Brandie Nonnecke Advocates for Responsible AI Practices: A Perspective from Women in AI at UC Berkeley
To give AI-focused women academics and others their well-deserved — and overdue — time in the spotlight, TechCrunch is launching a series of interviews focusing on remarkable women who’ve contributed to the AI revolution. We’ll publish several pieces throughout the year as the AI boom continues, highlighting key work that often goes unrecognized. Read more profiles here.
Brandie Nonnecke is the founding director of the CITRIS Policy Lab, headquartered at UC Berkeley, which supports interdisciplinary research to address questions around the role of regulation in promoting innovation. Nonnecke also co-directors the Berkeley Center for Law and Technology, where she leads projects on AI, platforms and society, and the UC Berkeley AI Policy Hub, an initiative to train researchers to develop effective AI governance and policy frameworks.
In her spare time, Nonnecke hosts a video and podcast series, TecHype, that analyzes emerging tech policies, regulations and laws, providing insights into the benefits and risks and identifying strategies to harness tech for good.
Briefly, how did you get your start in AI? What attracted you to the field?
I’ve dedicated almost a decade of my life to the governance of responsible Artificial Intelligence. My background in technology and public policy, along with how they intersect with societal impacts, drew me into this field. Artificial Intelligence is already profoundly influencing our lives, both negatively and positively. It is crucial for me to contribute significantly towards using this technology for societal good rather than remaining a passive bystander.
Which work in the AI sector are you most proud of?
There are two accomplishments that I am particularly proud of. The first one being the University of California, which was the first educational institution to establish principles for responsible AI and create a structure for governance, to enhance responsible procurement and usage of AI. Our commitment towards serving the public responsibly is something we take very seriously. I had the privilege of co-chairing both the University of California’s Presidential Working Group on Artificial Intelligence and the permanent Artificial Intelligence Council that followed. Through these roles, I have been able to gain firsthand experience in strategizing how to best operationalize our responsible AI principles, with the goal of protecting our educators, staff, students and the wider communities we cater to. Secondly, I believe it’s essential for the public to gain an understanding of emerging technologies, alongside their actual benefits and risks. To facilitate this, we initiated TecHype, a series of videos and podcasts aimed at debunking myths around emerging technologies and offering advice on effective technical initiatives and policy interventions.
How do you manage the difficulties posed by the male-dominated tech industry and, subsequently, the male-dominated AI industry?
Be curious, persistent and undeterred by imposter syndrome. I’ve found it crucial to seek out mentors who support diversity and inclusion, and to offer the same support to others entering the field. Building inclusive communities in tech has been a powerful way to share experiences, advice and encouragement.
What advice would you give to women seeking to enter the AI field?
For women entering the AI field, my advice is threefold: Seek knowledge relentlessly, as AI is a rapidly evolving field. Embrace networking, as connections will open doors to opportunities and offer invaluable support. And advocate for yourself and others, as your voice is essential in shaping an inclusive, equitable future for AI. Remember, your unique perspectives and experiences enrich the field and drive innovation.
What are some of the most pressing issues facing AI as it evolves?
One of the most significant challenges AI’s evolution is currently facing is the tendency to dwell on the latest hype cycles, such as generative AI. Generative AI indeed brings substantial development and may create huge impacts, whether positive or negative. However, there are other types of machine learning today that discretely make decisions directly impacting individuals’ rights. Therefore, instead of dwelling on the latest advances in machine learning, it’s more critical to concentrate on machine learning’s application, regardless of its technical supremacy.
Which issues should AI users be cognizant of?
Users of AI should understand the issues associated with data privacy and security, AI decision-making’s potential for prejudice, and the critical need for transparency in AI systems’ operations and decision-making processes. Becoming familiar with these issues will allow users to advocate for AI systems that are more responsible and fair.
What constitutes the most effective method of developing AI in a responsible manner?
Building AI responsibly requires infusing ethical practices at every step of its creation and implementation. This involves including a range of stakeholders, making methodologies transparent, managing bias, and regularly assessing impacts. Prioritizing societal benefits and designing AI technologies keeping human rights, fairness, and inclusivity in view, is crucial.
What can investors do to promote responsible AI?
This question is incredibly significant! The impact of investors and their role was seldom discussed explicitly before. I can’t emphasize how influential investors can be! The notion that “regulations hamper innovation” is often overstated and generally false. On the contrary, I strongly believe that smaller companies can gain from late mover benefits and borrow learnings from bigger AI firms that are already practicing responsible AI, along with advisories emerging from academia, government, and civil society. Investors can steer the industry’s direction by prioritizing responsible AI practices in their investment decisions, support initiatives tackling societal issues via AI, encourage diversity and inclusion in AI teams, and push for robust governance and technical strategies ensuring AI technologies are beneficial for all of society.
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