In this episode of Synergia, we are joined by Hannah Fitsch, a feminist sociologist of science and technology whose work sits at the intersection of neuroscience, artificial intelligence, museums, visual knowledge, and feminist theory. Awarded the Emma Goldman Snowball Award for her work, Hannah brings a deeply critical and creative lens to how science and technology shape and often limit our ways of knowing the world.
We begin by unpacking what feminist sociology of science and technology (STS) really means. Hannah explains why she was drawn to neuroscience, technology, and museums as sites where knowledge is produced, visualized, and normalized and how these spaces quietly encode social assumptions about bodies, minds, and value.
The conversation then turns to artificial intelligence as a “context-free zone.” From a feminist STS perspective, Hannah argues that AI systems often overlook, erase, or disregard context, bodies, and lived experiences. By categorizing and optimizing people into abstract data points, science and technology risk alienating us from nature, from one another, and from our own material realities. This algorithmic divide-and-conquer logic simplifies human life instead of engaging with its irreducible complexity.
A central theme of the episode is the disappearance of the body in AI and neuroscience. As computational neuroscience increasingly describes the brain through algorithms and mathematical models, Hannah asks a crucial question: What does the information-processing theory of mind exclude, and why? When thinking is formalized into equations, perception and experience are reduced, distorted by the very tools meant to explain them.
Drawing on the work of Max Horkheimer, Hannah critiques AI as an extension of instrumental reason—a logic focused on optimization, efficiency, and goal achievement, detached from ethical and social consequences. She extends this idea to what she calls “unconditional reason,” where data and algorithmic predictions are treated as universally valid, despite being rooted in partial, biased, and historically situated realities.
We also discuss her work The Beauty of Thinking, which explores the mathematization of perception in computational neuroscience. Hannah reminds us that thinking is far too complex and far too beautiful to be reduced to formulas. We do not think in algorithms, we do not have standardized bodies, and we are not averages of numbers.
This episode is an invitation to reimagine science and technology as situated, embodied, and relational practices and to ask what a more humane, feminist future of AI and neuroscience could look like.
Learn more about Hannah’s work:
https://www.neurogenderings.org/
