From the 'godfathers of AI' to newer people in the field: Here are 17 people you should know — and what they say about the possibilities and dangers of the technology.

Hinton's research has primarily focused on neural networks, systems that learn skills by analyzing data. In 2018, he won the Turing Award, a prestigious computer science prize, along with fellow researchers Yann LeCun and Yoshua Bengio.

Hinton also worked at Google for over a decade, but quit his role at Google last spring, so he could speak more freely about the rapid development of AI technology, he said. After quitting, he even said that a part of him regrets the role he played in advancing the technology. 

"I console myself with the normal excuse: If I hadn't done it, somebody else would have. It is hard to see how you can prevent the bad actors from using it for bad things," Hinton said previously. 

Hinton has since become an outspoken advocate for AI safety and has called it a more urgent risk than climate change. He's also signed a statement about pausing AI developments for six months. 

Yoshua Bengio also earned the "godfather of AI" nickname after winning the Turing Award with Geoffrey Hinton and Yann LeCun.

Bengio's research primarily focuses on artificial neural networks, deep learning, and machine learning. In 2022, Bengio became the computer scientist with the highest h-index — a metric for evaluating the cumulative impact of an author's scholarly output — in the world, according to his website. 

In addition to his academic work, Bengio also co-founded Element AI, a startup that develops AI software solutions for businesses that was acquired by the cloud company ServiceNow in 2020. 

Bengio has expressed concern about the rapid development of AI. He was one of 33,000 people who signed an open letter calling for a six-month pause on AI development. Hinton, Open AI CEO Sam Altman, and Elon Musk also signed the letter.

"Today's systems are not anywhere close to posing an existential risk," he previously said. "But in one, two, five years? There is too much uncertainty."

When that time comes, though, Bengio warns that we should also be wary of humans who have control of the technology.

Some people with "a lot of power" may want to replace humanity with machines, Bengio said at the One Young World Summit in Montreal. "Having systems that know more than most people can be dangerous in the wrong hands and create more instability at a geopolitical level, for example, or terrorism."

Altman was already a well-known name in Silicon Valley long before, having served as the president of the startup accelerator Y-Combinator 

While Altman has advocated for the benefits of AI, calling it the most tremendous "leap forward in quality of life for people" he's also spoken candidly about the risks it poses to humanity. He's testified before Congress to discuss AI regulation.

Altman has also said he loses sleep over the potential dangers of ChatGPT.

LeCun is professor at New York University, and also joined Meta in 2013, where he's now the Chief AI Scientist. At Meta, he has pioneered research on training machines to make predictions based on videos of everyday events as a way to enable them with a form of common sense. The idea being that humans learn an incredible amount about the world based on passive observation. He's has also published more than 180 technical papers and book chapters on topics ranging from machine learning to computer vision to neural networks, according to personal website.

LeCun has remained relatively mellow about societal risks of AI in comparison to his fellow godfathers. He's previously said that concerns that the technology could pose a threat to humanity are "preposterously ridiculous". He's also contended that AI, like ChatGPT, that's been trained on large language models still isn't as smart as dogs or cats.

Li's research focuses on machine learning, deep learning, computer vision, and cognitively-inspired AI, according to her biography on Stanford's website.

She may be best known for establishing ImageNet — a large visual database that was designed for research in visual object recognition — and the corresponding ImageNet challenge, in which software programs compete to correctly classify objects.  Over the years, she's also been affiliated with major tech companies including Google — where she was a VP and chief scientist for AI and machine learning — and Twitter (now X), where she was on the board of directors from 2020 until Elon Musk's takeover in 2022. 

Russell published Human Compatible in 2019, where he explored questions of how humans and machines could co-exist, as machines become smarter by the day. Russell contended that the answer was in designing machines that were uncertain about human preferences, so they wouldn't pursue their own goals above those of humans. 

He's also the author of foundational texts in the field, including the widely used textbook "Artificial Intelligence: A Modern Approach," which he co-wrote with former UC-Berkeley faculty member Peter Norvig. 

Russell has spoken openly about what the rapid development of AI systems means for society as a whole. Last June, he also warned that AI tools like ChatGPT were "starting to hit a brick wall" in terms of how much text there was left for them to ingest. He also said that the advancements in AI could spell the end of the traditional classroom. 

He spent several in the early 2000s directing the company's core search algorithms group and later moved into a role as the director of research where he oversaw teams on machine translation, speech recognition, and computer vision. 

Norvig has also rotated through several academic institutions over the years as a former faculty member at UC-Berkeley, former professor at the University of Southern California, and now, a fellow at Stanford's center for Human-Centered Artificial Intelligence. 

Norvig told BI by email that "AI research is at a very exciting moment, when we are beginning to see models that can perform well (but not perfectly) on a wide variety of general tasks." At the same time "there is a danger that these powerful AI models can be used maliciously by unscrupulous people to spread disinformation rather than information. An important area of current research is to defend against such attacks," he said. 

Gebru was a research scientist and the technical co-lead of Google's Ethical Artificial Intelligence team where she published groundbreaking research on biases in machine learning.

But her research also spun into a larger controversy that she's said ultimately led to her being let go from Google in 2020. Google didn't comment at the time.

Gebru founded the Distributed AI Research Institute in 2021 which bills itself as a "space for independent, community-rooted AI research, free from Big Tech's pervasive influence."

She's also warned that AI gold rush will mean companies may neglect implementing necessary guardrails around the technology. "Unless there is external pressure to do something different, companies are not just going to self-regulate," Gebru previously said. "We need regulation and we need something better than just a profit motive."

The endeavor lead to the Google Cat Project: A milestone in deep learning research in which a massive neural network was trained to detect YouTube videos of cats.

Ng also served as the chief scientist at Chinese technology company Baidu where drove AI strategy. Over the course of his career, he's authored more than 200 research papers on topics ranging from machine learning to robotics, according to his personal website. 

Beyond his own research, Ng has pioneered developments in online education. He co-founded Coursera along with computer scientist Daphne Koller in 2012, and five years later, founded the education technology company DeepLearning.AI, which has created AI programs on Coursera.  

"I think AI does have risk. There is bias, fairness, concentration of power, amplifying toxic speech, generating toxic speech, job displacement. There are real risks," he told Bloomberg Technology last May. However, he said he's not convinced that AI will pose some sort of existential risk to humanity — it's more likely to be part of the solution. "If you want humanity to survive and thrive for the next thousand years, I would much rather make AI go faster to help us solve these problems rather than slow AI down," Ng told Bloomberg. 

Koller told BI by email that insitro is applying AI and machine learning to advance understanding of "human disease biology and identify meaningful therapeutic interventions." And before founding insitro, Koller was the chief computing officer at Calico, Google's life-extension spinoff. Koller is a decorated academic, a MacArthur Fellow, and author of more than 300 publications with an h-index of over 145, according to her biography from the Broad Institute, and co-founder of Coursera.  

In Koller's view the biggest risks that AI development pose to society are "the expected reduction in demand for certain job categories; the further fraying of "truth" due to the increasing challenge in being able to distinguish real from fake; and the way in which AI enables people to do bad things."

At the same time, she said the benefits are too many and too large to note. "AI will accelerate science, personalize education, help identify new therapeutic interventions, and many more," Koller wrote by email.

Amodei co-founded Anthropic along with six other OpenAI employees, including her brother Dario Amodei. They left, in part, because Dario — OpenAI's lead safety researcher at the time — was concerned that OpenAI's deal with Microsoft would force it to release products too quickly, and without proper guardrails. 

At Anthropic, Amodei is focused on ensuring trust and safety. The company's chatbot Claude bills itself as an easier-to-use alternative that OpenAI's ChatGPT, and is already being implemented by companies like Quora and Notion. Anthropic relies on what it calls a "Triple H" framework in its research. That stands for Helpful, Honest, and Harmless. That means it relies on human input when training its models, including constitutional AI, in which a customer outlines basic principles on how AI should operate. 

"We all have to simultaneously be looking at the problems of today and really thinking about how to make tractable progress on them while also having an eye on the future of problems that are coming down the pike," Amodei previously told BI.

Hassabis, a former child chess prodigy who studied at Cambridge and University College London, was nicknamed the "superhero of artificial intelligence" by The Guardian back in 2016. 

After a handful of research stints, and a venture in videogames, he founded DeepMind in 2010. He sold the AI lab to Google in 2014 for £400 million where he's worked on algorithms to tackle issues in healthcare, climate change, and also launched a research unit dedicated to the understanding the ethical and social impact of AI in 2017, according to DeepMind's website. 

Hassabis has said the promise of artificial general intelligence — a theoretical concept that sees AI matching the cognitive abilities of humans — is around the corner. "I think we'll have very capable, very general systems in the next few years," Hassabis said previously, adding that he didn't see why AI progress would slow down anytime soon. He added, however, that developing AGI should be executed in a "in a cautious manner using the scientific method." 

The startup, which claims to create "a personal AI for everyone," most recently raised $1.3 billion in funding last June, according to PitchBook. 

Its chatbot, Pi, which stands for personal intelligence, is trained on large language models similar to OpenAI's ChatGPT or Bard. Pi, however, is designed to be more conversational, and offer emotional support. Suleyman previously described it as a "neutral listener" that can respond to real-life problems. 

"Many people feel like they just want to be heard, and they just want a tool that reflects back what they said to demonstrate they have actually been heard," Suleyman previously said. 

Crawford is also the senior principal researcher at Microsoft, and the author of Atlas of AI, a book that draws upon the breadth of her research to uncover how AI is shaping society. 

Crawford remains both optimistic and cautious about the state of AI development. She told BI by email she's excited about the people she works with across the world "who are committed to more sustainable, consent-based, and equitable approaches to using generative AI."

She added, however, that "if we don't approach AI development with care and caution, and without the right regulatory safeguards, it could produce extreme concentrations of power, with dangerously anti-democratic effects."

Mitchell has published more than 100 papers over the course of her career, according to her website, and spearheaded AI projects across various big tech companies including Microsoft and Google. 

In late 2020, Mitchell and Timnit Gebru — then the co-lead of Google's ethical artificial intelligence — published a paper on the dangers of large language models. The paper spurred disagreements between the researchers and Google's management and ultimately lead to Gebru's departure from the company in December 2020. Mitchell was terminated by Google just two months later, in February 2021

Now, at Hugging Face — an open-source data science and machine learning platform that was founded in 2016 — she's thinking about how to democratize access to the tools necessary to building and deploying large-scale AI models.  

In an interview with Morning Brew, where Mitchell explained what it means to design responsible AI, she said, "I started on my path toward working on what's now called AI in 2004, specifically with an interest in aligning AI closer to human behavior. Over time, that's evolved to become less about mimicking humans and more about accounting for human behavior and working with humans in assistive and augmentative ways."

Credo AI is a platform that helps companies make sure they're in compliance with the growing body of regulations around AI usage. In a statement to BI, Singh said that by automating the systems that shape our lives, AI has the capacity "free us to realize our potential in every area where it's implemented."

At the same time, she contends that algorithms right now lack the human judgement that's necessary to adapt to a changing world. "As we integrate AI into civilization's fundamental infrastructure, these tradeoffs take on existential implications," Singh wrote. "As we forge ahead, the responsibility to harmonize human values and ingenuity with algorithmic precision is non-negotiable. Responsible AI governance is paramount."

Socher believes we have ways to go before AI development hits its peak or matches anything close to human intelligence.

One bottleneck in large language models is their tendency to hallucinate — a phenomenon where they convincingly spit out factual errors as truth. But by forcing them to translate questions into code — essential "program" responses instead of verbalizing them — we can "give them so much more fuel for the next few years in terms of what they can do," Socher said. 

But that's just a short-term goal. Socher contends that we are years from anything close to the industry's ambitious bid to create artificial general intelligence. Socher defines it as "a form of intelligence that can "learn like humans" and "visually have the same motor intelligence, and visual intelligence, language intelligence, and logical intelligence as some of the most logical people," and it could take as little as 10 years, but as much as 200 years to get there. 

And if we really want to move the needle toward AGI, Socher said humans might need to let go of the reins, and their own motives to turn a profit, and build AI that can set its own goals.

"I think it's an important part of intelligence to not just robotically, mechanically, do the same thing over and over that you're told to do. I think we would not call an entity very intelligent if all it can do is exactly what is programmed as its goal," he told BI.