How Facebook decided to deploy its AI lab when the pandemic hit

There were a lot of ideas from a very enthusiastic team, and they all had to be guided by the gentle hand of the lab's managing director.

COVID-19 forecast at the U.S. county level.

Facebook has built tools that forecast the spread of the COVID-19 at the county level, as shown in this animation.

Image: Facebook

In late February, as coronavirus took hold in Europe, governments around the world were still resisting lockdowns. In Facebook's artificial intelligence lab in Paris, data scientists and machine learning researchers were dumbstruck.

"I mean, they are data nerds, right?" Antoine Bordes, managing director of Facebook AI Research, told Protocol. "There [were] really a lot of people [here], heads down in the data, who knew this [pandemic] was coming."

One researcher, Bordes recalls, skeptical of governmental responses to the pandemic, decided to do some modeling on the weekend using data grabbed from a New York Times COVID-19 tracker. He recalled their response on returning to the office: "Hmm, it doesn't look good."

So those researchers did what researchers do: They dug into the data, they played around and they started working out what could be usefully done. "I mean 60 people, roughly, they dropped what they were doing to start [COVID-19] projects," Bordes said.

"It didn't happen because the firm, the CTO, Mark Zuckerberg [or] me said 'We need to do something about COVID,' you know … it really started from the bottom, with a lot of people saying 'We want to act.'"

Fast forward to today, and Facebook's AI lab has built software that forecasts the spread of COVID-19 at the county level in the U.S., an early version of which was used to predict demand on hospitals in New York during that first peak of cases. It's also developed tools to detect COVID-19 misinformation (or at least some of it; that remains an unfathomably difficult task to automate), as well as identify posts offering or requesting help, so others can more easily connect with the right people via the Facebook Community Hub. And it has bigger plans to continue its forecasting across Europe.

But even at Facebook, the home of moving fast and breaking things, getting to this stage wasn't straightforward. Projects like this can normally take months or years, not weeks, to complete. And the flip side of having a team full of data nerds is that they all have ideas: At least 80 to 90 people provided ideas for projects, Bordes estimated.

He needed to work out how to impose some order on the enthusiasm. And quickly.

"I had a meeting with my boss, Jerome Pesenti, the VP of AI, and a lot of the AI leadership," Bordes said. "And it was [obvious that] OK, two things: First, we feel the pandemic is very serious and we want to do something about it as an organization … we don't know how but we want to do something."

He added: "The second one was: If we don't coordinate, we're going to do small things and nobody's going to have an impact." Even worse, the execs feared that there was the possibility that too many projects might lead to conflicting and contradictory information. "Sometimes you want to help, you want to have a humanitarian action, and actually by coming up with the wrong path, or the wrong way [of doing something], you're actually doing more harm than good," he said.

"I went to the team and I said, 'OK, in the next three days, you're going to come back and propose all the ideas of projects you have,'" Bordes said. At this stage, there was no prioritization: The team just wanted a comprehensive list of what everyone was thinking about and working on — everything from projects assessing the causality of lockdowns on the spread of COVID-19 to algorithms that might help dissuade people from touching their face.

As ideas crystallized into 10 to 15 projects, theme leaders were appointed. ("Some of them made it through, some of them didn't — that's research," Bordes said.) Then, his role became more about liaising with those leaders while finding external partners to work with.

Those kinds of collaborations have been a big deal for the team throughout this process: Bordes says he wouldn't let any of the forecasting work leave the company unless his team had worked with epidemiologists, because Facebook isn't expert in medical sciences. "We don't ever claim we're right," Bordes said.

The process of identifying stronger research themes gradually continued, with the team slowly building larger and larger teams on its areas of focus. The forecasting effort, for example, ultimately wound up being a 10-person team on top of the original researcher: people working on the legal issues of sourcing data, releasing the models as open-source software, liaising with universities, or working on communications. And all the time, the team was trying to "do it in, like, two weeks, not six months," Bordes said.

Perhaps the project the group seems proudest of is its attempt tot predict the spread of the virus. That work is actually based on a research project led by Maximilian Nickel, an AI researcher based in New York, which explores how messages propagate through social graphs. As the pandemic hit, Nickel and his team were working on models that were actually borrowed from epidemiology, so they were able to repurpose their work and use it to predict the spread of the virus in New York and New Jersey "within a couple of weeks," Bordes said.

Then, it was time to check it was actually useful. "We knocked on the doors of the epidemiology labs, and we showed [them] the forecasts, and said, 'OK, is this going to be useful?'" Bordes said. "And the epidemiology team at NYU and Cornell ... they really were impressed by the quality of these forecasts … so they took them and used them in their own epidemiology models." Subsequently, those forecasts were used by New York and New Jersey during the first wave to try to allocate health care resources.

That was six months ago, and the team's kept working since. It's extended its modeling across the entire U.S., forecasting the spread of COVID-19 at the county level at one, two and three weeks out — data it shares on the Humanitarian Data Exchange.

There is, of course, no shortage of COVID-19 predictions: Facebook's is one of many, all based on different data sets and assumptions, all offering slightly different predictions. "As a standalone model, I don't think it's unique," said Youyang Gu, an independent data scientist who has been building his own predictions and tracking those built by others. "But if it leads to more people using [or] accessing the forecasts, then that can lead to beneficial impacts."

Now, Facebook's working in collaboration with the Polytechnic University of Catalonia to do the same thing in Europe, but that's a task made much harder by the fact that European countries all report data in different formats.

Even trickier is the idea of extending the work beyond North America and Europe, where data collection and sharing is far less organized. The team has open-sourced its model, but without the right data, it's hard for Facebook to do much more with these algorithms for some of the most vulnerable nations in the world.

"We wish we could," Bordes said.


Why foundation models in AI need to be released responsibly

Foundation models like GPT-3 and DALL-E are changing AI forever. We urgently need to develop community norms that guarantee research access and help guide the future of AI responsibly.

Releasing new foundation models doesn’t have to be an all or nothing proposition.

Illustration: sorbetto/DigitalVision Vectors

Percy Liang is director of the Center for Research on Foundation Models, a faculty affiliate at the Stanford Institute for Human-Centered AI and an associate professor of Computer Science at Stanford University.

Humans are not very good at forecasting the future, especially when it comes to technology.

Keep Reading Show less
Percy Liang
Percy Liang is Director of the Center for Research on Foundation Models, a Faculty Affiliate at the Stanford Institute for Human-Centered AI, and an Associate Professor of Computer Science at Stanford University.

Every day, millions of us press the “order” button on our favorite coffee store's mobile application: Our chosen brew will be on the counter when we arrive. It’s a personalized, seamless experience that we have all come to expect. What we don’t know is what’s happening behind the scenes. The mobile application is sourcing data from a database that stores information about each customer and what their favorite coffee drinks are. It is also leveraging event-streaming data in real time to ensure the ingredients for your personal coffee are in supply at your local store.

Applications like this power our daily lives, and if they can’t access massive amounts of data stored in a database as well as stream data “in motion” instantaneously, you — and millions of customers — won’t have these in-the-moment experiences.

Keep Reading Show less
Jennifer Goforth Gregory
Jennifer Goforth Gregory has worked in the B2B technology industry for over 20 years. As a freelance writer she writes for top technology brands, including IBM, HPE, Adobe, AT&T, Verizon, Epson, Oracle, Intel and Square. She specializes in a wide range of technology, such as AI, IoT, cloud, cybersecurity, and CX. Jennifer also wrote a bestselling book The Freelance Content Marketing Writer to help other writers launch a high earning freelance business.

The West’s drought could bring about a data center reckoning

When it comes to water use, data centers are the tech industry’s secret water hogs — and they could soon come under increased scrutiny.

Lake Mead, North America's largest artificial reservoir, has dropped to about 1,052 feet above sea level, the lowest it's been since being filled in 1937.

Photo: Mario Tama/Getty Images

The West is parched, and getting more so by the day. Lake Mead — the country’s largest reservoir — is nearing “dead pool” levels, meaning it may soon be too low to flow downstream. The entirety of the Four Corners plus California is mired in megadrought.

Amid this desiccation, hundreds of the country’s data centers use vast amounts of water to hum along. Dozens cluster around major metro centers, including those with mandatory or voluntary water restrictions in place to curtail residential and agricultural use.

Keep Reading Show less
Lisa Martine Jenkins

Lisa Martine Jenkins is a senior reporter at Protocol covering climate. Lisa previously wrote for Morning Consult, Chemical Watch and the Associated Press. Lisa is currently based in Brooklyn, and is originally from the Bay Area. Find her on Twitter ( @l_m_j_) or reach out via email (


Indeed is hiring 4,000 workers despite industry layoffs

Indeed’s new CPO, Priscilla Koranteng, spoke to Protocol about her first 100 days in the role and the changing nature of HR.

"[Y]ou are serving the people. And everything that's happening around us in the world is … impacting their professional lives."

Image: Protocol

Priscilla Koranteng's plans are ambitious. Koranteng, who was appointed chief people officer of Indeed in June, has already enhanced the company’s abortion travel policies and reinforced its goal to hire 4,000 people in 2022.

She’s joined the HR tech company in a time when many other tech companies are enacting layoffs and cutbacks, but said she sees this precarious time as an opportunity for growth companies to really get ahead. Koranteng, who comes from an HR and diversity VP role at Kellogg, is working on embedding her hybrid set of expertise in her new role at Indeed.

Keep Reading Show less
Amber Burton

Amber Burton (@amberbburton) is a reporter at Protocol. Previously, she covered personal finance and diversity in business at The Wall Street Journal. She earned an M.S. in Strategic Communications from Columbia University and B.A. in English and Journalism from Wake Forest University. She lives in North Carolina.


New Jersey could become an ocean energy hub

A first-in-the-nation bill would support wave and tidal energy as a way to meet the Garden State's climate goals.

Technological challenges mean wave and tidal power remain generally more expensive than their other renewable counterparts. But government support could help spur more innovation that brings down cost.

Photo: Jeremy Bishop via Unsplash

Move over, solar and wind. There’s a new kid on the renewable energy block: waves and tides.

Harnessing the ocean’s power is still in its early stages, but the industry is poised for a big legislative boost, with the potential for real investment down the line.

Keep Reading Show less
Lisa Martine Jenkins

Lisa Martine Jenkins is a senior reporter at Protocol covering climate. Lisa previously wrote for Morning Consult, Chemical Watch and the Associated Press. Lisa is currently based in Brooklyn, and is originally from the Bay Area. Find her on Twitter ( @l_m_j_) or reach out via email (

Latest Stories