Panel: AI Feminism
summary
Panel argues that AI adoption needs practical education across ages: teach kids robotics to build creative and collaborative thinking, run mentoring like Pulsar to reskill degree-holders, and add AI modules across curricula. Concrete problems: many useful datasets are paywalled, sampling frames are poorly defined, and bias surfaces in practice — eg. Amazon hiring tool favored men and CCTV rollouts in Belgrade spark transparency concerns. Cites metrics — AI Watch 2021: gender up, business index down; Romania strong in university AI places — and calls for clearer scope, regulation, and open data.
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chapters (10)
- 0:00AI feminism panel intro
- 1:11Defining AI feminism
- 5:10AI's daily impact
- 9:48AI adoption challenges
- 14:24Bias in AI sampling
- 21:30AI access discrepancies
- 27:16Ethical AI transparency
- 35:17AI regulation and trust
- 37:27Diversity in AI education
- 40:23AI inclusivity empowerment
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