In this episode, we explore the future of artificial intelligence through the lens of policy, ethics, and governance; examining how this rapidly evolving technology is reshaping society and the responsibilities that come with it.

Joining the conversation are Renée Cummings, Professor of Practice in Data Science and a leading voice in AI ethics, and Mona Sloane, Assistant Professor of Data Science and Media Studies, whose work focuses on the intersection of technology and society.

Together, they share insights on how we can guide the development of AI in ways that are responsible, equitable, and grounded in the public interest.

Stay connected with UVA Data Points and UVA School of Data Science

Catch all our latest episodes of UVA Data Points here: https://uvadatapoints.castos.com

Learn more about the UVA School of Data Science: https://datascience.virginia.edu

• (00:00:50) - When Do You Use AI in Your Work?
• (00:05:02) - AI and the Epistemic Crisis
• (00:05:46) - Is ChatGPT the End All Be All of AI?
• (00:09:06) - AI's Social Infrastructure
• (00:17:37) - What Can I Do With a Generative AI System?
• (00:27:43) - The Need for Ethical AI Use
• (00:28:44) - Policy Conversations About AI
• (00:33:00) - Hype Around Technological Innovation vs. Reality
• (00:34:00) - AI's Lifeblood Is Data
• (00:34:40) - Human Risk vs. Machine Risk
• (00:38:08) - Looking for a Job in an AI-Mediated World
• (00:40:39) - How AI Is Affecting Recruitment
• (00:45:47) - Career Impacts of AI

Interested in what a career in data science can look like?

Here, we’re joined by two members of the School of Data Science Advisory Board: Heidi Lanford, co-founder of NavAlytix AI and former Chief Data Officer at Fitch Group, and Kane Geyer, Principal at PwC and most recently the leader of the U.S. and Global Chief Data Office. In conversation with Reggie Leonard from UVA’s School of Data Science, they share perspectives shaped by decades of experience leading data and AI initiatives across global organizations.

Our Guests

Heidi Lanford is an award-winning global executive with a track record of transformative leadership and operational expertise. She is the co-founder of NavAlytix AI, a technology startup that is focused on the adoption, impact and outcomes of AI. She was most recently the pioneering Chief Data Officer at Fitch Group (parent of Fitch Ratings), a Hearst Company. She joined Fitch from Red Hat (IBM), where she led their enterprise data, analytics and AI strategy. She has earlier executive leadership experience at Avaya, WPP and PwC, across the Americas, Asia, and Europe, in both B2B and B2C companies.

Heidi is a frequent keynote speaker on AI strategy and transformation. She holds a BA in mathematics and statistics from the University of Virginia. She is a strategic advisor to Domino Data Labs and several other early-stage AI companies. She was previously an advisor to HearstLab, which provides investment and services to early-stage, women-led technology startups.

Kane Geyer is a Principal at PwC where he has spent his career working with clients and internal stakeholders to transform businesses by integrating leading-edge decision-making capabilities and building high impact data and analytics teams. In his current role as leader of the U.S. and Global Chief Data Office, Kane oversees the evolution of the enterprise data and knowledge strategy to design and develop analytical capabilities for commercial and internal purposes. Serving in this capacity has been a phenomenal learning experience in leadership, collaboration, and navigating the complex risk and regulatory facets of delivering analytics capabilities at scale in a global marketplace.

Prior to leading the Global and U.S. CDO, Kane served clients in PwC’s Consumer Markets vertical where he led multi-disciplinary teams across data, analytics, and technology competencies to deliver enterprise scale decision capabilities. Over a 20-year career, he built a fabric of experiences that invited him to see the world through business, technology, and operational eyes. Serving early in his career as analyst, engineer, and architect and later as strategist and operational leader yielded a sound professional foundation shaped by diverse perspectives and business challenges.

The lessons learned over the course of a rewarding career have been many. Some were learned early and matured into core professional values and guiding principles. Others were harvested by taking calculated risks and learning through failure. The privilege of joining the School of Data Science Advisory Board presents a great opportunity to share some of those lessons and knowledge to help others navigate the path forward.

Kane graduated from the University of Virginia in 1998 with a B.A. in Environmental Sciences. Following the ethos of living a lifetime of learning, he pursued graduate studies at the Leonard N. Stern School of Business, New York University where he earned an M.B.A. in 2010. Kane enjoys balancing his professional life and aspirations by maximizing his time outdoors and traveling. He currently resides in Connecticut with his wife and two children.

Stay connected with UVA Data Points and UVA School of Data Science

Catch all our latest episodes of UVA Data Points here:

• (00:00:43) - Meet the Board of the University of Virginia School of Data Science
• (00:01:58) - What's Your Career Story on Your Resume
• (00:03:13) - How to Get Out of Your Start Job
• (00:05:50) - Getting Out of Data Science Boot Camp
• (00:10:44) - Choosing the Right Path for Your Career
• (00:14:38) - The Emergence of Data Science
• (00:21:49) - Heidi on Quick Wins and Low-Hanging Fruit
• (00:25:23) - How to Start a Business with Data and AI.
• (00:29:35) - How Did You Build a Startup With No Full Time Employees?
• (00:30:56) - Kane on Data Science and the Future
• (00:33:05) - Bluefin Tuna
• (00:33:24) - Quantum Intelligence: The Power of Data
• (00:39:44) - The Future of Decision-Making Is AI
• (00:42:16) - Citizen Data Scientists and Vibe Coding
• (00:46:30) - What Advice Would You Have For Your Younger Self?

In this episode of UVA Data Points, we explore the rapidly evolving world of digital brain twins; personalized, data-driven models of the brain that could revolutionize medicine and neuroscience. Joining the conversation are two leading experts: Dr. Randy McIntosh, a pioneer in brain network analysis, and Dr. Emiliano Ricciardi, an expert in cognitive neuroscience and neuroimaging. Together, with Jack Van Horn, Professor with the School of Data Science and Department of Psychology, they'll dive into how these digital replicas of the brain could change the way we understand cognition, disease, and treatment.

• (00:01:30) - Cognitive Science Podcast
• (00:02:16) - What Exactly constitutes a Digital Brain Twin?
• (00:13:12) - What are the computational requirements for a synthetic brain?
• (00:16:53) - The computational requirements of the Digital Twin
• (00:28:05) - Do Digital Twins Play a Role in Estimating Brain Age?
• (00:34:09) - Ethical Implications of Digital Twins
• (00:38:01) - Ethical Issues of the Digital Twin
• (00:44:04) - Could a Digital Twin Brain Ever Become Conscious?
• (00:51:30) - Digital Brain Twins: The Future of Science
• (00:56:30) - Digital Brain Twins