To give AI-focused women academics and others their well-deserved – and overdue – time within the highlight, TechCrunch is launching a series of interviews specializing in notable women who’ve contributed to the AI ​​revolution. As the AI ​​boom continues, we are going to publish several articles all year long highlighting essential work that always goes unrecognized. You can find more profiles here.
Brandie Nonnecke is the founding director of the CITRIS Policy Lab based at UC Berkeley, which supports interdisciplinary research to reply questions surrounding the role of regulation in fostering innovation. Nonnecke can be co-director of 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 free time, Nonnecke hosts the video and podcast series TecHype, which analyzes latest technology policies, regulations and laws, provides insight into the advantages and risks, and identifies strategies to leverage technology for good.
questions and answers
In short, how did you start with AI? What attracted you to this field?
I even have been working in the world of ​​responsible AI governance for nearly a decade. My training in technology, public policy, and their intersection with societal impact led me to this field. AI is already ubiquitous and is having a profound impact on our lives – for higher or worse. It is very important to me to make a meaningful contribution to making sure that society can use this technology for an excellent purpose moderately than simply standing on the sidelines.
What work are you most pleased with (within the AI ​​space)?
I'm really pleased with two things we achieved. First, the University of California was the primary university to determine responsible AI principles and a governance structure to raised ensure responsible procurement and use of AI. We take seriously our obligation to serve the general public responsibly. I had the dignity of co-chairing the UC Presidential Working Group on AI and its subsequent standing AI Council. These roles allowed me to realize first-hand experience and reflect on how we are able to best implement our responsible AI principles to guard our faculty, staff, students, and the broader communities we serve. Second, I consider it’s critical that the general public understand latest technologies and their real advantages and risks. We launched TecHype, a video and podcast series that demystifies latest technologies and provides guidance for effective technical and policy interventions.
How do you overcome the challenges of the male-dominated technology industry and subsequently also the male-dominated AI industry?
Be curious, persistent and don't let impostor syndrome scare you away. I even have found it crucial to hunt down mentors who support diversity and inclusion and to offer the identical support to others entering the sector. Building inclusive communities in technology has been a robust option to share experiences, advice and encouragement.
What advice would you give to women wanting to enter the AI ​​field?
For women entering the AI ​​field, I offer three pieces of recommendation: Relentlessly pursue knowledge, because AI is a rapidly evolving field. Take advantage of networking because contacts open doors to opportunities and supply invaluable support. And advocate for yourself and others, because your voice is critical to shaping an inclusive, equitable future in AI. Remember that your unique perspectives and experiences enrich the sector and drive innovation.
What are a number of the most pressing issues facing AI because it continues to evolve?
I consider that probably the most pressing problems facing AI because it evolves shouldn’t be buying into the newest hype cycles. We’re seeing this now with generative AI. To ensure, generative AI represents significant advances and may have enormous impacts – for higher or worse. However, other types of machine learning are also in use today, secretly making decisions that directly impact each individual's ability to exercise their rights. Instead of specializing in the newest wonders of machine learning, it’s more essential that we concentrate on how and where machine learning is applied, no matter its technological prowess.
What issues should AI users concentrate on?
AI users should concentrate on the problems surrounding privacy and security, the potential for bias in AI decisions, and the importance of transparency in how AI systems operate and make decisions. Understanding these issues can empower users to demand more responsible and fair AI systems.
What is the most effective option to construct AI responsibly?
Building AI responsibly requires considering ethical considerations at every stage of development and deployment. This includes diverse stakeholder engagement, transparent methodologies, bias management strategies and ongoing impact assessments. It is crucial to prioritize the common good and be sure that human rights, fairness and inclusivity are at the center of the event of AI technologies.
How can investors higher advance responsible AI?
This is such a very important query! For an extended time, we never explicitly talked concerning the role of investors. I can't express enough how influential investors are! In my opinion, the saying “regulation stifles innovation” is overused and infrequently unfaithful. Instead, I strongly consider that smaller corporations can enjoy a late-mover advantage and learn from the larger AI corporations which have developed responsible AI practices, in addition to from the guidance from academia, civil society and government. Investors have the ability to find out the direction of the industry by making responsible AI practices a critical consider their investment decisions. This includes supporting initiatives focused on addressing societal challenges through AI, promoting diversity and inclusion throughout the AI ​​workforce, and advocating for strong governance and technical policies that help AI technologies profit society profit as a complete.
