? 8 March ? 15:00 – 17:30 (CET)
Webinar
UNESCO and the World Economic Forum present Girl Trouble: Breaking Through The Bias in AI on International Women’s Day. This timely round-table brings together a range of leading female voices in tech to confront the deep-rooted gender imbalances skewing the development of artificial intelligence.
Today critics charge that AI feeds on biased data-sets, amplifying the existing anti-female biases of our societies, and that AI is perpetuating harmful stereotypes of women as submissive and subservient. Is it any wonder when only 22% of AI professionals globally are women?
The panelists are female change-makers in AI. From C-suite professionals taking decisions which affect us all, to women innovating new AI tools and policies to help vulnerable groups, to those courageously exposing injustice and algorithmic biases.
There’s an urgent need for more women to participate in and lead the design, development, and deployment of AI systems. Evidence shows that by 2022, 85% of AI projects will deliver erroneous outcomes due to bias.
AI Recruiters searching for female AI specialists online just cannot find them. Companies hiring experts for AI and data science jobs estimate fewer than 1 percent of the applications they receive come from women. Women and girls are 4 times less likely to know how to programme computers, and 13 times less likely to file for technology patent. They are also less likely to occupy leadership positions in tech companies.
Building on UNESCO’s cutting edge research in this field, and flagship 2019 publication “I’d Blush if I Could”, and policy guidance on gender equality in the 2020 UNESCO Draft Recommendation on the Ethics of Artificial Intelligence, the panel will look at:
The 4th industrial revolution is on our doorstep, and gender equality risks being set back decades; What more can we do to attract more women to design jobs in AI, and to support them to take their seats on the boards of tech companies.
How can AI help us advance women and girls’ rights in society? And how can we solve the problem of algorithmic gender bias in AI systems?
Women’s leadership in the AI Sector at all levels, from big tech to the start-up AI economy in developing countries will be placed under the microscope.
