Episode Summary

In this episode, Kimberly and Jessica dig into the rising crisis of AI-generated deepfake non-consensual intimate imagery (NCII), and why it's not really a technology story. It's a power story. From a class action lawsuit against Elon Musk's xAI/Grok to a history of technology being used to harm women dating back to the printing press, this conversation situates deepfake porn within a long pattern of systems failing to protect women and girls at scale.

They discuss a New York Times op-ed about a lawsuit involving three Tennessee teenagers whose yearbook photos were used to generate sexually explicit images and what the outcome of that case could mean for tech accountability. They also cover what parents can do, why law enforcement is struggling to keep up, and where to turn if you or someone you know has been victimized.

In this episode:

• What deepfakes are, and why "it's not real" doesn't reduce the harm
• The xAI/Grok class action lawsuit and the co-creator legal argument
• A quick history lesson: from the printing press to Facebook's origins as "FaceMash"
• Why the barrier to entry is the real game-changer
• What Elon Musk says about it — and why critics aren't buying it
• Open-source models with no guardrails
• The Take It Down Act and state-level deepfake legislation
• Resources for victims and what watermarking can and can't do
• Why talking to your kids matters (and why they probably know more than you)

Resources and Links

Primary episode sources:

• New York Times op-ed: Deepfake Nudes Are Harming Teens
• AP News: xAI/Grok lawsuit coverage
• Lieff Cabraser on the NYT op-ed and the lawsuit

Victim resources:

• StopNCII.org
• Sensity AI

Legislation and policy:

• The Take It Down Act (Latham & Watkins summary)
• State deepfake legislation tracker — Public Citizen

Context and background:

• Understood: Deepfake Porn Empire (Apple Podcasts)
• Understood: Deepfake Porn Empire (Spotify)
• University College Cork: Deepfake Real Harms — Six Myths
• AlgorithmWatch: Spain schoolboys and AI-generated fake nudes
• Laura Bates, The New Age of Sexism
• Brotopia by Emily Chang
• Gilded Rage by Jacob Silverman

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Kimberly Becker joins George and George on the Bare Knuckles and Brass Tacks podcast to talk about what our research is revealing about the language AI produces and what it means for the rest of us.

Topics Covered

• How Kimberly's research compared AI-generated abstracts to human-written ones in nursing journals and what the key linguistic differences were
• Why AI text tends to be informationally dense, formulaic, and stripped of hedging language
• The Porter and Jick letter and how a five-sentence note helped fuel the opioid epidemic through citation chaining
• What happens when AI scales the same kind of telephone game with scientific evidence
• How algorithmic silos and certainty amplification may be eroding our tolerance for nuance
• The difference between accuracy and complexity in writing, and why polished text is not the same as deep thinking
• Why smaller, well-vetted language models may produce better outcomes than massive ones trained on internet slop
• Neil Postman's idea that writing "freezes speech" and what that means in an era when fewer people are doing their own writing

Referenced in This Episode

• Bare Knuckles and Brass Tacks podcast
• The Porter and Jick letter (1980) on opioid addiction
• Neil Postman, Amusing Ourselves to Death
• James Marriott's essay on the post-literate society
• Derek Thompson, "The Decline of Thinking" (The Atlantic)
• OpenAI's Prism research tool

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Jessica and Kimberly just had a paper accepted for publication in Frontiers in Education. So today, they're sharing what they've learned.

The big idea is that AI is not a neutral tool. It's a cultural intermediary. Just like a human translator doesn't swap words one for one, AI mediates the way we understand the world. It shapes what we write, what we trust, and what we treat as true. And most of us have no idea that's happening.

They walk through the research behind their framework, talk about what AI actually does well (fluency and accuracy), and where it falls short (depth, nuance, relational intelligence). And they share real examples from their work that show what it looks like when we hand over too much of our thinking to a machine.

Topics Covered

• What it means to treat AI as a cultural intermediary and why that framing changes everything
• The difference between accuracy, fluency, and depth in writing, and why AI can only get you so far
• How the same consulting firm that charged thousands of dollars produced a report that ChatGPT could replicate in minutes
• What a capability map for AI literacy looks like, from emerging to proficient
• Why relational intelligence is the human edge that AI cannot replicate
• How AI is widening the distance between people and what we lose when we stop talking to each other
• The social media influencer as a double intermediary, and what that means for kids whose brains aren't fully developed yet
• Why publishing in an AI-focused field is its own kind of pit

Referenced in This Episode

• The "Attention Is All You Need" paper and the transformer architecture
• Timnit Gebru and the Stochastic Parrots paper
• Taylor & Francis and the $75 million content licensing deal with AI companies

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Contact us: https://www.womentalkinboutai.com/