Events

Fri 03/12/21 05:00 - 7:00pm Virtual

Understanding and Addressing Algorithmic Bias in Hiring

This online session is designed to generate insight into algorithmic bias in employment assessment software tools (aka hiring). Using a rotating presenter/panel format and building on timely field-based debates, the goal is to establish a common point of entry into the issue by tackling the socio-historical foundation of bias in technology that is present in today’s systems, especially algorithmic auditing initiatives (Mona Sloane); engaging in a deep dive into how these tools actually work, including the role of data in decisions, through the accessible metaphor of baking sourdough bread (Julia Stoyanovich); and sharing concrete evidence of current impacts through recent research, first-hand experience of such tools and critical perspectives on algorithmic auditing (Hilke Schellmann).

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Co-Opting AI: Games

This event will explore the deep historical and cultural links between games and technology, and specifically artificial intelligence. Featuring Kishonna L. Gray, Bo Ruberg, Julian Togelius, and Mona Sloane, the discussions will examine how games serve as a frontier of AI research, but also what – and whose – narratives shape “technological innovation” and “progress”, how this is connected to gaming cultures (or not), and how it is linked to wider structures of power and oppression.

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Digital Life Seminar | No. 2

The public Digital Life seminar series offers students and guests an opportunity to engage actively with leading scholars and practitioners researching and responding to the development and application of digital technologies.

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TechTalks: Tackling Race, Bias & Inequality in Artificial Intelligence

Artificial Intelligence (AI) is increasingly impacting our lives and interacting with the biases and inequalities that exist in our society.

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Co-Opting AI: Security

NYU’s Institute for Public Knowledge, the NYU Center for Responsible AI, and the 370 Jay Project invite you to a discussion on finance in the series “Co-Opting AI.” Narratives, policies, and innovations in AI are often tied up with notions of “security”. While our increasingly AI-mediated social world is vulnerable to different forms of cyber threats, “security” also serves as justification for large-scale surveillance of already over-policed and oppressed communities. The event will feature Laura Norén, Ram Shankar Siva Kumar, Newton Campbell, and Mona Sloane and will examine links between the topics of algorithmic harm, national security, and cybersecurity, and to ask what – or who – counts as “risk” or as “threat” in the context of AI.

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MLK Week Kick-Off: Courageous Conversations in AI

It is widely known that data science technology, if used irresponsibly, can reinforce inequity, limit accountability, and infringe on the privacy of individuals. Open and effective conversations around these issues of social (in)justice in Artificial Intelligence (AI) and beyond are pivotal in coalition-building and community engagement. And yet, in moments of opposing opinions, high stakes, and strong emotions, people often find themselves immobile and polarized. How, then, do we choose between chaos or community? How do we move forward? In this webinar, co-director of the NYU Center for Responsible AI, Dr. Julia Stoyanovich, and Stern adjunct assistant professor, Jennifer Wynn, will discuss these central questions and their implications. Virtual attendees will acquire the knowledge, tools, and courage required to help them engage in challenging conversations, remain vigilant within their communities, and enact social change in our increasingly digital and tech-oriented spaces.

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Uncovering Hidden Decisions: AI in Hiring

Join NYU’s Center for Responsible AI and the Queens Public Library's Job and Business Academy for a dynamic introduction to the often invisible but increasing role that artificial intelligence (AI) and automated decision systems (ADS) play in the hiring process, from screening and ranking resumes to the use of facial recognition software in interviews.

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Uncovering Hidden Decisions: AI in Hiring

Join NYU’s Center for Responsible AI and the Queens Public Library's Job and Business Academy for a dynamic introduction to the often invisible but increasing role that artificial intelligence (AI) and automated decision systems (ADS) play in the hiring process, from screening and ranking resumes to the use of facial recognition software in interviews.

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Uncovering Hidden Decisions: AI in Hiring

Join NYU’s Center for Responsible AI and the Queens Public Library's Job and Business Academy for a dynamic introduction to the often invisible but increasing role that artificial intelligence (AI) and automated decision systems (ADS) play in the hiring process, from screening and ranking resumes to the use of facial recognition software in interviews.

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Algorithmic Bias, Tech Policy, & Equity at NYC Media Summit

It is no secret that automated decision systems (ADS) are seeing ever broader use. In critical domains like hiring, these tools can help improve efficiency for both job seekers and employers, but they can also lead to arbitrary, unfair, or even discriminatory outcomes. How can we tell whether an ADS actually works? Who is responsible for catching bias and discrimination bugs? Should we regulate the use of these systems? What can we as technologists, business leaders, and members of the public contribute to the responsible design, development, and use of ADS? Join us to learn more and to make your voices heard!

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RIIPL Algorithmic Justice Webinar Series

Falaah Arif Khan and Julia Stoyanovich discuss their comic treatment of AI bias, normativity, and exclusion, as well as possible solutions with Professor Ellen P. Goodman. “Mirror Mirror”. Data, Responsibly Comics, Volume 1 (2020)

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