Mothering the Machine: Feminist Theory Meets Silicon Valley's Newest Metaphor

Guest: Dr. Michelle Morkert — gender scholar, leadership coach, founder of the Women's Leadership Collective.

In this repisode (get it? re-episode?), Kimberly and Jessica sit down with Dr. Michelle Morkert to unpack the growing call from AI leaders for "maternal AI," which is the idea that treating AI systems like children we're raising will make them safer, kinder, and less likely to turn on us. Michelle walks through the difference between a gender analysis (counting heads) and a feminist analysis (asking who holds power and why), then the conversation turns to why "maternal" is a loaded, historically fraught word to hand to an industry that has never asked mothers what they actually need or wondered how mothers (or even women in general) might benefit.

Topics covered:

• Gender analysis vs. feminist/intersectional analysis, illustrated through the demographics of the U.S. Senate
• The "maternal AI" proposal from figures like Geoffrey Hinton (computer scientist and cognitive psychologist often referred to as the "Godfather of AI" and Mo Gawdat, former chief business officer at Google X. We talk about why they never get specific about what "maternal" would actually mean in practice. 
• Sarah Ruddick's concept of "maternal thinking" as a non-gendered ethical stance, and how it differs from what's being proposed now
• Why Sam Altman's comment that saying "please" and "thank you" to ChatGPT costs OpenAI "tens of millions of dollars," which he called "well spent", is a small but telling data point in this conversation 
• Deepfake harm and non-consensual imagery as the more urgent, material issue getting sidelined by the "maternal AI" metaphor
• Radicalization pipelines and the "tradwife" aesthetic as a case study in how "maternal" framing gets co-opted politically
• Donna Haraway's "God trick" and why tech's claim to neutrality keeps women out of the room
• Karen Hao's Empire of AI and the Indigenous-language-model counterexample as a picture of what reciprocal, non-extractive AI development could actually look like

Also referenced in this episode:

• Alison Gopnik, The Scientist in the Crib
• Laura Bates on BBC's Radical with Amal Rajan (dehumanization and algorithmic feeds)
• Allie K Miller's interview on the Mel Robbins Podcast