Dr. Kirstine Dale: Discussion about Data Science and Environmental Intelligence

This week, Dr. Kirstine Dale joined Women In Climate for a discussion about Data Science and Environmental Intelligence: what it is, its applications, and the underrepresentation of women in the field and what this implies. Kirstine is a passionate scientist (“Science is like magic, but real”) and in her talk she gave an overview of her career path which followed her interests. Kirstine is the Met Office’s Principal Fellow for Data Science and Co-Director for the Joint Centre for Excellence in Environmental Intelligence between the Met Office and the University of Exeter.

What is Data Science and why is it exciting?

Data Science describes the field of exploring large data sets with means of machine learning and artificial intelligence, or in essence drawing meaning and value from large amounts of data. Data Science surrounds us every day. From suggesting optimal driving routes to delivering personalised newsfeeds, there are few areas not influenced by Data science. It also benefits diverse scientific applications, like health care solutions or weather and ocean predictions. In fact, the current time marks a sweet spot for Data Science because of the concurrence of increasing computing power, the unprecedented amount of data, and availability of techniques to analyse this data.

The Met Office has identified the importance of Data Science and included in its Research and Innovation strategy the goal of ‘Fusing simulations with Data Science’. Kirstine is in a leading position in this field as the Met Office Principal Fellow for Data Sciences and the Co-Director of the Joint Centre for Excellence in Environmental Intelligence. The Joint Centre supplies the resources and research to explore applications of Environmental Intelligence – the exploration of environmental data with artificial intelligence – creating the networks across institutions for enabling exchange and progress.

Where are the Women?

To exploit its full potential, the emerging field Data Science needs all hands on deck – Is this mirrored in a diverse, vibrant workforce?

Not quite. As in most STEM subjects, women are underrepresented in Data Sciences. A report by the Alan Turing Institute found that globally only 26% of employees in Data Science are women (22% in the UK) and that women tend to change jobs more often or leave the sector. Another report found that the majority of Data Science teams don’t include women at all (53%). At the same time, Artificial Intelligence positions are reported as “hard to fill” (69%).

The gender imbalance has negative implications for the quality of Data Science, and diversifying the workforce is beneficial beyond being a box-ticking exercise. Kirstine gave three reasons: first and foremost, it is the right thing to do! Second, Artificial Intelligence algorithms and Data Sciences are inherently prone to bias. Algorithms are trained with and based on data, which therefore have to be representative of the society. If there is a bias in the people collecting the data, analysing it, creating the algorithms, etc. the outcome will likely be biased as well and in consequence not represent or benefit the entire society. Third, numerous studies have found that diverse workforces are more productive, more creative, more resilient, etc. (see for example a study by Nielsen et al. (2018) or this Catalyst summary). Therefore employers and companies benefit directly from a diverse workforce.

Overall, this evidence is a strong call to diversify Data Science, from data collection to algorithms. A diverse Data Science team is more likely to produce solutions for the entire society for the challenges of our time.

In the discussion, Kirstine gave some brilliant tips for how to thrive in your career and build the courage to aim high:

  • Build a support network. This can be friends, family, and mentors, from distance or near you. Claim some positive energy whenever you need a boost in confidence (and of course return the favour another time). In this way, taking risks will become easier, and large professional steps less daunting.
  • Follow your interests. Take risks. Apply to positions you are interested in, even if you don’t tick all the boxes for the application. For preparing for the times an application is rejected, build your resilience by being passionate about your subject but not too attached personally.
  • Demonstrate leadership and be a role model for the change you want to see. This involves saying yes e.g. to panel discussions if this improves gender balance, or saying no e.g. to give someone else the opportunity such as a younger colleague.

We thank Kirstine for taking the time to join Women of Climate and supporters for this inspiring talk. Thanks to Laura Dawkins for leading the discussion.