Francesca is the co-founder and CEO of Diversity VC, a non-profit made up of interested individuals working in venture capital, who seek to increase diversity of thought in the venture and tech industry. As well as producing content, running training for VCs, events for founders and an internship programme, Diversity VC publishes original data on the state of diversity in the technology and VC industry, including the first-ever study on the number of Women in VC in 2017 in partnership with the BVCA and the Female Founder and VCs report in February 2019 in partnership with the British Business Bank and the BVCA. Diversity VC has been featured in the Financial Times, The Sunday Times and was highlighted by the Chancellor in the UK Government Budget 2017. Francesca is also a seed investor focused on investing in overlooked entrepreneurs. She’s worked at Seraphim Capital, Downing Ventures and Techstars. She graduated from Cambridge and worked in advertising before joining the VC industry. Francesca was named 35 Under 35 in Management Today 2018 and Forbes 30 Under 30 Europe in 2019.
AI has a diversity problem. Too few women and people from diverse cultural or economic backgrounds are making it into the industry. This matters not just for those who are unfairly prevented from becoming data scientists, but for society as a whole. Tackling that lack of diversity could be the difference between a world where AI plays an overwhelmingly positive role in humanity's future, and one where it amplifies biases and division.
Dr Sarah Jarvis is a leading computer engineer and neuroscientist with a career founded on applying intelligent solutions to real-world problems. As Head of Data Science at PROWLER.io in Cambridge, she works with a global team of researchers and engineers in building PROWLER.io’s ground-breaking decision-making platform.
She trained at Freiburg University in Germany and Imperial College in London. Prior to joining PROWLER.io, she worked in public health, building machine learning tools to help developing countries decide how to best allocate budgets for their health programmes. Working closely with the World Bank, she helped to guide the spending of budgets worth in total more than $250 million.
Data Science Research Fellow
The Alan Turing Institute
Quantifying Bias: A Data-driven Approach to Workplace Gender Equality
Quantifying bias: A Data-Driven Approach to Workplace Gender Equality
AI affects almost every aspect of our daily lives, yet there is a troubling underrepresentation of women in this sector. As technology reflects the worldview of its developers, AI systems are being coded with social biases. Alongside gender-biased AI, there are significant economic and governance-related issues associated with the exclusion of women from AI careers. This talk explores how the gendered nature of technical culture and workplace defaults are key factors in women’s underrepresentation in tech. It introduces the current data-driven research at the Turing to monitor these ‘chilly’ workplace environments and motivate evidence-based policy towards achieving gender equality.
Anna FitzMaurice is a postdoctoral research fellow on The Alan Turing Institute’s Women in Data Science and AI project. Her research at the Turing sits at the intersection of technology and society, taking a data-driven approach to investigating the systematic exclusion of women from tech, and the impact this is having on the development of AI. As well as industry experience in data science, she holds a PhD from Princeton University in Atmospheric and Oceanic Sciences, with a focus on modelling ice-ocean interactions under future climate change scenarios, and an MMath in Mathematics (first class) from the University of Oxford.
In 2016 a small team at Facebook set out to find a way to exclude sad posts from their in-feed Memories product, “On This Day”. We used a multi-disciplined approach, including a machine learning model to predict sad memories, to significantly reduce the number of sad and emotional posts seen in feed, improving the user experiences.
Sandi Conroy is a Data Science Manager at Facebook who studied Maths and Statistics at The Pennsylvania State University and George Mason University. Her expertise is in statistical modelling and using product analytics to set team strategy. Sandi has a particular passion for building diverse and inclusive teams and co-founded the Diversity Committee for her current department.