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37 Santa Clara High Tech. L. J. 119 (2021)
Copyrighting Copywrongs: An Empirical Analysis of Errors with Automated DMCA Takedown Notices

handle is hein.journals/sccj37 and id is 121 raw text is: COPYRIGHTING COPYWRONGS: AN EMPIRICAL ANALYSIS OF ERRORS WITH AUTOMATED DMCA TAKEDOWN NOTICES By Daniel Seng' Under the Digital Millennium Copyright Act (DMCA), reporters issuing takedown notices are required to identify the infringed work and the infringing material and provide their contact information (functional formalities), attest to the accuracy of such information and their authority to act on behalf of the copyright owner, and sign the notices (non-functional formalities). Online service providers will evaluate such notices for compliance with these DMCA formalities before acting on them. This paper seeks to answer questions about the quality of takedown notices, especially those generated by automated systems, which are increasingly being used by copyright owners to detect instances of online infringement and issue takedown notices on their behalf After parsing three million takedown notices and more than eighty million takedown complaints served on Google between 2011 and 2015, this paper analyzes each notice for errors. This paper finds that almost all notices comply with the non-functional formalities. However, at least 5.5% of all takedown notices between 1 Daniel Seng, Associate Professor, Faculty of Law, National University of Singapore. I would like to thank Mark Lemley, Deborah Hensler, Phil Malone and Maria Jose Cordero for their useful feedback and suggestions for an earlier draft of this paper, which was entitled Trust But Verify. I would also like to record my deepest thanks to Shaun Lim for his invaluable help in revising this paper and updating the statistics with the porting of the Chilling Effects database onto the Lumen platform. The original material for this paper based on the Chilling Effects database was first presented at the 15th Year Retrospective of the Digital Millennium Copyright Act, Santa Clara University on March 15, 2013. It has since been updated with the dataset from the Lumen database. I also wish to thank Adam Holland from the Berkman Klein Centre for Internet & Society, Harvard University, for his kindness in enabling me unprecedented access to the Lumen database for purposes of this research. Funding support for the research that made this paper possible is provided by the National University of Singapore through the Singapore Ministry of Education Academic Research Fund Tier 1. 119