Across the globe, women make up only 22 per cent of artificial intelligence workers. Dr Maisie Li is part of that minority, but her work packs a punch. She develops innovative tools, powered by machine learning and artificial intelligence (ML/AI), to help us get to the bottom of biology faster and with greater accuracy.
Maisie is currently working with CSIRO's Collaborative Intelligence Future Science Platform[Link will open in a new window] to improve the efficiency and accuracy of genome annotation by harnessing both human and machine skills and strengths in an optimised workflow.
We caught up with her to find out more and discover her gene-ius ideas for improving diversity in the AI workforce.
Tell us about your role with CSIRO
I am a CERC postdoctoral fellow in the Crops Data Science Team of the Agriculture and Food business unit.
What is your professional background and what are the areas you specialise in?
My background is in computing science for my Bachelor, Master and PhD degrees. The specific research questions I have solved are from the bioinformatics field, which involves collecting and analysing complex biological data such as genome annotations.
What made you want to pursue a career in tech?
I was interested in a career in tech because I wanted to use my skills and knowledge to develop useful tools using ML/AI for biologists and discover biological insights based on data. ML/AI tools can speed up the process of finding knowledge and answering biological research questions based on the data.
Much of your research has had a women’s health focus, for example developing computational methods for breast cancer prognosis and identifying preeclampsia biomarkers using machine learning methods. What drew you to these projects?
These two diseases significantly threaten women’s health worldwide. Specifically, breast cancer is the most commonly diagnosed cancer in females. It accounted for 24.5% of all new cancer cases and 15.5% of all cancer deaths in 2020. Preeclampsia is a hypertensive disorder of pregnancy and a leading cause of maternal and neonatal mortality and morbidity globally. My work has focussed on developing ML/AI methods to help to improve the disease’s management and treatment.
Tell us about the project you’re currently working on with the Collaborative Intelligence FSP?
My current work focuses on designing the Human-AI Collaborative Intelligence Future Science Platform in Genomics and Bioinformatics.
Annotating sequenced genomes in the process identifying functional and structural elements along the sequence of a genome. It is the bridge that connects understanding the genetic make up of an organism to potential impact, by giving meaning to the data.
But biology is messy, and annotations may vary between species and individuals. Genome annotation has thus been accomplished by meticulous, manual processes carried out for model species by human experts over many years.
However this is extremely time consuming and limited in scale. On the other hand, automated genome annotation by AI is an error-prone process due to incomplete and erroneous genome data. Errors in genome annotation can lead to incorrect experimental design or interpretation of biological mechanisms.
Collaborative Intelligence brings an opportunity to leverage both human and artificial intelligence together, which will improve the efficiency and effectiveness of genome annotation.
How can colleagues, organisations and industries within tech better support and enable women?
Firstly, colleagues and organisations can work to create a culture that promotes inclusion, making women feel valued and respected. Secondly, flexible working arrangements can help to support women who are juggling career and family responsibilities. Lastly, ensuring that women are paid and promoted fairly is critical to supporting their career advancement.
What advice would you give to women and girls wanting to pursue a career in tech?
Believe that women and girls can succeed in a career in tech. If you decide to pursue a career in tech, you must persevere in your studies and any other opportunities such as attending conferences and industry internships. Don’t be afraid of failure. Learn from your mistakes and keep pushing forward!