Women in AI: Brandie Nonnecke of UC Berkeley says investors should insist on responsible AI practices

To present AI-focused ladies teachers and others their well-deserved — and overdue — time within the highlight, TechCrunch is launching a series of interviews specializing in exceptional ladies who’ve contributed to the AI revolution. We’ll publish a number of items all year long because the AI increase continues, highlighting key work that usually goes unrecognized. Learn extra profiles 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 Legislation and Expertise, 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, rules and legal guidelines, offering insights into the advantages and dangers and figuring out methods to harness tech for good.

Q&A

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

I’ve been working in accountable AI governance for almost a decade. My coaching in expertise, public coverage and their intersection with societal impacts drew me into the sphere. AI is already pervasive and profoundly impactful in our lives — for higher and for worse. It’s essential to me to meaningfully contribute to society’s potential to harness this expertise for good reasonably than stand on the sidelines.

What work are you most happy with (within the AI subject)?

I’m actually happy with two issues we’ve achieved. First, The College of California was the primary college to determine accountable AI ideas 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 honour of co-chairing the UC Presidential Working Group on AI and its subsequent everlasting AI Council. In these roles, I’ve been capable of acquire firsthand expertise pondering by means of find out how to finest operationalize our accountable AI ideas so as to safeguard our school, employees, college students, and the broader communities we serve. Second, I feel it’s important 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 supplies steerage on efficient technical and coverage interventions.

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

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

What recommendation would you give to ladies looking for to enter the AI subject?

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

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

I consider some of the 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 could have great impression — good and unhealthy. However different types of machine studying are in use in the present day which might be surreptitiously making choices that immediately have an effect on everybody’s potential to train their rights. Quite than specializing in the most recent marvels of machine studying, it’s extra essential that we concentrate on how and the place machine studying is being utilized no matter its technological prowess.

What are some points AI customers ought to pay attention to?

AI customers ought to pay attention to points associated to knowledge privateness and safety, the potential for bias in AI decision-making and the significance of transparency in how AI programs function and make choices. Understanding these points can empower customers to demand extra accountable and equitable AI programs.

What’s the easiest way to responsibly construct AI?

Responsibly constructing AI entails integrating moral issues at each stage of growth and deployment. This consists of various 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 buyers higher push for accountable AI?

That is such an essential query! For a very long time we by no means expressly mentioned the function of buyers. I can’t specific sufficient how impactful buyers are! I consider the trope that “regulation stifles innovation” is overused and is commonly unfaithful. As a substitute, I firmly consider smaller companies can expertise a late mover benefit and study from the bigger AI corporations which have been growing accountable AI practices and the steerage rising from academia, civil society and authorities. Buyers have the facility to form the trade’s course by making accountable AI practices a important issue of their funding choices. This consists of supporting initiatives that target addressing social challenges by means of AI, selling variety and inclusion inside the AI workforce and advocating for sturdy governance and technical methods that assist to make sure AI applied sciences profit society as a complete.