Only 22% of AI professionals are women.
Artificial intelligence (AI) and machine learning (ML) are fields that have traditionally been male-dominated, but that’s starting to change. Today, there are many talented and successful women leaders in AI and ML who are making a significant impact on the industry and are inspiring others to follow in their footsteps.
Here are 7 women leaders in AI/ML to follow and gather inspiration from:
1. Chip Huyen
Chip is a writer, computer scientist and entrepreneur who co-founded Claypot AI, a platform for real-time machine learning. She’s currently teaching CS 329S: Machine Learning Systems Design at Stanford University. Her O’Reilly book, Designing Machine Learning Systems is an Amazon #1 bestseller in Artificial Intelligence. She is consistently posting engaging content and is building a strong MLOps community on LinkedIn and was included in the Top Voices in Data Science & AI in 2020.
2. Rana el Kaliouby
Rana’s mission in life is to humanize technology before it dehumanizes us. She is Deputy CEO at Smart Eye, where they are driving AI innovation with a focus on ethics evangelizing Emotion AI in automotive Interior Sensing, Media Analytics, and beyond. She is an acclaimed TED Talk Speaker, was named by Forbes on their list of America’s Top 50 Women in Tech, and is the co-founder of Affectiva, the company credited with defining the field of Emotion AI.
3. Aishwarya Srinivasan
Aishwarya is a data scientist currently working on the Google Cloud AI Services team, and an entrepreneur who founded Illuminate AI, a first of its kind non-profit organization that provides resources and volunteer mentorship for people who want to build their career in the field of AI. Aishwarya was awarded Trailblazer of the Year by Women in AI in 2022 and Women of Influence by Business Journal in 2022.
4. Lila Ibrahim
Lila is the Chief Operating Officer at DeepMind, a research organization that is committed to developing artificial General intelligence (AGI). She is also a co-founder and chair of Team4Tech, a education technology non-profit that partners with industry-leading companies to bring technology curricula and infrastructure to students in underserved communities. In addition, Lila is a member of the UK AI Council, which works to support the growth and adoption of AI in the UK.
5. Timnit Gebru
Timnit is a computer scientist who works on algorithmic bias, the ethical implications underlying AI projects, and data mining. She is the founder and executive director of the Distributed Artificial Intelligence Research Institute (DAIR). DAIR is an organization that advocates for independent, community-rooted AI research, free from Big Tech’s pervasive influence. She also co-founded Black in AI which aims to increase the presence, inclusion, visibility, and health of black people in the field of AI.
6. Thu Vu
Thu is a senior data analytics consultant for PwC Nederland who has a background in economics and computer science. She is passionate about being creative when explaining difficult topics in data science and general tech. She has a popular YouTube channel called Thu Vu data analytics where she does exactly that. Her mission is to give insight to anyone who is entering the Data analytics/Data science field, wants to advance their R/Python skills, or see what daily life is really like as a data scientist.
7. Tanu Chellam
Tanu is a product leader, international entrepreneur, and VP of Product here at Seldon. She leads the product management, design, developer relations, and product marketing for our machine learning operations scale-up. She has won awards for managing both people and products globally in the past 17 years of her career. Her latest awards include being named Inspiring Fifty in the UK by EQL:Her as part of London Tech Week, and awarded 35 Under 35 by Management Today.
These seven women are just a few of the many leaders in the innovative field of AI and machine learning who are positively impacting the industry. Their continuous work is helping to shape the future of these technologies. We can’t wait to see more female leadership emerge (Let’s raise that 22%!).
