Algorithmic (In)Tolerance: Experimenting with Beethoven’s Music on Social Media Platforms

Abstract

Popular social media platforms, such as YouTube and Facebook, see insurmountable volumes of media uploaded every day. The extent of which cannot be feasibly monitored through human efforts alone to identify infringing activity. Such companies employ algorithmic methods to enforce copyright by removing or monetizing content on behalf of copyright owners; however, occasionally flagged material is misidentified as infringing. These instances represent a potential loss of income for independent artists by way of misappropriated revenue or removal of material, and time spent challenging automated decisions. This article discusses an experiment seeking to ascertain the false positive rate of YouTube’s Content ID and Facebook’s Rights Manager. This is put in the context of existing legal precedence in the United States, including the Digital Millennium Copyright Act (DMCA). The article makes recommendations for technological and logistical modifications to these systems, and it encourages public education and research on the topic.

Keywords

• social media
• public domain, fair use
• copyright
• algorithmic moderation
• digital rights management