#152 Driving diversity in data science with Fiona Milne, founder of WiMLDS Chapter

As few as 15% of data scientists today are women. And that lack of diversity is a serious issue. AI algorithms are susceptible to bias, so building them requires a team that includes a wide range of views and experiences. What’s preventing more women from joining the field? In this week’s podcast episode, Felipe will be speaking with Fiona Milne, Head of Data and Ai at Whispir and Founder of WiMLDS Chapter Fiona is an Astrophysicist and Mathematician that heads the data and Ai at Whispir. With more than 10 years of experience in data science, Fiona offers Whispir invaluable experience on machine learning with previous projects for NAB, Odds.com.au, MYOB and the ACCC (Australian Competition and Consumer Commission). She has also founded the ‘Women in Machine Learning and Data Science’ Meetup alongside two industry colleagues. The group encourages and supports women in the industry through monthly events which include speakers, panels, evening and lunchtime events. With a Masters in Astrophysics, she also has spent time working on ‘passion projects’ which use machine learning to at images from Kepler telescope and leveraging Google AI’s open-source library Astronet to potentially discover new exoplanets. Quotes: Diversity is really important. Diverse teams are proven to be more creative and more innovative. And they're proven to be better at solving problems, they're proven to be better at making decisions. Biases or unfairness in the development of AI. And that kind of like helps us have a conversation where we get to decide the society that we want to create in the future, instead of blindly perpetuating the one that we've had so far. Knowing that there are improvements we can make there. If you are in a position to vote with your feet, go for it. We need visible leaders that come from different parts, that think differently, that is diverse in their genders and across the spectrum. Thanks to our sponsor Talent Insights Group Read the full episode summary here: Ep 152 Enjoy the show!

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