To present AI-focused women academics and others their well-deserved — and overdue — time within the highlight, TechCrunch is launching a series of interviews specializing in remarkable women who’ve contributed to the AI revolution. We’ll publish several pieces all year long because the AI boom continues, highlighting key work that always 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 handle questions across 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 coach 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 advantages and risks and identifying strategies to harness tech for good.
Q&A
Briefly, how did you get your start in AI? What attracted you to the sector?
I’ve been working in responsible AI governance for nearly a decade. My training in technology, public policy and their intersection with societal impacts drew me into the sector. AI is already pervasive and profoundly impactful in our lives — for higher and for worse. It’s necessary to me to meaningfully contribute to society’s ability to harness this technology for good somewhat than stand on the sidelines.
What work are you most pleased with (within the AI field)?
I’m really pleased with two things we’ve achieved. First, The University of California was the primary university to ascertain responsible AI principles and a governance structure to higher ensure responsible procurement and use of AI. We take our commitment to serve the general public in a responsible manner seriously. I had the glory of co-chairing the UC Presidential Working Group on AI and its subsequent everlasting AI Council. In these roles, I’ve been capable of gain firsthand experience pondering through how one can best operationalize our responsible AI principles in an effort to safeguard our faculty, staff, students, and the broader communities we serve. Second, I feel it’s critical that the general public understand emerging technologies and their real advantages and risks. We launched TecHype, a video and podcast series that demystifies emerging technologies and provides guidance on effective technical and policy interventions.
How do you navigate the challenges of the male-dominated tech industry, and, by extension, the male-dominated AI industry?
Be curious, persistent and undeterred by imposter syndrome. I’ve found it crucial to hunt down mentors who support diversity and inclusion, and to supply the identical support to others entering the sector. Constructing inclusive communities in tech has been a robust strategy to share experiences, advice and encouragement.
What advice would you give to women searching for to enter the AI field?
For ladies 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 crucial in shaping an inclusive, equitable future for AI. Remember, your unique perspectives and experiences enrich the sector and drive innovation.
What are a number of the most pressing issues facing AI because it evolves?
I imagine one of the vital pressing issues facing AI because it evolves is to not get hung up on the most recent hype cycles. We’re seeing this now with generative AI. Sure, generative AI presents significant advancements and could have tremendous impact — good and bad. But other types of machine learning are in use today which can be surreptitiously making decisions that directly affect everyone’s ability to exercise their rights. Relatively than specializing in the most recent marvels of machine learning, it’s more necessary that we give attention to how and where machine learning is being applied no matter its technological prowess.
What are some issues AI users should concentrate on?
AI users should concentrate on issues related to data privacy and security, the potential for bias in AI decision-making and the importance of transparency in how AI systems operate and make decisions. Understanding these issues can empower users to demand more accountable and equitable AI systems.
What’s the very best strategy to responsibly construct AI?
Responsibly constructing AI involves integrating ethical considerations at every stage of development and deployment. This includes diverse stakeholder engagement, transparent methodologies, bias management strategies and ongoing impact assessments. Prioritizing the general public good and ensuring AI technologies are developed with human rights, fairness and inclusivity at their core are fundamental.
How can investors higher push for responsible AI?
That is such a very important query! For a very long time we never expressly discussed the role of investors. I cannot express enough how impactful investors are! I imagine the trope that “regulation stifles innovation” is overused and is commonly unfaithful. As an alternative, I firmly imagine smaller firms can experience a late mover advantage and learn from the larger AI corporations which were developing responsible AI practices and the guidance emerging from academia, civil society and government. Investors have the facility to shape the industry’s direction by making responsible AI practices a critical consider their investment decisions. This includes supporting initiatives that give attention to addressing social challenges through AI, promoting diversity and inclusion inside the AI workforce and advocating for strong governance and technical strategies that help to make sure AI technologies profit society as an entire.
