Evelyn Smith is a Marketing Ph.D. candidate at the University of Washington studying AI fairness, responsible technology, and the intersection of data, behavior, and ethics. In this episode, Jason Cavness and Evy explore how algorithms shape marketing decisions, why fairness and transparency matter in AI systems, and how game theory can explain everything from business strategy to human motivation.

This is a deep dive into the future of responsible AI — where technology, academia, and humanity meet.

Episode Highlights

• AI fairness and its implications for marketing and society • Game theory, decision-making, and behavioral insights • Data privacy, cybersecurity, and ethical technology design • The peer review process and challenges in academia • The concentration of power in tech companies • The balance between scientific integrity and funding • Coding as a "blue-collar" path to upward mobility • Global academic talent and the brain drain challenge

Guest Bio (Condensed)

Evelyn Smith is a Marketing Professor and Ph.D. candidate in Game Theory and Mathematical Modeling at the University of Washington. Her research focuses on the marketing implications of artificial intelligence, AI fairness, responsible AI, Web3/Blockchain, and pricing strategy. With a passion for ethical innovation and data-driven insight, Evy's work bridges the gap between academic rigor and real-world application in today's AI-driven economy.

Guest Links

LinkedIn – https://www.linkedin.com/in/evelynosmith/

Guest Quote / Advice

"We need to design AI systems that understand context — not just data. Fairness in AI isn't about perfection; it's about accountability and human impact."

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