PANEL : EMPOWERING WOMEN: STORIES OF GROWTH & TRANSFORMATION
summary
Panel documents actionable steps: recommend auditing training data and following a UNESCO manifesto for reduced AI gender bias; require full applicant lists and rewrite job descriptions to boost female applicants; run studio visits and classroom workshops—Technovation Montréal runs after‑school projects for girls 8–18 that combine coding and entrepreneurship; animate nuanced characters (example: Nimona) rather than stereotypes; use inclusive recruitment and one‑person‑one‑voice research methods so diversity actually changes hiring and product outcomes.
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chapters (8)
- 0:00Introduction and panelist introductions
- 4:41AI bias and responsible systems
- 7:37Diversity and inclusion in tech teams
- 15:03Female character representation in animation
- 22:12Gender bias in user research data
- 24:42Closing the gender gap in programming education
- 37:24Career advice and personal growth reflections
- 49:38Q&A and closing remarks
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