Lessons from Edwin Land

Edwin Land, Polaroid co-founder and inventor of instant photography, joined applied physics with product design while investigating color perception, treating business as an extension of science and making failure part of the discipline required to build impossible things.

Lessons from Eleanor Duckworth

Eleanor Duckworth, an educational psychologist trained under Jean Piaget, built classroom methods around “the having of wonderful ideas,” trusting students’ struggles with materials and confusion while demanding disciplined listening, critical exploration, and curriculum shaped by learners.

Lessons from Elinor Ostrom

Elinor Ostrom, a political scientist and the first woman to win the Nobel Prize in Economics, showed that communities can manage shared resources without tragedy, state control, or privatization by drawing on local knowledge, cooperation, and institutional design.

Lessons from Emily Bender

Emily M. Bender, a University of Washington computational linguistics professor, examines large language models’ limits and ethical risks, using “stochastic parrots” and the Bender Rule to distinguish statistical text generation and linguistic structure from understanding or human thought.

Lessons from Grace Hopper

Grace Hopper, a mathematician, computer scientist, and U.S. Navy rear admiral, invented the first compiler and championed English-like programming languages, laying groundwork for COBOL while modeling technical leadership that challenged institutional stagnation and centered human needs.

Lessons from John Carmack

John Carmack built the graphics engines behind Doom and Quake, solving problems central to 3D gaming and online multiplayer through a brute-force pragmatism that favors raw performance over elegant abstractions, revealing a broader approach to code and work.

Lessons from Julie Bornstein

Julie Bornstein, a former digital strategy leader at Sephora, Nordstrom, and Stitch Fix, founded The Yes and Daydream to replace broken keyword search with AI systems that match human taste, joining retail insight, data science, and entrepreneurship.

Lessons from Kate Crawford

Kate Crawford studies artificial intelligence’s social and political realities, arguing in Atlas of AI that machine learning depends on extracted resources, labor, and data, and that systems of classification and measurement operate as registries of power reshaping society.

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