Santa Clara High Technology Law Journal Volume 37 Issue 2 Article 1 4-1-2021 COPYRIGHTING COPYWRONGS: AN EMPIRICAL ANALYSIS OF ERRORS WITH AUTOMATED DMCA TAKEDOWN NOTICES Seng, Daniel Follow this and additional works at: https://digitalcommons.law.scu.edu/chtlj Part of the Intellectual Property Law Commons, and the Science and Technology Law Commons Recommended Citation Seng, Daniel, COPYRIGHTING COPYWRONGS: AN EMPIRICAL ANALYSIS OF ERRORS WITH AUTOMATED DMCA TAKEDOWN NOTICES, 37 SANTA CLARA HIGH TECH. L.J. 119 (2021). Available at: https://digitalcommons.law.scu.edu/chtlj/vol37/iss2/1 This Article is brought to you for free and open access by the Journals at Santa Clara Law Digital Commons. It has been accepted for inclusion in Santa Clara High Technology Law Journal by an authorized editor of Santa Clara Law Digital Commons. For more information, please contact
[email protected]. COPYRIGHTING COPYWRONGS: AN EMPIRICAL ANALYSIS OF ERRORS WITH AUTOMATED DMCA TAKEDOWN NOTICES By Daniel Seng1 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.