Digital Commons Network^™

The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag

Faculty Articles

Now that the dust has settled on the Authors Guild cases, this Article takes stock of the legal context for TDM research in the United States. This reappraisal begins in Part I with an assessment of exactly what the Authors Guild cases did and did not establish with respect to the fair use status of text mining. Those cases held unambiguously that reproducing copyrighted works as one step in the process of knowledge discovery through text data mining was transformative, and thus ultimately a fair use of those works. Part I explains why those rulings followed inexorably from copyright's most …

Beyond Abstraction: The Law And Economics Of Copyright Scope And Doctrinal Efficiency, Matthew Sag

Faculty Articles

Uncertainty as to the optimum extent of protection generally limits the capacity of law and economics to translate economic theory into coherent doctrinal recommendations in the realm of copyright. This Article explores the relationship between copyright scope, doctrinal efficiency, and welfare from a theoretical perspective to develop a framework for evaluating specific doctrinal recommendations in copyright law.

The usefulness of applying this framework in either rejecting or improving doctrinal recommendations is illustrated with reference to the predominant law and economics theories of fair use. The metric-driven analysis adopted in this Article demonstrates the general robustness of the market-failure approach to …