Principal Investigator: Mona Sloane, NYU
Collaborators: John Havens, IEEE; Rumman Chowdhury, Parity
This project is a collaboration between the NYU Alliance for Public Interest Technology, the Institute of Electrical and Electronics Engineers (IEEE) and Parity, a collaborative platform that utilizes AI/ML to extract useful information from qualitative methods and combines them with rigorous quantitative assessments. It contributes to the emerging field of Public Interest Technology (PIT) and addresses the fact that there is little research and interdisciplinary exchange on issues pertaining to data science, public procurement, and transparency and justice. This is a glaring gap: 12% of the global GDP is spent following procurement regulation (World Economic Forum, 2020), and procurement is a core mechanism through which algorithmic power is distributed in public institutions.
To fill this gap, this project will consist of three interdisciplinary “Procurement Roundtables” – one focused on data science solutions used by public institutions, one focused on algorithmic justice and responsible AI, and one focused on governance innovation. These roundtables will bring together experts in data science, social science (particularly critical technology studies), and governance.
Timeline: November 2020 — March 2021
Contact: Mona Sloane, email@example.com