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Event overview
National Health Policy Conference and Health Datapalooza is a gathering for health data and policy innovation. It provides a platform for public sector organizations to discuss how they can generate, hold, use, govern, and transform healthcare with data.
The conferences harness and strengthen the synergies that exist between the data and policy worlds and showcase innovative solutions to address the challenges, opportunities, and threats facing U.S. health care.
Connect with Infosys Public Services
Infosys Public Services will be presenting a session on Practicing Responsible AI. Experts from academia, government, and industry will discuss the opportunities and risks associated with enabling responsible AI. They will outline a governance framework for organizations to practice AI responsibly and build AI models that are transparent and engender trust.
Speakers
Dr. Suman De, Head of Government Healthcare Analytics, Infosys Public Services
Ritu Agarwal, PhD, University of Maryland
Gloria Washington, PhD, Howard University
Diya Wynn, Amazon Web Services
Session details
Topic
Practicing Responsible AI: Risks, Challenges & Opportunities
Date
April 4, 2022
Time
2:45 PM – 4 PM
Location
Crystal Gateway Marriott - Salon C, Arlington, VA
Speakers
Ritu Agarwal, PhD, University of Maryland
Gloria Washington, PhD, Howard University
Diya Wynn, Amazon Web Services
Moderator
Dr. Suman De, Head of Government Healthcare Analytics, Infosys Public Services
Session Description
Democratization of technology and the pandemic has fueled AI/ML adoption across the public sector. Several public health agencies have leveraged AI/ML technologies to support their initiatives including the identification of vulnerable populations, delivery of personalized interventions, and elimination of fraudulent transactions.
While these AI-enabled initiatives generated new insights and enabled the agencies to improve outcomes, they also raised serious concerns regarding the bias in AI/ML adoption and renewed the focus on trust and transparency.
From changing regulations to increasing constituent trust and cost of building AI/ML models, data scientists, agency leaders and policy makers need to understand the challenges, opportunities and risks associated with AI. They need to adopt the right strategies and tactics to ensure AI systems are built responsibly, are explainable, use resources in an optimal manner, and engender trust.
Join this session for perspectives from experts on the definition and implementation of responsible AI and a governance framework built on people, process and technology pillars, to help organizations develop purposeful AI models
