Processing: Our Future with AI

About Processing: Our Future with AI

Processing: Our Future with AI is an educational initiative and podcast designed to empower young people to navigate and shape the AI landscape. Sponsored by the All Tomorrows Institute, the podcast is created by youth, for youth and hosted by Emma Nicotra, a student at Georgetown University.

Publisher

All Tomorrows Institute

Category

news · technology

Language

en

Explicit

No

First episode

12 May 2026

Latest episode

27 Oct 2026

Latest episodes

8 episodes in the feed.

1. 

   27 Oct 2026

   Funding the Future: AI, Jobs, and Government Revenue with Noah Frank

   In this episode, we talk to Noah Frank, Head of Research at Centaurian AI, where he leads the firm's research, consulting, and thought leadership on AI and the future of work. Noah previously shaped federal AI workforce policy at Americans for Responsible Innovation and worked as a Strategy Consultant at Boston Consulting Group. Noah walks us through his winding path into AI policy, from studying political science, to pivoting toward tech and entrepreneurship, to building the kind of "adjacent" career moves he now advises young people to make. Alongside his research, Noah leads marketing and editorial for The AI Collective, a newsletter reaching over 200,000 subscribers each week. We dig into two major questions. First, the economic impacts of AI on labor markets: what signals are worth watching, which economic models actually hold up, and what second-order effects might we be missing if large-scale disruption arrives. Second, we cover Noah's co-authored paper from the Convergence Fellowship with SPAR on funding government in an increasingly automated economy. Since labor and social insurance taxes make up over half of public revenue across OECD countries, what happens to that revenue base as AI reshapes work? We walk through the range of futures the paper lays out, from "Inequality Dystopia" to "Technofeudalism," the nine revenue strategies Noah's team evaluated, and why he thinks the window for intervention is narrower than most people realize. We close out talking about what this all means for young people specifically, how the next 10 to 20 years could look dramatically different, and what Noah would tell someone who wants to work on these problems, plus what's changed his mind over the past year, and what's giving him hope.

2. 

   13 Oct 2026

   AI Companions and Redteaming for Mental Health Risk with Circuit Breaker Labs

   In this episode, we talk to Arul and Shirali, siblings and co-founders of Circuit Breaker Labs. Arul's background spans defense AI, semiconductors, and venture and Shirali's runs through neuroscience, engineering, and public health. These backgrounds converged while the siblings were discussing tragic cases of AI companions missing warning signs and causing harm to users. In this episode, we start with the landscape. What makes chatbots fundamentally different from the internet young people have always had access to? Arul and Shirali walk through why hyper-personalization and sycophancy can make these tools more isolating and more powerful than any social media algorithm, and why the anthropomorphizing design of companion apps and avatars adds a layer psychologists still don't fully understand. From there, we go inside the safety testing process itself. Arul and Shirali explain how they've adapted red teaming from its cybersecurity origins into something built for a probabilistic system, where the real questions are whether a model misses nuance, fails to surface a crisis resource, or breaks down under typos and phrasing variation. We cover the limits of manual red teaming at scale, the emerging practice of using LLMs to evaluate other LLMs, and the emotional weight of the human review work underneath it all. We close on access and equity: the genuine promise of AI to close the mental health access gap in rural areas and places with long wait times, the risks for users with marginalized identities, and why companion apps and avatars introduce risks a standard chatbot doesn't. We wrap with what Arul and Shirali want young people using AI for emotional support to know, and what's giving them hope.

3. 

   28 Aug 2026

   Democratizing Education and Responsible AI Adoption with Sophia Romee

   In this episode, we talk to Sophia Romee, who spent six years at College Board and most recently founded and led its GenAI Studio, a cross-functional team of 25 working across product, strategy, design, data science, and engineering. 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.

4. 

   4 Aug 2026

   Gender Equity, Deepfakes, and Algorithmic Bias with Anika Dugal

   What does it mean when 99% of deepfake victims are women and girls? Why do "helper" chatbots so often default to feminized voices and identities? And what happens when the people most affected by AI aren't the ones building it? 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/ (https://www.centergeai.org/) Learn more: https://www.anikadugal.com/about (https://www.anikadugal.com/about) Resources & Further Reading Center for Gender Equitable AI: https://www.centergeai.org/ (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/ (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 (https://www.congress.gov/bill/119th-congress/senate-bill/146) Algorithmic Justice League: https://www.ajl.org/ (https://www.ajl.org/) Coded Bias (documentary): https://www.codedbias.com/ (https://www.codedbias.com/)

5. 

   15 Jul 2026

   International Coordination and the AI Off-Switch with Aaron Scher

   What does it mean for AI systems to have "goals"? How could those goals differ from human goals? Why are some researchers calling for an "off-switch," and what would it look like? What are different future scenarios MIRI has mapped out and how could these play out on the international stage? 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.

6. 

   30 Jun 2026

   Mass Surveillance and Child Safety with Allie Maloney

   From personal medical advice and foreign-language translations to help filling out financial documents and more, we've grown to trust chatbots with an increasing amount of sensitive information. Yet, as things stand today, the legal protections surrounding much of the information we share with these systems remain unclear and, in some cases, significantly weaker than those governing more traditional forms of communication. 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.

7. 

   23 Jun 2026

   The Data Workers Behind AI with Camilla Salim Wagner

   What if the chatbot you've been confiding in is actually a 50-year-old man halfway around the world? What happens after you report inappropriate content online, and who has to review it? If AI is supposed to automate work, why does it still depend on so many human workers? 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.

8. 

   12 May 2026

   Trailer: Welcome to Processing!

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