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To give AI-focused female academics and others their deserved – and overdue – time in the spotlight, TechCrunch is launching a series of interviews Focusing on notable women who have contributed to the AI revolution. As the AI boom continues, we’ll be publishing several pieces throughout the year, highlighting key work that often goes unrecognized. Read more profiles Here,
miranda book She is the founding director of the Center for Democracy and Technology’s AI Governance Lab, where she works to help create solutions that can effectively regulate and control AI systems. She helped guide responsible AI strategies at Meta and previously worked as a senior policy analyst at the Uptown organization, which seeks to use the technology to advance equity and justice.
Briefly, how did you get your start in AI? What attracted you to this field?
I was drawn to working on machine learning and AI by seeing the way these technologies were colliding with fundamental conversations about society – values, rights and which communities are left behind. My early work exploring the intersection of AI and civil rights reinforced to me that AI systems are more than technical artifacts; They are systems that are shaped and created by their interactions with people, bureaucracy and policies. I’ve always been adept at translating between technical and non-technical contexts, and at helping communities with a variety of expertise shape the way we build AI from the ground up, helping to break down the appearance of technical complexity. I was excited by the opportunity. ,
What work (in the AI field) are you most proud of?
When I first started working in this field, many people still needed convincing that AI systems could have discriminatory effects for marginalized populations, without the need to do anything about those harms. Not there. Although there is still a huge gap between the status quo and a future where biases and other harms are systematically tackled, I am satisfied with the research my colleagues and I have done. Discrimination in personalized online My work within the industry on advertising and algorithmic fairness helped advance Meaningful changes to Meta’s ad delivery system and progress toward reducing inequalities in access to vital economic opportunities.
How do you deal with the challenges of the male-dominated tech industry and, by extension, the male-dominated AI industry?
I’ve been fortunate to work with phenomenal colleagues and teams who have been generous with both opportunities and sincere support, and I’ve tried to bring that energy to any room we find ourselves in. In my most recent career change, I was delighted that almost all of my choices involved working within unprecedented women-led teams or organizations, and I hope this field will continue to elevate the voices of those who have traditionally been technology-led. Are not focused in oriented conversation.
What advice would you give to women wanting to enter the AI field?
This is the same advice I give to anyone who asks: Find supportive managers, mentors, and teams who energize and motivate you, who value your opinions and perspectives, and who are willing to stand up for you and your work. Let’s put ourselves on the line.
What are some of the most pressing issues facing AI during its development?
The impacts and harms that AI systems can have on people are already well known at this point, and one of the biggest challenges is moving from describing the problem to systematically addressing those harms and encouraging adoption. Have to develop strong attitude. we launched AI Governance Lab On the CDT to advance progress in both directions.
What issues should AI users be aware of?
For the most part, AI systems are still missing seat belts, airbags, and traffic signs, so proceed with caution before using them for consequential tasks.
What’s the best way to create AI responsibly?
The best way to build AI responsibly is with humility. Consider how success for the AI system you are working on is defined, who that definition serves, and what context may be missing. Think about what might cause the system to fail and what would happen if it did. And build systems not only with the people who will use them, but also with the communities who will be subject to them.
How can investors better push for responsible AI?
Investors need to make room for technology makers to proceed more thoughtfully before bringing half-baked technologies to market. The intense competitive pressure to release the latest, biggest and brightest new AI models is leading to less investment in responsible practices. While seamless innovation sings a catchy siren song, it is a mirage that will leave everyone worse off.
AI is not magic; This is just a mirror that is being held in front of the society. If we want it to reflect something different, we have to work.
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