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Join Us Sept. 17: One Prompt, One Planet – Can We Afford the AI Revolution?

  • Posted by admin
  • Categories News
  • Date September 11, 2026
One Prompt, One Planet: Can We Afford the AI Revolution? Webinar graphic

Thursday, September 17, 2026 | 12:00-1:00 PM ET | Online webinar

The C+M Center on Data Science and Social Equity invites the public to a timely conversation with Ruopeng An about the environmental footprint of artificial intelligence and what more responsible AI use could look like.

Every AI prompt sets physical infrastructure in motion: servers wake, electricity flows, water cools machines, and a data center absorbs the cost. In this fast-moving, story-driven webinar, Professor An will follow a single prompt from the screen into the infrastructure powering it. The session will separate myth from science, examine the tradeoffs behind convenience and innovation, and consider whether AI could become part of the environmental solution.

What the webinar will explore

  • The electricity, water, and data-center resources behind an AI prompt
  • Environmental myths, evidence, and tradeoffs
  • Practical ways to use AI more responsibly
  • How AI and data centers may reshape the planet

Continuing Education (CE) credits are provided for licensed social workers and mental health professionals by the NYU Silver School of Social Work.

Register for the webinar

About the presenter

Ruopeng An is the Constance and Martin Silver Endowed Professor in Data Science and Prevention and Director of the C+M Center on Data Science and Social Equity. He is an elected Fellow of the American Academy of Health Behavior and the American College of Epidemiology and has been listed among the top 2% most-cited scholars by Elsevier/Stanford since 2020.

All are welcome. Our events and initiatives are open to individuals of all backgrounds and identities. Individuals requiring accommodations may indicate them during registration or email silver.cmscenter@nyu.edu at least 72 hours before the event.

Tag:Artificial Intelligence, Data Science, Social Work

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