The Alliance was thrilled to recently participate in and lead an interactive session on Coding Gender Equality: at the world’s leading event for open internet – MozFest. If you are unfamiliar with MozFest – every year the Mozilla Foundation gathers technologists, educators, activists, researchers, and young people together to explore, learn and collaborate on how we can make the internet healthier. And this year was extra special – it was the 10th anniversary of MozFest and the week long event welcomed 2500 participants from over 50 countries.
MozFest = discovering cutting edge technology, new collaborations and connections, sharing brilliant ideas and hearing inspiring stories in over 300 interactive sessions . So both leaders of the Alliance: Ciudaaplusdbadmina Inteligente and Women at the Table, were proud to have led an interactive session ‘Coding Gender Equality: Affirmative Action for Algorithms’.
The goal of our interactive session was to deepen participants awareness and knowledge of the relevance of gender in ADM and the real-life constraints that hinder gender equality in ADM (that is gender bias in ADM) – creating a space for individuals to become active creators and contributors to mitigating and correcting for gender bias in ADM.
In interactive session the landscape was set for gender bias in ADM highlighting the alarming prevalence of real-world examples of gender bias in ADM and machine learning. Don’t worry – the session offered hope through practical tools, solutions and concrete actions to mitigate and correct for real life gender biases in ADM. We shared innovative approaches such as the implementation of low cost targeted pilots that correct for gender bias across geographies on the municipal level (amongst other tools and recommendations shared!). We were delighted that the session fuelled creativity and invigorated focus on gender equality in ADM.
In the era of AI, ADM and machine learning we must raise awareness and spur action around the challenges of digital inclusion – AI must serve humanity. The Alliance will continue to keep talking and taking action to correct gender bias in ADM – we need to drive change by effecting individual and institutional transformation. We need to ensure gender bias is not baked into the ADM and machine learning systems of the future! Join the Alliance now.