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The Stanford professor and godmother of artificial intelligence on why existential worries are not her priority, and her work to ensure the technology improves the human condition

Fei-Fei Li is a pioneer of modern artificial intelligence (AI). Her work provided a crucial ingredient big data for the deep learning breakthroughs that occurred in the early 2010s. Lis new memoir, The Worlds I See, tells her story of finding her calling at the vanguard of the AI revolution and charts the development of the field from the inside. Li, 47, is a professor of computer science at Stanford University, where she specialises in computer vision. She is also a founding co-director of Stanfords Institute for Human-Centered Artificial Intelligence (HAI), which focuses on AI research, education and policy to improve the human condition, and a founder of the nonprofit AI4ALL, which aims to increase the diversity of people building AI systems.

AI is promising to transform the world in ways that dont necessarily seem for the better: killing jobs, supercharging disinformation and surveillance, and causing harm through biased algorithms. Do you take any responsibility for how AI is being used?First, to be clear, AI is promising nothing. It is people who are promising or not promising. AI is a piece of software. It is made by people, deployed by people and governed by people.

Second, of course I dont take responsibility for how all of AI is being used. Should Maxwell take responsibility for how electricity is used because he developed a set of equations to describe it? But I am a person who has a voice and I feel I have a responsibility to raise important issues which is why I created Stanford HAI. We cannot pretend AI is just a bunch of math equations and thats it. I view AI as a tool. And like other tools our relationship with it is messy. Tools are invented by and large to deliver good but there are unintended consequences and we have to understand and mitigate their risks well.

You were born in China, the only child of a middle-class family that emigrated to the US when you were 15. You faced perilous economic circumstances, your mother was in poor health and you spoke little English. How did you get from there into AI research?You laid out all the challenges, but I was also very fortunate. My parents were supportive: irrespective of our financial situation and our immigrant status, they supported that nerdy sciencey kid. Because of that, I found physics in high school and I was determined to major in it [at university]. Then, also luckily, I was awarded a nearly full scholarship to attend Princeton. There I found fascination in audacious questions around what intelligence is, and what it means for a computational machine to be intelligent. That led me to my PhD studying AI and specifically computer vision.

Your breakthrough contribution to the development of contemporary AI was ImageNet, which first came to fruition in 2009. It was a huge dataset to train and test the efficacy of AI object-recognition algorithms: more than 14m images, scraped from the web, and manually labelled into more than 20,000 noun categories thanks to crowd workers. Where did the idea come from and why was it so important?ImageNet departed from previous thinking because it was built on a very large amount of data, which is exactly what the deep learning family of algorithms [which attempt to mimic the way the human brain signals, but had been dismissed by most as impractical] needed.

The world came to know ImageNet in 2012 when it powered a deep learning neural network algorithm called AlexNet [developed by Geoffrey Hintons group at the University of Toronto]. It was a watershed moment for AI because the combination gave machines reliable visual recognition ability, really for the first time. Today when you look at ChatGPT and large language model breakthroughs, they too are built upon a large amount of data. The lineage of that approach is ImageNet.

Prior to ImageNet, I had created a far smaller dataset. But my idea to massively scale that up was discouraged by most and initially received little interest. It was only when [Hintons] group which had also been relatively overlooked started to use it that the tide turned.

Your mother inspired you to think about the practical applications of AI in caring for patients. Where has that led?Caring for my mom has been my life for decades and one thing Ive come to realise is that between me, the nurses and the doctors we dont have enough help. Theres not enough pairs of eyes. For example, my mom is a cardio patient and you need to be aware of these patients condition in a continuous way. Shes also elderly and at risk of falling. A pillar of my labs research is augmenting the work of human carers with non-invasive smart cameras and smart sensors that use AI to alert and predict.

To what extent do you worry about the existential risk of AI systems that they could gain unanticipated powers and destroy humanity as some high-profile tech leaders and researchers have sounded the alarm about, and which was a large focus of last weeks UK AI Safety Summit?I respect the existential concern. Im not saying it is silly and we should never worry about it. But, in terms of urgency, Im more concerned about ameliorating the risks that are here and now.

Where do you stand on the regulation of AI, which is currently lacking?Policymakers are now engaging in conversation, which is good. But theres a lot of hyperbole and extreme rhetoric on both sides. Whats important is that were nuanced and thoughtful. Whats the balance between regulation and innovation? Are we trying to regulate writing a piece of AI code or [downstream] where the rubber meets the road? Do we create a separate agency, or go through existing ones?

Problems of bias being baked into AI technology have been well documented and ImageNet is no exception. It has been criticised for the use of misogynist, racist, ableist, and judgmental classificatory terms, matching pictures of people to words such as alcoholic, bad person, call girl and worse. How did you feel about your system being called out and how did you address it?The process of making science is a collective one. It is important that it continues to be critiqued and iterated and I welcome honest intellectual discussion. ImageNet is built upon human language. Its backbone is a large lexical database of English called WordNet, created decades ago. And human language contains some harsh unfair terms. Despite the fact that we tried to filter out derogatory terms we did not do the perfect job. And that was why, around 2017, we went back and did more to debias it.

Should we, as some have argued, just outright reject some AI-based technology such as facial recognition in policing because it ends up being too harmful?I think we need nuance, especially about how, specifically, it is being used. I would love for facial recognition technology to be used to augment and improve the work of police in appropriate ways. But we know the algorithms have limitations [racial] bias has been an issue and we shouldnt, intentionally or unintentionally, harm people and especially specific groups. It is a multistakeholder problem.

Disinformation the creation and spread of false news and images is in the spotlight particularly with the Israel-Hamas war. Could AI, which has proved startlingly good at creating fake content, also help combat it?Disinformation is a profound problem and I think we should all be concerned about it. I think AI as a piece of technology could help. One area is in digital authentication of content: whether it is videos, images or written documents, can we find ways to authenticate it using AI? Or ways to watermark AI-generated content so it is distinguishable? AI might be better at calling out disinformation than humans in the future.

What do you think will be the next AI breakthrough?Im passionate about embodied AI [AI-powered robots that can interact with and learn from a physical environment]. It is a few years away, but it is something my lab is working on. I am also looking forward to the applications built upon the large language models of today that can truly be helpful to peoples lives and work. One small but real example is using ChatGPT-like technology to help doctors write medical summaries, which can take a long time and be very mechanical. I hope that any time saved is time back to patients.

Some have called you the godmother or mother of AI how do you feel about that?My own true nature would never give myself such a title. But sometimes you have to take a relative view, and we have so few moments where women are given credit. If I contextualise it this way, I am OK with it. Only I dont want it to be singular: we should recognise more women for their contributions.

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Excerpt from:

AI pioneer Fei-Fei Li: Im more concerned about the risks that are here and now - The Guardian

The Defense Department today released its strategy to accelerate the adoption of advanced artificial intelligence capabilities to ensure U.S. warfighters maintain decision superiority on the battlefield for years to come.

The Pentagon's 2023 Data, Analytics and Artificial Intelligence Adoption Strategy builds upon years of DOD leadership in the development of AI and further solidifies the United States' competitive advantage in fielding the emerging technology, defense officials said.

"As we focused on integrating AI into our operations responsibly and at speed, our main reason for doing so has been straight forward: because it improves our decision advantage," Deputy Defense Secretary Kathleen Hicks said while unveiling the strategy at the Pentagon.

"From the standpoint of deterring and defending against aggression, AI-enabled systems can help accelerate the speed of commanders' decisions and improve the quality and accuracy of those decisions, which can be decisive in deterring a fight and winning in a fight," she said.

The latest blueprint, which was developed by the Chief Digital and AI Office, builds upon and supersedes the 2018 DOD AI Strategy and revised DOD Data Strategy, published in 2020, which have laid the groundwork for the department's approach to fielding AI-enabled capabilities.

The new document aims to provide a foundation from which the DOD can continue to leverage emerging AI capabilities well into the future.

"Technologies evolve. Things are going to change next week, next year, next decade. And what wins today might not win tomorrow," said DOD Chief Digital and AI Officer Craig Martell.

"Rather than identify a handful of AI-enabled warfighting capabilities that will beat our adversaries, our strategy outlines the approach to strengthening the organizational environment within which our people can continuously deploy data analytics and AI capabilities for enduring decision advantage," he said.

The strategy prescribes an agile approach to AI development and application, emphasizing speed of delivery and adoption at scale leading to five specific decision advantage outcomes:

Superior battlespace awareness and understanding

Adaptive force planning and application

Fast, precise and resilient kill chains

Resilient sustainment support

Efficient enterprise business operations

The blueprint also trains the department's focus on several data, analytics and AI-related goals:

Invest in interoperable, federated infrastructure

Advance the data, analytics and AI ecosystem

Expand digital talent management

Improve foundational data management

Deliver capabilities for the enterprise business and joint warfighting impact

Strengthen governance and remove policy barriers

Taken together, those goals will support the "DOD AI Hierarchy of Needs" which the strategy defines as: quality data, governance, insightful analytics and metrics, assurance and responsible AI.

In unveiling the strategy, Hicks emphasized the Pentagon's commitment to safety and responsibility while forging the AI frontier.

"We've worked tirelessly for over a decade to be a global leader in the in the fast and responsible development and use of AI technologies in the military sphere, creating policies appropriate for their specific use," Hicks said. "Safety is critical because unsafe systems are ineffective systems."

In January, the Defense Department updated its 2012 directive that governs the responsible development of autonomous weapon systems to the standards aligned with the advances in artificial intelligence.

The U.S. has also introduced a political declaration on the responsible military use of artificial intelligence, which further seeks to codify norms for the responsible use of the technology.

Hicks said the U.S. will continue to lead in the responsible and ethical use of AI, while remaining mindful of the potential dangers associated with the technology.

"By putting our values first and playing to our strengths, the greatest of which is our people, we've taken a responsible approach to AI that will ensure America continues to come out ahead," she said. "Meanwhile, as commercial tech companies and others continue to push forward the frontiers of AI, we're making sure we stay at the cutting edge with foresight, responsibility and a deep understanding of the broader implications for our nation."

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DOD Releases AI Adoption Strategy > U.S - Department of Defense

LONDON (AP) Chatbots like ChatGPT wowed the world with their ability towrite speeches, plan vacations orhold a conversationas good as or arguably even better than humans do, thanks to cutting-edge artificial intelligence systems. Now, frontier AI has become the latest buzzword as concerns grow that the emerging technology has capabilities that could endanger humanity.

Everyone from the British government to top researchers and even major AI companies themselves are raising the alarm about frontier AIs as-yet-unknown dangers and calling for safeguards to protect people from its existential threats.

The debate comes to a head Wednesday, when British Prime Minister Rishi Sunak hosts a two-day summit focused on frontier AI. Its reportedly expected to draw a group of about 100 officials from 28 countries, including U.S. Vice President Kamala Harris, European Commission President Ursula von der Leyen and executives from key U.S. artificial intelligence companies including OpenAI, Googles Deepmind and Anthropic.

The venue is Bletchley Park, a former top secret base for World War II codebreakers led by Alan Turing. The historic estate is seen as the birthplace of modern computing because it is where Turing and others famously cracked Nazi Germanys codes using the worlds first digital programmable computer.

In a speech last week,Sunak saidonly governments not AI companies can keep people safe from the technologys risks. However, he also noted that the U.K.s approach is not to rush to regulate, even as he outlined a host of scary-sounding threats, such as the use of AI to more easily make chemical or biological weapons.

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Cutting-edge AI raises fears about risks to humanity. Are tech and ... - The Columbian