Aditi Ramesh – Medium

Published in Data Stewards Network

·Jul 13, 2021

JOIN US: Open Peer Review of new Data Artefact Study: “Facebook’s Population Density Map”

At The GovLab, we are interested in how data can improve the way we make decisions in the public interest. One particular area of inquiry involves the emergence of new data analytical products from collaborative innovations in how data was re-used for public good. We call these new and innovative…

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JOIN US: Open Peer Review of new Data Artefact Study: “Facebook’s Population Density Map”

3 min read

Published in Data Stewards Network

·Jul 1, 2021

Global Perspectives on AI Ethics Panel #5: Confronting the realities of data subjects, AI governance at the local level, and building an ethically conscious business culture

AI Ethics: Global Perspectives is a free, online course jointly offered by The Governance Lab (The GovLab) at the NYU Tandon School of Engineering, the Global AI Ethics Consortium (GAIEC), Center for Responsible AI @ NYU (R/AI), and the TUM Institute for Ethics in Artificial Intelligence (IEAI). It conveys the…

5 min read

Global Perspectives on AI Ethics Panel #5: Confronting the realities of data subjects, AI…

5 min read

Published in Data Stewards Network

·Jun 17, 2021

Global Perspectives on AI Ethics Panel #4: data equity, perspectives from the Global South, high risk profiling systems, and the role of universities

6 min read

Published in Data Stewards Network

·Apr 29, 2021

Global Perspectives on AI Ethics Panel #3: EU’s new AI regulation, the use of social robots in care settings, evaluating training datasets, and the need for more independent research on AI Ethics

AI Ethics: Global Perspectives is a free, online course jointly offered by The Governance Lab (The GovLab) at the NYU Tandon School of Engineering, The Global AI Ethics Consortium (GAIEC), Center for Responsible AI @ NYU (R/AI), and the TUM Institute for Ethics in Artificial Intelligence (IEAI). It conveys the…

6 min read

Global Perspectives on AI Ethics Panel #3: EU’s new AI regulation, the use of social robots in…

6 min read

Published in Data Stewards Network

·Mar 29, 2021

Global Perspectives on AI Ethics Panel #2: Moving beyond data regimes, collective approaches to data, and deriving contextual standards and policies for AI

Events

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Global Perspectives on AI Ethics Panel #2: Moving beyond data regimes, collective approaches to…

Events

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Published in Data Stewards Network

·Mar 2, 2021

Improving oversight, asking the right questions, and cultivating diversity in AI systems

AI Ethics: Global Perspectives is a free, online course jointly launched by The Governance Lab (The GovLab) at the NYU Tandon School of Engineering, The Global AI Ethics Consortium (GAIEC), Center for Responsible AI @ NYU (R/AI), and the TUM Institute for Ethics in Artificial Intelligence (IEAI), which aims to…

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Global Perspectives on AI Ethics Panel #1: Improving oversight, asking the right questions, and…

5 min read

Published in Data Stewards Network

·Feb 5, 2021

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

BROOKLYN, New York, Wednesday, 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…

5 min read

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

5 min read

Published in Open Data Policy Lab

·Oct 21, 2020

Toward Responsible Data Re-Use for COVID-19 in New York City: Key Takeaways from The Data Assembly

By Aditi Ramesh, Andrew Young, and Andrew J. Zahuranec The Data Assembly is an initiative from The GovLab supported by the Henry Luce Foundation to solicit diverse, actionable public input on data re-use for crisis response in the United States. …

8 min read

Toward Responsible Data Re-Use for COVID-19 in New York City: Key Takeaways from The Data Assembly

8 min read