The Technically Human Podcast

On this episode I’m joined by Jess Holbrook, Head of UX Research for Microsoft AI.

We talk about what UX research can—and cannot—tell us about what people need; why user-centered design may be too individualistic for technologies whose effects extend across families, workplaces, communities, and institutions; and what it means to put researchers in the room while AI systems are still being built rather than after fundamental design decisions have already been made.

Over the past 12 years, Jess has held senior research and design leadership roles across Microsoft, Meta, Google, and Amazon. He previously led Generative AI, Responsible AI, and data transparency UX research at Meta, and at Google he founded and led the People + AI Research group, or PAIR, before serving as Head of UX for the Responsible AI and Human-Centered Technology group. His work has focused on bringing human-centered and inclusive approaches into the development of AI systems and translating emerging machine-learning capabilities into products designed around people’s needs.

Jess also writes regularly about AI, frontier UX research, research slop and the future of human-centered technology on his Substack, Gen Purpose.

This episode was produced by Jack Lucas Chang.

Today I’m speaking with Dana Mazia, General Manager of the Bright Initiative by Bright Data, which provides nonprofits, academic institutions, and public bodies with pro bono access to public web data and expertise.

Dana is a lawyer, social entrepreneur, and World Economic Forum Global Shaper with more than 14 years of experience across technology, data, and social impact.

Bright Data is a web-data platform that provides the infrastructure organizations use to collect, process, and analyze publicly available information from across the internet. The Bright Initiative is its public-interest program, making that technology and expertise available to organizations working in academic research, public policy, transparency, and social impact.

Conversations about artificial intelligence typically focus on models: what they can do, what they produce, and whether their outputs are accurate or safe. But behind every model is a less visible infrastructure—the systems through which information is collected, organized, and made usable.

That raises important questions about who can access public web data, what “public” really means, and whether an open internet benefits everyone equally or primarily its most powerful actors. These questions become even more urgent as AI systems move from learning from the web to actively operating within it.

Dana and I discuss the politics of data infrastructure, the ethics of web scraping, the risk of information monopolies, and the legal and ethical questions that arise when information from the public web is collected and operationalized at scale. Ultimately, we ask who should have access to this infrastructure—and who will have the power to shape the AI ecosystem built upon it.

Today I am interviewing Bruce Friedrich, the author of the newly published book "Meat: How the Next Agricultural Revolution Will Transform Humanity's Favorite Food―and Our Future." Bruce Friedrich is the president and founder of the Good Food Institute, one of the leading think tanks working to make the global food system better for the planet, people, and animals. As an international network of organizations, they advance alternative proteins to help meet climate, global health, food security, and biodiversity goals.

Bruce Friedrich serves as GFI’s chief thought leader and relationship-builder, working in close partnership with GFI’s global teams and food system stakeholders around the world. Before founding the Good Food Instiute, he served as Director of Policy for four years at Farm Sanctuary. Prior to that, he worked at PETA for 15 years as Head of Public Campaigns, leading many of the organization's highest-profile and most memorable campaigns.

Bruce has penned op-eds for the Wall Street Journal, Foreign Policy, Nature Food, Wired, and many other publications. He has represented GFI on the Ezra Klein Show, Making Sense (Sam Harris), TED Radio Hour, New Yorker Radio Hour, PBS News Hour, and a variety of other podcasts and TV programs. Bruce’s TED talk has been viewed almost 2.5 million times and translated into 30 languages. Nature featured Bruce’s 2026 book Meat as one of its five “best science picks,” and Publishers Weekly selected Meat as one of the 10 best new releases in science, writing: “This packed account makes food science feel like an urgent and essential undertaking.”

The book has also received praise from Nobel Laureate in economics Michael Kremer, primatologist Jane Goodall, and science fiction master Kim Stanley Robinson, among many others.

Bruce graduated magna cum laude from Georgetown Law and also holds degrees from Johns Hopkins University, the London School of Economics, and Grinnell College.

This episode was produced by Jack Lucas Chang.

My guest for this episode is Professor Aleem Hossain, a writer and director working across science fiction, fantasy, experimental cinema, and television. His feature film After We Leave won Best Feature Film at the Sci-Fi-London film festival and Best Director at the Berlin Sci-Fi festival, and his AI-generated short film, Do Bangladroids Dream of Electric Tagore?, premiered at Fantastic Fest and won Best Narrative Film at the AI Art & Film Awards.

His work is shaped by his own multicultural upbringing—the son of a Muslim immigrant from Bangladesh and a mother from a Roman Catholic family in Connecticut—as well as by his interest in expanding both the kinds of stories we tell and the people who are able to tell them.

He is also an associate professor of digital storytelling at Occidental College, where he teaches filmmaking and screenwriting.

In this conversation, we talk about what generative AI makes possible for independent filmmakers, what it fails to understand about culture and identity, and how the arrival of these tools may change not only how films are made, but who gets to imagine the future.

This episode was produced by Jack Lucas Chang.

Globally, 8 billion people will experience trauma in their lifetime. Ninety-three percent of those in crisis will not receive adequate care. The barriers are familiar: cost, stigma, language, geography, workforce shortages. What is less familiar is someone actually building technology to address all of them at once, starting from survivor experience rather than market opportunity.

Megs Shah is the Founder and CEO of The Parasol Cooperative, a nonprofit that builds trauma-informed AI tools for survivors of domestic violence, human trafficking, and technology-facilitated abuse. Her flagship product, Ruth, is the world's first trauma-informed AI chat — designed by and for survivors and the advocates who support them. In just over a year, Ruth has facilitated more than 679,000 private crisis support interactions across 147 countries in 85 languages, earning a 92% helpfulness rating. It requires no login, no account, and no personal information. Privacy is not a feature; it is the architecture.

In this conversation, Megs and I talk about what it means to build technology under a fundamentally different moral and financial logic — one that centers dignity, safety, and access rather than engagement and data capture. We discuss how lived experience from survivors shapes design decisions that conventional technologists miss, why trauma-informed AI is categorically different from general-purpose AI deployed in sensitive contexts, and what it looks like to measure success when the meaningful metrics are trust, stabilization, and safety rather than clicks. We also talk about the ways technology is already being weaponized against the people Ruth is built to protect — and what it would take to design systems that take patterned harm seriously before it escalates.

This episode was produced by Jack Lucas Chang.