Sophia walks us through her path into education, from a formative college course on social entrepreneurship to growing up in Little Havana, Miami, watching her mother teach in under-resourced schools. That experience shaped a throughline that runs through her entire career: democratizing technology and opportunity for the learners and workers that legacy systems too often leave behind.

We go beyond the SAT and AP exams to talk about what else College Board is building, including BigFuture.org and AP Career Kickstart, a new credentialing pathway developed with employers like Cisco and IBM. Sophia explains how she approaches responsible AI adoption inside a 2,000-person organization, why College Board deliberately moved away from usage metrics like prompts sent or tokens used in favor of outcome-based measures, and what "human in the loop" means in practice rather than as a buzzword.

We close out talking through Sophia's own advice for students navigating AI, including a practice from the GenAI Studio called "prompt mobbing," where teams learn together by testing and refining prompts as a group, and what's giving her hope about where all of this is headed.

In this episode, we talk with Anika Dugal, founder and Executive Director of the Center for Gender Equitable AI (CGEAI), an organization of over 200 young people working to address gendered harms in AI. Anika shares the story behind CGEAI, from its founding as Girls for Algorithmic Justice during her junior year of high school, to its rebrand and current "star shape" model of organizing around advocacy, research, education, and community.

We dig into the organization's #StopExplicitDeepfakes campaign and its role in supporting the bipartisan TAKE IT DOWN Act, which requires platforms to remove nonconsensual intimate imagery, including AI-generated deepfakes. We also explore algorithmic bias more broadly: how gendered defaults show up in image generation and machine translation, why representation is what Anika calls a "root cause solution," and how the feminization of chatbots and digital assistants reinforces and reflects broader gender stereotypes.

We close with Anika's own path from women's rights advocacy into AI policy, her experience running an advocacy organization while studying computer science and public policy at Duke, and her advice for young people looking to work at this intersection.

Guest
Anika Dugal
Founder & Executive Director, Center for Gender Equitable AI
Website: https://www.centergeai.org/
Learn more: https://www.anikadugal.com/about

Resources & Further Reading
Center for Gender Equitable AI: https://www.centergeai.org/

"The Online Degradation of Women and Girls That We Meet With a Shrug," Nicholas Kristof, The New York Times (republished via WRAL): https://www.wral.com/story/nicholas-kristof-online-degradation-of-women-and-girls-that-we-meet-with-a-shrug/21344898/

TAKE IT DOWN Act, S.146, 119th Congress: https://www.congress.gov/bill/119th-congress/senate-bill/146

Algorithmic Justice League: https://www.ajl.org/

Coded Bias (documentary): https://www.codedbias.com/

In this episode, we interview Aaron Scher from the Machine Intelligence Research Institute (MIRI). As an organization, MIRI has played an influential role in shaping the AI safety movement.

Aaron speaks in his personal capacity as a technical governance researcher. We go through a brief history of AI, the risks these systems could pose, the current policy landscape, and what can be done about it. We talk through scenarios MIRI has written about, as well as the work being done to try to mitigate them, and discuss the feasibility of international coordination on AI. We close out with Aaron's own path from a psychology degree into AI safety.

I am very excited to be joined today by Allie Maloney, a policy analyst at Americans for Responsible Innovation, a bipartisan nonprofit advocacy organization based in Washington, D.C., to discuss these questions and more.

Beyond questions of who can access this information lies a new concern, one that is largely unprecedented. For years, governments and third parties have had the ability to collect enormous amounts of data about our behavior, but analyzing it at scale was often difficult, expensive, and time-consuming. Now, it isn't.

AI has automated the ability to analyze and act on personal data, from video surveillance and digital tracking cookies to our conversations with chatbots. In this episode, we dive into the policy: What laws currently exist, and what additional protections do we need?

Beyond privacy, we also discuss the implications of this technology for children. How is generative AI shaping kids' lives, from digital tutors and homework helpers to video game characters and companion chatbots? How might the market incentives driving these products cause them to evolve in harmful ways, and what are legislators doing to prevent negative outcomes?

This was a wide-ranging conversation from privacy and surveillance to child safety and how new technology is becoming increasingly woven into our daily lives.

In this episode, we interview Camilla Salim Wagner, political scientist and researcher at the Data Workers' Inquiry, supported by the Distributed AI Research Institute. 

We also discuss the realities of data work, the ethical questions surrounding AI labor, and the growing movement advocating for greater recognition and protections for the people behind the technology. We explore the hidden workforce behind today's AI systems. We learn what data workers do, who they are, and what many of them are fighting for today.

It's easy to focus on the downstream impacts of AI (its effects on the economy, the environment, or humanity's long-term future). While those questions are important, this episode focuses on the people experiencing the impacts of AI right now.

How is the race to build more powerful AI systems affecting real people? What responsibilities do technology companies have toward the workers whose labor makes AI possible? As governments and companies race to develop increasingly powerful AI systems, questions about labor rights, transparency, accountability, and humane working conditions are becoming increasingly urgent.