Gig nursing apps promise flexibility. Nurses, nursing aides, and other medical professionals can log in and, with a push of a button, design their own schedules by bidding on open shifts at nearby hospitals, nursing homes, long-term care residences, and correctional facilities.

Apps such as Clipboard Health, KARE Technologies, Nursa, and ShiftKey operate like Uber or Hinge for nursing, algorithmically filling nursing shifts by matching employers with qualified staff.

But a recent AI Now report by Katie Wells, Maya Pinto, and Funda Ustek Spilda finds that these companies are pulling from the “Uber playbook” in more ways than one, lobbying at least 17 statehouses since 2022. They argue they should be treated as a “healthcare worker platform” rather than a staffing agency, mirroring the rideshare company’s strategy to circumvent government regulations on taxi services. 

It’s a move Wells said is eroding worker protections and misrepresenting the level of control these platforms have over workers.

"The real threat right now is less in terms of displacement of jobs and more in terms of degradation — just really lowering the quality of jobs for the care workers that we need,” Wells said. 

Proof reached out to the app companies for comment on the report. None responded.

A transcript of our conversation, edited for brevity and clarity:

Bansal: Healthcare is supposedly the one part of the economy where jobs were plentiful and safe from AI. My guest Katie Wells is a senior fellow at AI Now Institute where she has come out with a report on gig nursing apps. Think Uber for nursing. It's a world where nurses are gig workers who don't know where or when they will be clocking in next week. Welcome, Katie. 

Wells: I'm so glad we're having this conversation. I also am worried about what the future of healthcare looks like with these kinds of apps at the helm. 

So the easiest way to think about this new kind of business which really emerged in post recession around 2016 is that they are a platform that lives on your phone that seeks to create a magical match between understaffed healthcare facilities and nurses who are looking for work. And what these apps do is matchmaking. They're the OKCupid or the Hinge or the Bumble and they create a match between these two entities.

But the problem with this match is it's a really consequential one and it's one done with very little human intermediation. And so what it means is that if Varsha you or I were to sign up, we would never be interviewed by a human. We would sign up as a nurse or nursing assistant or a radiology tech or a dental assistant and we would just be able to indicate our interest in a shift and on some apps we would be bidding on them. We see this kind of app, these gig nursing apps, we see them in hospitals, public and private. We see them in long-term care facilities. We see them recently in some schools. We see them in correctional facilities. And there have been reports that they are being used to staff some ICE facilities. 

Bansal: When you say ICE facilities, does that mean that these nurses are being chosen from these apps? Specifically, are they being trained to work at ICE facilities? 

Wells: That's a great question. We have no information about whether these ICE facilities, that we've heard reports of in Texas and Minnesota, are specifically training these nurses to work in their facilities. If we go through patterns when nurses or nursing assistants work through these apps at correctional facilities — at jails and prisons — we know that they are not given additional paid training. For many of these workers, they go into facilities not having an orientation.

Now, some facilities do require it, but these apps don't require it. So, if it's up to a facility to choose, and then when nurses get somewhere, they often don't know where the supply closet is or how to log into a patient portal. One thing I remember from talking to nurses in the course of this work is one nurse said to us and this sticks with me a lot: “I just feel like I'm on an island by myself.”

Bansal: That's not a great feeling when you're supposed to be caregiving to other people who are in need of that. So that sounds horrible. You have described AI as creating a mass degradation of work in your report. What do you mean by that and what does that really look like for nurses? You gave us a picture, but can you go deeper into that?

Wells: So, one of the things about these gig nursing apps is that they are powered by AI technologies that they're using automated decision-making to allocate shifts and allocate wages. And when we think about AI … every time I open up the newspaper, there's talk about this mass displacement that could arrive.

And what this work around AI and healthcare has shown me is that oh my goodness right now there already are huge threats to healthcare but it's less in terms of displacement of jobs and more in terms of the degradation about just really lowering the quality of jobs for the care workers that we need. The reality for many of these gig nursing apps is that they encourage nurses and nursing assistants or dental assistants or radiology text to bid against each other in a wage auction. 

And so a question that I have as a researcher is well who makes that final decision about how low a facility is willing to accept a wage? If someone, you know, bids $3 an hour, would that be possible? Many of these apps don't allow that. There are bans. But I don't know who is setting that base rate. Is it the facility and or is it possible it's the algorithm? And when I say the algorithm, I really just mean the gig nursing company. 

Bansal: You write that there is a nationwide effort going on to deregulate nursing.

Wells: Laws have been proposed in dozens of states to carve out nursing from worker protections. Gig nursing companies are really following Uber's playbook from 2012. Uber went city by city and state by state to argue in the US that it was not a chauffeur service. It was not a taxi company and so it should not be regulated as taxi companies are. What gig nursing companies are doing is this very same playbook. They are going state by state and at these state houses telling legislators, “Oh, we're not a healthcare staffing agency. That's not what we do. And so, we cannot possibly be regulated as healthcare staffing agencies. Instead, we need a new term, a new business category. We should call ourselves a healthcare worker platform or healthcare technology platform.”

Bansal: Even though they are staffing health care workers in facilities and hospitals.

Wells: Yes. But you know Uber made the argument. Uber won. Uber has carveouts in 34 states.  

Bansal: What kind of an impact does this have overall on nurses, on patients?

Wells: We are very much worried about the impacts on patient care. We know from recent studies about even unionized versus non-unionized nursing homes that the mortality rates and the patient fall rates increase when workers are not unionized. So I can only imagine and I'm guessing here that the patient care concerns and the risks are going to increase when workers are not employees of a facility but instead are just day workers that come in without any formal relationship with a facility or patients.

Bansal: Thank you so much, Katie. I really appreciate you coming here and sharing all of this knowledge with us about gig nursing. Before I end, I'll remind you all that I'm reporting on these apps and want to hear from you. You can find me at proofnews.org. And while you're there, check out all our coverage about AI automation and work. Thank you.