Women & AI: driving positive feedbackloops for change

Report, strategy, training

Women's relationship to technology is usually defined in terms of women's representation—or lack thereof—in the technology sector. There is a troubling and persistent absence of women employed in the AI and data science fields. However, the intersection of AI technologies and women requires a wider analysis. From Apple's discriminatory algorithm, which gave men a higher credit limit than women with better credit scores to facial recognition systems that don't recognize Black women's faces, algorithmic harms that are experienced by women are unlikely to be addressed only by closing digital skills divides.
I worked with a major French fashion, beauty and luxury house’s head of global innovation for 6 months to help them understand the geopoltics of AI, AI applications in fashion, beauty and luxury, and ethics and regulations of AI.

I mapped and scoped the intersection of women and AI and delivered five hours of executive training sessions. Using systems thinking, I drafted a report that is tailored for the specific industry and aligned with the brand identity. I provided company-wide and industry-wide pathways for action and communications campaign ideas.

“While AI thinking defines and dictates who is a woman, what is womanhood, and which jobs, credits, rights women deserve; it is important to remind women that they have always been there and enable them to appropriate AI technologies that are actually not more than statistical tools.”

You can find the resources I collected for project researh on this are.na channel

Contact me for the project report: ︎ buse@rbc.xyz