In the realm of artificial intelligence, the spotlight often falls on male pioneers and tech giants, overshadowing the significant contributions made by brilliant women in the UK and beyond. While men have played a vital role in advancing AI, it’s high time we recognise and celebrate the women who have propelled the AI revolution forward.
We’ve brought together some incredible women at the forefront of the AI revolution – but these are just the tip of the iceberg.
Women in AI technology to watch
Timnit Gebru is a computer scientist known for her work on algorithmic bias and addressing ethical concerns of AI. She is the founder of Distributed Artificial Intelligence Research Insitute (DAIR) and co-founder of the Black in AI initiative and has been an advocate for diversity and inclusion in the tech industry.
Gebru’s research has focused on bias and fairness in AI systems and the societal impact of AI technologies. She has made significant contributions to the field and has been recognised for her efforts in promoting fair, responsible AI development. In 2022, she was named one of Time’s 100 most influential people.
Virginia Dignum is a professor of Responsible Artificial Intelligence and the scientific Director of WASP-HS, the Wallenberg AI, Autonomous Systems and Software Program on Humanities and Society, at Umeå University in Sweden. She is an expert in the field of AI ethics and responsible AI development. Dignum has conducted extensive research on ethical decision-making in autonomous systems and the societal implications of AI. She is actively involved in several international policy initiatives for AI research and applications, including the World Economic Forum’s Global Artificial Intelligence Council.
- Suggested reading: Responsible Artificial Intelligence
- Suggested watch: Scottish AI Summit 2022 Keynote – Responsible AI: Why Care?
Joy Buolamwini is an AI researcher and activist known for her work on addressing biases in facial recognition technology. As the founder of the Algorithmic Justice League, Buolamwini campaigns for transparency and accountability in AI systems. Her groundbreaking research has exposed the biases present in facial recognition algorithms, particularly concerning gender and race.
- Suggested watch: Joy Buolammwini: How I’m fighting bias in algorithms – TED Talk
Professor Shannon Vallor is the Baillie Gifford Chair in the Ethics of Data and Artificial Intelligence at the University of Edinburgh. Professor of philosophy and the author of the book “Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting”, her research focuses on the ethical implications of emerging technologies. Vallor explores the intersection of technology, moral character, and ethical decision-making. Her work emphasises the importance of cultivating virtues and ethical frameworks to guide the development and use of AI.
- Suggested reading: Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting
Maria Axente is an award-winning AI ethics and global public policy expert working as an Intellectual Forum Senior Research Associate at the University of Cambridge and Responsible AI and AI for Good Lead at PwC United Kingdom. She is a member of various advisory boards including the UNICEF #AI4Children and the UK All-Party Parliamentary Group on AI. At PwC, Axente advises partners across industry, academia, governments, and more, on how to harness the power of AI in an ethical and responsible manner. She has played a crucial part in the development and set-up of PwC’s UK AI Center of Excellence, the firm’s AI strategy and most recently the development of PwC’s Responsible AI toolkit, firms methodology for embedding ethics in AI.
- Suggested listening: Responsible AI by design with Maria Axente, PwC UK with the Data Democratization Podcast
Gender bias in AI: How can we dismantle bias and build a more inclusive industry?
Better understand and combat gender bias in data
AI systems are only as unbiased as the data they’re trained on. Recognising this, researchers and data scientists work diligently to eliminate gender biases in datasets to ensure fairer and more equitable AI outcomes. We should constantly strive to identify and mitigate biases in AI and data systems. Regular audits and evaluations can help uncover and rectify discriminatory outcomes.
Invisible Women: Exposing Data Bias in a World Designed for Men by Caroline Criado Perez is a must-read for anyone interested in exploring how data bias impacts the world around us.
Empower future generations of leaders
Initiatives like Scotland Women in Technology, Girls Who Code UK, and AI4ALL dedicate themselves to empowering young women with the skills and opportunities needed to thrive in the AI and data industry. By bridging the gender gap in tech, they are fostering a more diverse and inclusive landscape. Schools are also at the forefront of leading change with AI programs and courses promoting diversity and inclusivity.
Data Skills for Work offers lots of free and funded training for students and learners of all ages. Explore their portfolio of courses to try anything from Introduction to Machine Learning to Data Analysis, AI, Python and beyond.
Promote and action diverse hiring
Organisations should actively seek to diversify their AI teams by implementing inclusive hiring practices, promoting gender diversity, and providing equal opportunities for women and underrepresented groups. Did you know that you can use AI to attract more diverse talent? Generative AI is currently being used to create more inclusive job descriptions. These AI algorithms analyse existing job descriptions and suggest changes that can make them more inclusive (though remember, AI is only as unbiased as the data they’re trained on)!
MIT has a quick check list of things to avoid when creating job descriptions, which is a great starting point.
Foster collaboration and mentorships to create safer spaces for discussion
Establishing mentorship programs that connect women in AI with experienced professionals can guide and support their career journeys. Collaborative efforts can empower women and facilitate knowledge sharing. We should encourage open conversations about biases, ethics, and inclusivity in AI.
The Data Lab Community recently hosted a Meetup for Women in Data & AI, which brought together a dynamic and diverse group of individuals passionate about advancing women in data, AI, and technology. Events like these are important to provide a platform and space for attendees to connect, share experiences, and explore opportunities to drive positive change.
The Data Lab Community also has an incredible mentoring programme to match people with experienced professionals. It’s free to join and benefit from this great programme.
So – what next?
As we witness the AI revolution unfold, it is crucial to acknowledge the invaluable contributions of women who have played (and continue to play) instrumental roles in its advancement. From groundbreaking research to transformative applications, women are reshaping industries, challenging biases, and championing inclusivity. By recognising their achievements and taking active steps to create an inclusive, diverse, and ethical data and AI community, we can ensure that diverse perspectives drive the AI revolution and lead to a future that benefits all humanity.
Who are the heroines in AI that you are following? Let us know in the comments!
Blog by Jane Blanchard, Brand and Campaign Manager at The Data Lab