Girls in AI: Brandie Nonnecke of UC Berkeley says traders ought to insist on accountable AI practices


To offer AI-focused girls teachers and others their well-deserved — and overdue — time within the highlight, TechCrunch is launching a sequence of interviews specializing in exceptional girls who’ve contributed to the AI revolution. We’ll publish a number of items all year long because the AI growth continues, highlighting key work that always goes unrecognized. Learn extra profiles right here.

Brandie Nonnecke is the founding director of the CITRIS Coverage Lab, headquartered at UC Berkeley, which helps interdisciplinary analysis to handle questions across the function of regulation in selling innovation. Nonnecke additionally co-directors the Berkeley Heart for Regulation and Know-how, the place she leads tasks on AI, platforms and society, and the UC Berkeley AI Coverage Hub, an initiative to coach researchers to develop efficient AI governance and coverage frameworks.

In her spare time, Nonnecke hosts a video and podcast sequence, TecHype, that analyzes rising tech insurance policies, laws and legal guidelines, offering insights into the advantages and dangers and figuring out methods to harness tech for good.


Briefly, how did you get your begin in AI? What attracted you to the sector?

I’ve been working in accountable AI governance for practically a decade. My coaching in expertise, public coverage 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 skill to harness this expertise for good fairly than stand on the sidelines.

What work are you most pleased with (within the AI discipline)?

I’m actually pleased with two issues we’ve achieved. First, The College of California was the primary college to ascertain accountable AI rules and a governance construction to raised guarantee accountable procurement and use of AI. We take our dedication to serve the general public in a accountable method critically. I had the distinction of co-chairing the UC Presidential Working Group on AI and its subsequent everlasting AI Council. In these roles, I’ve been in a position to achieve firsthand expertise pondering by way of how one can greatest operationalize our accountable AI rules with a view to safeguard our college, workers, college students, and the broader communities we serve. Second, I believe it’s vital that the general public perceive rising applied sciences and their actual advantages and dangers. We launched TecHype, a video and podcast sequence that demystifies rising applied sciences and offers steering on efficient technical and coverage interventions.

How do you navigate the challenges of the male-dominated tech business, and, by extension, the male-dominated AI business?

Be curious, persistent and undeterred by imposter syndrome. I’ve discovered it essential to hunt out mentors who help range and inclusion, and to supply the identical help to others coming into the sector. Constructing inclusive communities in tech has been a robust solution to share experiences, recommendation and encouragement.

What recommendation would you give to girls in search of to enter the AI discipline?

For ladies coming into the AI discipline, my recommendation is threefold: Search data relentlessly, as AI is a quickly evolving discipline. Embrace networking, as connections will open doorways to alternatives and provide invaluable help. And advocate for your self and others, as your voice is crucial in shaping an inclusive, equitable future for AI. Keep in mind, your distinctive views and experiences enrich the sector and drive innovation.

What are a few of the most urgent points going through AI because it evolves?

I imagine one of the vital urgent points going through AI because it evolves is to not get hung up on the most recent hype cycles. We’re seeing this now with generative AI. Positive, generative AI presents important developments and may have large impression — good and unhealthy. However different types of machine studying are in use right this moment which might be surreptitiously making selections that immediately have an effect on everybody’s skill to train their rights. Fairly than specializing in the most recent marvels of machine studying, it’s extra necessary that we give attention to how and the place machine studying is being utilized no matter its technological prowess.

What are some points AI customers ought to concentrate on?

AI customers ought to concentrate on points associated to information privateness and safety, the potential for bias in AI decision-making and the significance of transparency in how AI methods function and make selections. Understanding these points can empower customers to demand extra accountable and equitable AI methods.

What’s one of the simplest ways to responsibly construct AI?

Responsibly constructing AI includes integrating moral issues at each stage of improvement and deployment. This consists of numerous stakeholder engagement, clear methodologies, bias administration methods and ongoing impression assessments. Prioritizing the general public good and making certain AI applied sciences are developed with human rights, equity and inclusivity at their core are elementary.

How can traders higher push for accountable AI?

That is such an necessary query! For a very long time we by no means expressly mentioned the function of traders. I can’t specific sufficient how impactful traders are! I imagine the trope that “regulation stifles innovation” is overused and is usually unfaithful. As an alternative, I firmly imagine smaller corporations can expertise a late mover benefit and be taught from the bigger AI corporations which were growing accountable AI practices and the steering rising from academia, civil society and authorities. Buyers have the ability to form the business’s path by making accountable AI practices a vital issue of their funding selections. This consists of supporting initiatives that target addressing social challenges by way of AI, selling range and inclusion throughout the AI workforce and advocating for sturdy governance and technical methods that assist to make sure AI applied sciences profit society as an entire.

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