Katherine Oyama is Senior Policy Counsel for Google in Washington, DC, where she manages U.S. federal policy for copyright, trademark, music licensing, online creativity, and intermediary liability. From 2009 to 2011, she worked at the White House as Associate Counsel and Deputy Counsel to Vice President Joseph R. Biden. Prior to her government service, Katherine was a litigation associate at Wilmer Cutler Pickering Hale & Dorr’s Washington office. She previously worked for a New York-based strategy consulting firm; Marc Andreessen's Silicon Valley-based startup, LoudCloud; and a Washington-based public interest research organization.
Katherine is a graduate of Smith College, where she graduated with High Honors in Government, and the University of California, Berkeley School of Law (Boalt Hall), where she served as senior articles editor of the Berkeley Technology Law Journal (BTLJ).
She has testified before Congress on issues relating to copyright, trademark, and the creative economy multiple times. In addition to her work in the U.S., Katie has represented Google on global trade and digital economy issues at the United Nations (UN), Internet Governance Forum (IGF), World Intellectual Property Organization (WIPO), World Trade Organization (WTO), European Union (EU), U.S. Mission to the EU, World Economic Forum (WEF) and met with policymakers on 6 continents. She is a board member of the Digital Media Association (DiMA) (the leading digital music services organization in the U.S.) and serves on the advisory boards of the Duke Law Center for Innovation Policy, the American Library Association Public Policy Advisory Council (PPAC), and the Atlas Corp Tech Advisory Board.
Objectives.
- Engage with the Cambridge community on the policy issues influencing—and influenced by—machine learning and AI;
- Learn from researchers and engineers about how data and copyrighted works enable (and constrain) machine learning;
- Solicit viewpoints on whether current copyright frameworks enable or restrict machine learning;
- Analyze model frameworks for emerging digital markets seeking to support machine learning research (e.g., Singapore, South Africa, Korea, Israel, etc.)
- Document ways in which national law can restrict machine learning activities due to restrictive copyright rules lacking fair use or text and data mining flexibilities (e.g., EU, France, Germany, Australia, Mexico, New Zealand, Vietnam, Chile, etc.)
