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Ive spent two decades as a researcher and educator in artificial intelligence, drawn to the field by the opportunity to explore the mysteries of perception and cognition. But life is rarely as simple as wed like, and the arc of my career has paralleled my mothers escalating health struggles, including a chronic, life-threatening cardiovascular condition. As all-consuming as the world of academia can be, it sometimes feels as if Ive spent as much time in hospitals as I have in my lab.

Im happy to report my mother continues to persevere, but her resilience hasnt been the only silver lining to this ordeal. Years spent in the company of nurses and doctorsunfailingly committed, but perpetually overworked and often sleep deprivedconvinced me that the power of AI could radically elevate the way care is delivered. Intelligent sensors could keep tireless watch over patients, automate time-consuming tasks like charting and transcription, and identify lapses in safety protocols as they happen. After all, if AI can safely guide cars along freeways at 70 miles per hour, I wondered, why cant it help caregivers keep up with the chaos of the healthcare environment?

At the heart of this idea was an obstacle, however. I was proposing research that extended beyond the limits of computer science and into an entirely different field, with decades of literature and traditions stretching back generations. It was clear I needed a collaboratornot just an authority in healthcare, but one with the patience and open-mindedness to help an outsider bring something new to the table. For the first time in my career, success would depend on more than the merits of my work; it would require the humility of researchers like me to recognize the boundaries of our knowledge, and the graciousness of experts in another discipline to help us overcome them.

Thankfully, luck was on my side. In 2012, a colleague introduced me to Arnie Milstein, a Stanford Medical School professor and member of the National Academy of Medicine with an interest in both the policy and the technology that drives healthcare. Our first real conversation on the topic turned a casual lunch at a Vietnamese pho restaurant into an impromptu, hours-long brainstorming session. The exuberance of that day never wore off, as we convened a coalition of researchers to explore the automated tracking of surgical tools during operations, privacy-preserving monitors that ensure the safety of high-risk patients and vulnerable seniors, and networks of smart sensors that help hospital staff maintain hand hygiene throughout their shifts. Finally, in September, after years of experimentation, refinements, and presentations at conferences all over the world, our research was published in Nature. And now, with the help of legal scholars, bioethicists, and even a philosopher, were partnering with select hospitals and senior homes to pilot its use in the hands of real caregivers.

The success of my collaboration with Professor Milstein demonstrates an important idea: AIs applications are vast, but technology will represent only part of any given breakthrough. The remainder will be found in the contributionseven leadershipof experts from a growing list of fields, of which healthcare is only one example. Similar partnerships await as AI intersects with economics, energy, environmental science, public health, education, and even the humanities.

For instance, its hard to talk about any application of technology in 2020 without addressing the coronavirus pandemic. This was among the motivating factors behind the launch of AI Cures, an MIT initiative that brings together researchers in machine learning and life sciences to accelerate the speed with which antivirals can be identified, evaluated, and ultimately deployed. Its applications in the face of COVID-19 are obvious, but its broader goal of elevating our defense against pathogens of all kinds will remain relevant long after the challenges of the present moment are behind us. In addition to its core research mission, the group has organized impressively inclusive events in recent months, providing a venue for presenters with backgrounds in computer science, infectious disease, cardiology, synthetic biology, and many others.

Similarly encouraging is the work of my colleague, Stanford law professor Dan Ho. His lab has published extensively on the utility of AI in the public sector, and is now working with the EPA to use machine learning to dramatically improve the tracking of ecological contamination at a national scale. The underlying technology is transformative, but its the involvement of legal scholars, policymakers, and government representatives that truly makes it applicable in the real world.

These stories are a testament to the power of humility, but the sheer scale of the challenges that remain calls for a more organized response. It was with this in mind that I partnered with Stanford professor of philosophy and former provost John Etchemendy to co-found the Stanford Institute for Human-Centered Artificial Intelligence, or HAI, in 2018. Its ongoing mission is to reframe the pursuit of AI in unequivocally human terms, to reflect its dependence on interdisciplinary alliances, and to ensure ethics, compassion, and societal responsibility are baked in from the earliest stages of our workwhether its an algorithm, a commercial product, or even legislation.

HAIs reach as an institution is helping to cross new divides as well, beyond those that separate academic worlds. Partnerships with corporations, governments, and NGOs, for instance, will be essential in building a larger community around these values. Already, for example, theyve helped us organize cross-disciplinary workshops that bring ethical, philosophical, and legal expertise to bear on contentious technologies like facial recognition, with audiences of executives and legislators at both the state and federal level. And our relationships with tech leaders like Google and Amazon allow us to offer powerful cloud computing accessa foundational but often cost-prohibitive resource for modern AI researchto young, innovative thinkers in the form of grants.

Ultimately, however, this appreciation for the power of humilityopenness, transparency, and a reverence for the expertise of otherscant be mandated from the top down. It must be built up from a cultural level, and thus requires an investment in educational efforts to instill them in the next generation of AI practitioners. Here at Stanford, political science professor Rob Reich co-created a course in the computer science department entitled Computers, Ethics and Public Policy, intended to augment the education of engineers with an awareness of their impact on people and communities, while Harvard computer science professor Barbara Grosz explores similar issues in a course called Embedded Ethics. These are encouraging signs of a shift in the way we educate not just tomorrows technologists, but business leaders, social scientists, and politicians. Its my hope that universities across the world will be inspired to follow suit.

The excitement and anxiety surrounding AI can lend it a fatalistic tone, with aggressive language like revolution, tectonic shift, and force for change all too common. But while it might seem inevitable that AI will reshape the world, collaborations like these are a chance for the worldin all its messy, complicated vibrancyto reshape AI in turn. So although Im continually excited by what were learning about intelligent machines, Im even more excited by what we can learn from each other. All it takes is the willingness to ask, and that great, understated strengthour humility.

Dr. Fei-Fei Li is the Sequoia Professor, Computer Science Department, and Denning Codirector, Stanford Institute for Human-Centered Artificial Intelligence, Stanford University. She is an elected Member of the National Academy of Engineering, and the National Academy of Medicine.

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Stanford AI scholar Fei-Fei Li writes about humility in tech - Fast Company