Josh is a PhD candidate in the Government Department and a Graduate Fellow at the Edmond J. Safra Center for Ethics.
His research explores the politics of machine learning. When the injustices of our world are encoded in big data, machine learning requires choices to be made, from which some win and some lose, and which shape the distribution of power over time. Josh’s dissertation explores what follows from recognizing this political character of machine learning, using machine learning to explore familiar problems in politics and law. It begins by critiquing the narrowness of current U.S. discrimination law, arguing for a broader focus on the historical aims of civil rights movements and applying them to machine learning. It then explores existing regulatory proposals for governing the power of technology companies to moderate speech using machine learning. The dissertation ends by asking what is at stake for the future of democracy as we work out how to govern the world’s most powerful decision-making tool – machine learning. Josh works part-time with Facebook, seeking to improve the way the company makes difficult decisions about the design and deployment of systems driven by machine learning. Josh is also working on projects with Danielle Allen on ‘Political Economy and Justice’ at the Edmond J. Safra Centre for Ethics, with the New America Foundation’s India-US Technology Policy programme to explore India’s proposals for governing data and machine learning, and with the Institute for the Future of Work in the UK to rethink UK discrimination law in the age of algorithms. Josh formerly worked as a Policy Advisor for the Labour Party in the British Parliament and graduated with a starred double first in Politics from Cambridge University.