The R/AI Rockstar series aims to improve the representation of women and members of historically under-represented groups in AI careers. We do this by bringing role models who work on RAI topics and contribute to the diversity of voices in this area of research, education, and practice. The second Rockstar in this series, Dr. Moshe Y. Vardi, will …
As part of a continuing effort led by the Director of R/AI, Dr. Julia Stoyanovich, 13 research fellows from the Ukrainian Catholic University and other universities from Ukraine collaborated with faculty and graduate students from New York University, the University of Washington, and the University of Edinburgh in 6 research projects on Responsible AI through …
R/AI Responsible AI Research Program – Fall 2022 Project Showcase Read More »
The RAI Rockstar series aims to improve the representation of women and members of historically under-represented groups in AI careers. We do this by bringing role models who work on RAI topics and contribute to the diversity of voices in this area of research, education, and practice. Our first RAI Rockstar, Dr. Sihem Amer-Yahia, will visit NYU R/AI …
The 10th edition of Maker Faire in Rome hosted one of the largest platforms for inventors and enthusiasts to share and learn about the ongoing inventions happening world-over. Julia Stoyanovich attended Maker Faire Rome in October, and spoke about making Responsible AI synonymous with AI at the Opening Conference, in a talk titled “IA responsabile: …
The Innovations Dialogue: AI Disruption, Peace, and Security (ID22) is the 4th edition of the flagship conference conducted by UNIDIR with a focus on the future of artificial intelligence (AI), potential risks and rewards of AI technologies for international peace and security, and exploring the path to Responsible AI. Dr.Julia Stoyanovich will speak in the …
Explanations for query results have been the subject of extensive research. The advantages of such explanations are evident, as they allow users to validate and justify the results of the query and deepen their knowledge about the data. However, when the query is proprietary and needs to remain confidential or when the data is cloaked …
Research Seminar: On the Tradeoff Between Explainability and Privacy in Databases Read More »
The research team at R/AI conducted an audit on automated hiring systems used by prominent companies. The main contribution was the development of a socio-technical framework for auditing the stability of algorithmic systems. Read more about our findings in the paper we published at the AIES’22 Conference and our journal paper. Video Presentation:
The ongoing war in Ukraine has displaced hundreds of thousands of people, including many university students. The Ukrainian Catholic University (UCU) in Lviv, has been active in their attempts to keep the students engaged and to allow them to successfully complete the academic year. To support these efforts, NYU’s Center for Responsible AI (R/AI) collaborated …
In Spring 2021, the All Aboard project funded by the NSF Northeast Big Data Hub brought together data scientists, disability scholars and activists and social scientists to devise new workflows for making public education on AI and data science more accessible. The group used the existing public education portfolio of the NYU Center for Responsible …
This summer, the NYU Tandon Center for Responsible AI (NYU R/AI) has had the pleasure of hosting 19 Research Fellows from Ukrainian universities in a fully remote 6-week research program. The Fellows worked on 8 exciting projects on a range of topics, including algorithmic fairness, explainability, data quality, differentially private synthetic data generation, and social …
