Press

Le Monde “Miroir, mon beau miroir”

Our Mirror Mirror comic in french featured in Le Monde

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Unite.AI “Prof. Julia Stoyanovich, Director of the Center for Responsible AI – Interview Series”

February 9, 2021. Julia Stoyanovich, is a professor at NYU’s Tandon School of Engineering and founding Director of the Center for Responsible AI. She recently delivered testimony to the NYC Council’s Committee on Technology about a proposed bill that would regulate the use of AI for hiring and employment decisions.

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CATO Institute Blog “Algorithmic Bias Under the Biden Administration”

February 5, 2021. This is the third and final entry analyzing technology policy issues (the gig economy, online speech, and algorithmic bias) under the Biden administration.

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NewsWise “Free, online course brings together 20 global experts in the field of ethical AI”

February 3, 2021. The Governance Lab (The GovLab), NYU Tandon School of Engineering, Global AI Ethics Consortium (GAIEC), Center for Responsible AI @ NYU (R/AI), and Technical University of Munich (TUM) Institute for Ethics in Artificial Intelligence (IEAI) jointly launched a free, online course, AI Ethics: Global Perspectives, on February 1, 2021.

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SHRM “HireVue Discontinues Facial Analysis Screening”

February 3, 2021. Decision reflects re-examination of AI hiring tools

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Toronto Star “How can we be assured smart city tech will do more good than harm? It all comes down to governance”

January 14, 2021. Earlier this fall, Julia Stoyanovich, a New York University assistant professor of computer science, engineering, and data science, and Falaah Arif Khan, a research fellow and artist-in-residence at NYU’s Centre for Responsible AI, published “Mirror, Mirror,” the first of a series of “scientific comics” entitled “Data, Responsibly.”

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WIRED “New York City Proposes Regulating Algorithms Used in Hiring”

January 8, 2021. A bill would require firms to disclose when they use software to assess candidates, and vendors would have to ensure that their tech doesn’t discriminate.

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SHRM “New York City Considers Regulating AI Hiring Tools”

December 7, 2020. Employers would be required to inform job applicants if and how they are using artificial intelligence (AI) technology in hiring decisions under a bill being considered by the New York City Council.

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CBS News “New York City wants to restrict artificial intelligence in hiring”

November 20, 2020. New York City is trying to rein in the use of algorithms used to screen job applicants. It's one of the first cities in the U.S. to try to regulate what is an increasingly common — and opaque — hiring practice.

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Medium “Data, ethics and humor. Teaching data responsibility through comics”

October 20, 2020. As the field of data science matures and its practitioners make more and more advancements, many have raised valid questions about how to make these advancements in a manner that is responsible to the people they will impact. As a response to this, CDS faculty Julia Stoyanovich collaborated with Falaah Arif Khan, a Research Fellow in the CVIT Lab at IIIT-Hyderabad and an Artist in Residence at the NYU Center for Responsible AI and at the Montreal AI Ethics Institute, to create the comic “Mirror, Mirror,” the first in a series that attempts to answer the field’s most pressing questions head-on.

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Government Technology “Comic Book Bridges Gap Around Education in AI, Ethics”

September 29, 2020. The Data, Responsibly project, based out of New York University, has taken its research on responsible data management and expanded it to improve messaging around what it means to collect and use data ethically.

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IEEE Spectrum “The Devil is in the Data: Overhauling the Educational Approach to AI’s Ethical Challenge”

The New York University Tandon School of Engineering is taking a novel approach to educating the next generation of computer scientists and data scientists on the ethical implications of AI

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The Chronicle of Higher Education “Is AI Effective If It Isn’t Equitable and Responsible?””

In the early days of the COVID-19 pandemic, officials in many states based their decisions about who would get a scarce coronavirus test and where to set up testing facilities on the demographics of the first groups of patients. It was, they asserted, a purely straightforward and data-driven approach that just happened to lead them to focus on affluent, White communities. As a result, poor people and people of color — many with underlying conditions that increased their risk — suffered disproportionately as the virus ravaged their neighborhoods.

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