks. In our five-month field experiment with 640 Kenyan entrepreneurs, we assessed the impact of AI-generated advice on small business revenues and profits. Participants were randomly assigned to a control group that received a standard business guide or to a treatment group that received a GPT-4 powered AI business mentor via WhatsApp.
While we find no average treatment effect, this is because the causal effect of generative AI access varied with the baseline business performance of the entrepreneur: high performers benefited by just over 20% from AI advice, whereas low performers did roughly 10% worse with AI assistance. Exploratory analysis of the WhatsApp interaction logs shows that both groups sought the AI mentor's advice, but that low performers did worse because they sought help on much more challenging business tasks. These findings highlight how the tasks selected by firms and entrepreneurs for AI assistance fundamentally shape who will benefit from generative AI.
About the Nardone Family Seminar Series
Made possible by a gift from David R. Nardone, this seminar series brings scholars and practitioners to Northeastern University to share insights on emerging markets.