My research examines the entanglements of artificial intelligence and legal reasoning. As an anthropologist, I follow scientists, engineers, lawyers, policymakers, businesspeople, and activists as they negotiate computational and legal frameworks to regulate ethical, political, and epistemological concerns. I situate the present debates in the histories of civil rights struggles, of risk-based thinking in capitalist institutions (private insurance, consumer credit, housing finance, health care, criminal justice), and of probability and statistics in the human sciences.
Beyond Legitimation: Rethinking Fairness, Interpretability, and Accuracy in Machine Learning (forthcoming)
Rodrigo Ochigame, Chelsea Barabas, Karthik Dinakar, Madars Virza, and Joichi Ito
35th International Conference on Machine Learning (ICML 2018)
Machine learning researchers will be unable to contend with issues of fairness, interpretability, and accuracy as long as they try to reduce these issues to strictly computational problems. Reductive understandings can give legitimacy to false claims, unexplained models, and unjust decisions. The problem of legitimation is especially troubling in the case of risk assessment algorithms in the US penal system.
Filtering Dissent: Social Media and Land Struggles in Brazil
Rodrigo Ochigame and James Holston
New Left Review 99 (2016)
Hailed as organizational tools of the oppressed, social media have also emerged as powerful surveillance apparatuses, but could existing power structures be reinforced even by the very algorithms they use to order data? A history of algorithmic filtering and a case study of its role in the land struggles of Brazil’s Guarani and Kaiowá peoples.