Underlying structural inequities and pervasive biases often surface in the data sets that train AI systems. This can determine how data-driven and automated decisions unfairly funnel access to opportunity — and outcomes — in medicine, employment, education, and the law.
To examine this challenge and contribute towards creative solutions with participants, the Center for Responsible AI will discuss the current state of the field, legislation in the pipeline, and emerging public education efforts. With an emphasis on AI in hiring and employment, the session will identify what “responsible AI” can look like, and include:
- the risks of introducing, and then normalizing, new barriers
- how to move beyond harm mitigation to achieve “human-aware and trustworthy” systems
- new research, standards, and tools (from technical advances and shifts in business practices to better audit mechanisms)
Robust participation invited! Help create a future in which responsible AI is the only AI.
Moderated by: Steven Kuyan Director, Center for Responsible AI @ NYU Director of Entrepreneurship, NYU Tandon and Managing Director, NYU Tandon Future Labs
Speakers: Julia Stoyanovich Director, Center for Responsible AI @ NYUAssistant Professor, NYU Tandon and the Center for Data Science at NYU Stefaan Verhulst Co-Founder and Chief Research and Development Officer of the Governance Laboratory @NYU Eric Corbett Affiliate, Center for Responsible AI Smart Cities Postdoctoral Associate, NYU CUSP Help create a future in which responsible AI is the only AI.
