Add to Calendar: Google | Outlook | Office365 | Yahoo
Marshall Van Alstyne is the Allen and Kelli Questrom Professor of Information Systems at Boston University. He is one of the world’s foremost experts on network business models and coauthor of the international bestseller Platform Revolution. He conducts research on information economics, covering such topics as the economics of speech markets, platform economics, intellectual property, social effects of technology, and productivity effects of information. He has been a major contributor to the theory of two-sided networks taught worldwide, and to the theory of platforms as inverted firms, applied in antitrust law.
Website: https://www.bu.edu/questrom/profiles/marshall-van-alstyne/
Paper: https://drive.google.com/file/d/11cz6scvhxfj8E7zyiDWRGZZXIkOpq2wR/view?usp=drive_link
Abstract
If different intellectual property regimes create different incentives, which ones hasten dynamic innovation? This research shows that, when innovation hinges on fast combinations of private information, as in the case of modern machine learning, an ex-ante commitment to fairness increases innovation compared to traditional property rights. We prove formally that welfare improves in the absolute sense of enabling new projects and in the relative sense of reordering projects that people undertake. Second, in contrast to models of ``other regarding'' preferences, we show self-interest alone is sufficient to motivate fairness in a one-time encounter. Adapting an idea from Rawls, the gap between present and future provides the ``veil of ignorance'' needed to justify self-interested fairness. Third, we show how the hold-up problem is worse for information than for tangible goods. Fourth, we sketch a practical way to promote fairness using liability rules rather than property rights. Liability rules give idea-developers greater flexibility and incentives yet protect them from exploitation. The problem is old but, in the modern context, fairness helps thread the needle between a property system that requires machine learning systems to negotiate with millions of copyright owners and an open system that does not require compensating information sources but then does not motivate open sharing.
If you would like to give a presentation in a future webinar, contact our Senior Economist Dr. Wen Chen (wen.chen@luohanacademy.com). For other inquiries, please contact: events@luohanacademy.com.