‘Boring A.I.’ may be the real lifesaver in this pandemic

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A lot of attention is being given to the role that artificial intelligence can play in helping to combat the coronavirus pandemic.
Much of it been focused on areas with a high degree of what, for lack of a better term,  I’ll call sex appeal: A.I. that can spot and track emerging epidemics; A.I. that can help with contact tracing and social-distancing enforcement; A.I. that can possibly help diagnose COVID-19; and, perhaps most importantly, A.I. that might find possible treatments or vaccines.
Last week, Stanford University’s Institute for Human-Centered Artificial Intelligence held a virtual conference in which researchers discussed many of these uses of A.I. (If you didn’t catch the live broadcast, I highly recommend watching the recorded version here.)
This is all important and potentially game changing. And I don’t want to belittle the work of these researchers and companies in any way. But much of the technology is relatively immature and unproven. It will likely take time to validate and perfect. A lot of these machine learning techniques will probably be more helpful in ensuring we can beat the next emerging epidemic than in fighting this one.
If you want to know where A.I. might be able to have the biggest impact in the battle against coronavirus, it might be wiser to look at some uses of the technology that are more mundane and, frankly, boring.
To show you what I mean, I want to tell you just a little bit about my wife. After having spent the better part of two decades in the diplomatic service, she recently retrained as a medical doctor. She’s now a junior doctor here in London, and she’s working, like most of her colleagues, on the front lines of this pandemic. Last week, she worked three consecutive overnight shifts in her hospital’s intensive care unit.

What is one of the biggest challenges her hospital has faced? Scheduling.

Rostering medical staff—“doing the rota” in the parlance of the British National Health Service—is a big administrative hassle even in normal times. Most British hospitals employ a small cadre of administrators whose sole job is to perform this thankless task, usually using an array of Excel spreadsheets. (U.K. hospitals are notoriously behind-the-times when it comes to administrative I.T.)
 
During the current crisis, scheduling has become monumentally more complex: Staff are moved off their usual assignments so they can work in emergency departments and intensive care units, routine elective surgeries have been cancelled, leaves have been curtailed, shift times have been extended from 8 hours to 12 hours, final-year medical students, graduated early, have been drafted in to help fill staffing gaps, and a large number of workers are absent on any given day because they are ill themselves or are self-isolating because a member of their household is sick. Some British hospitals have reported absence rates as high as 30%.
On top of all this, here in the U.K., the government has been asking retired doctors and nurses to return to active service. So far, more than 11,000 of them have answered that call. The government has said it also wants to recruit 250,000 volunteers, from all walks of life, to help support the NHS and other vital services during the crisis.
Figuring how best to deploy these volunteers alongside regular staff is a colossal job. But, it turns out, A.I. is ideally suited to help—and the technology has already proved its mettle in the corporate world.
Last week, I spent some time chatting with Helge Bjorland and Jan Kristiansen, two co-founders of Globus.AI, a startup that has created software for exactly this purpose. The company, founded in Oslo in 2017 by four friends who had worked together in Norway’s oil sector, helps companies across industries find the right workers to fill shifts.
Among Globus’s customers is Scandinavian medical staffing company Dedicare. Globus helps the company match doctors and nurses with shifts in private hospitals. The software was handling about 4,500 shifts per week, Kristiansen, Globus’s chief operating officer, says.
When the coronavirus pandemic began spreading, Globus realized it might be able to help, says Bjorland, the company’s CEO. Globus tweaked its software and offered it for free to Norway’s public hospitals. The software allows a hospital to match healthcare workers’ competencies to its needs and to align doctors’ availability with open shifts.
The software, Kristiansen says, saves about 90% of the time it takes to fill each available slot, saving a rota manager between two and four hours every day. What’s more, because it can more efficiently match staff to slots, hospitals find their allocation capacity actually increasing between 30% and 40%. And it only takes an administrator about an hour, he says, to learn to use the software.
The technology is not that fancy—though Globus uses natural language processing to extract some information and deep learning to do some matching of candidates’ competencies to jobs, it also uses much simpler machine learning techniques, like logistical regression, to help fill available time slots. And it incorporates some good old-fashioned rules to take into account legal requirements, such as those that limit the number of hours doctors and nurses can work in one stretch, or hospital policies, like the need for at least one senior doctor to be rostered on to each shift to supervise more junior staff.
So far, the system has been deployed in Oslo and Sola, another Norwegian city. Ernst & Young, with which Globus has a partnership, is helping the company roll the system out to public hospitals elsewhere in the country.
But Globus wants to help hospitals and healthcare organizations around the world. “The main thing for us is having the word out to let other countries know that we have actually have something that can help them,” Kristiansen says.
If I had to bet, it will be simple uses of A.I. such as this that wind up being the real life-saver in this pandemic.
And now here’s the rest of this week’s news in A.I.

Jeremy Kahn
jeremy.kahn@fortune.com
@jeremyakahn

This story was originally featured on Fortune.com