- What role do you play in narrowing the skills gap in Data Science, AI or Data Ethics? For the last few years, I have been focusing on AI-Literacy (in other words, AI education) at AIClub, with a heavy focus on K-12. My belief is that AI will impact all aspects of human life, and that AI literacy will need to be a skill we all acquire, not just data scientists. I also believe that ensuring safe and ethical AI will require everyone to have a basic understanding of AI so that they can be part of the conversation of how to use and practice AI safely.
- What challenges have you faced as a woman in your field?I think the situation for women in technical fields has improved substantially over the last couple of decades. When I started out, I was often the only woman in any meeting. On one hand, that makes it easy to be noticed! However, it can be uncomfortable till you get used to it. I was lucky to have mentors (both men and women) who gave me tips on how to overcome shyness and to speak up when I needed to. Sometimes the issues are subtle – for example you may give a joint presentation with a male colleague and find that all the questions will be directed at him even if you are the more senior presenter. These kinds of things can be very demoralizing, but they happen to women in tech roles everywhere. My advice to young women in the field is to develop a circle of support – others that you can discuss these issues with, learn tips, keep working, and don’t shy away from sharing your accomplishments and opinions. Merit shines through.
- Who was your greatest mentor or inspiration professionally? One of my favorite mentors, whom I met early in my career, was Harriet Coverston. She was a Distinguished Engineer at Sun Microsystems, where I had my first job as a staff engineer. It was inspiring to hear her story of being an engineer from the early days of supercomputing at Lawrence Livermore Labs to founding several startups.
- With such a demand for data science roles, what non-traditional paths have you found to be beneficial for employers seeking to create data teams? I actually wrote an article about this for Forbes (Hiring a Data Scientist – the Good, the Bad and the Ugly). The key thing I have learned is to identify clearly what skills are essential in each team member (rather than the master list of desired skills) and then find ways to train people for those skills. Some approaches that have worked well for me include (a) hiring statisticians who want to learn how to code and complementing their existing knowledge with python and other skills, (b) hiring software engineers who want to learn data science and training them – leveraging their existing skills in production code and deployment, and (c) hiring fresh graduates who have demonstrated an aptitude for data science in their college courses.
- What characteristics does a person need to begin (or advance) their career in data/AI/ ethics? I think there will be a very wide range of roles in data/AI/ethics in the future. What I generally look for in a hire is the ability and willingness to learn. All of the required skills can be taught and learned.
- What additional advice would you offer to women looking to enter your field? I think AI and data science (and all the roles within) are great opportunities for women. In my work with AIClub, I am seeing girls as young as 6th grade do amazing projects with AI. As someone who has spent decades in computer science roles, one thing that distinguishes AI is how easy it is to connect the work you are doing to impact. This is particularly appealing to young girls. Studies have also shown that AI ethics issues like bias can only be seriously mitigated when there is human diversity in every stage of the AI lifecycle. For women entering the field, what I would say is – do not let the implied math and coding scare you. The key traits that are needed are problem solving, investigative curiosity, desire to communicate, and willingness to learn. If you have those – go for it!
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