already-full workloads for our caregivers— NLP can support the easy recording of medical/health related conversation and reporting,” Rosenbaum says. “Combined with machine learning and

predictive analytics—the key AI functions within Arena's realm of expertise—medical records can become highly organized and recommendations and insights for care can be surfaced.” Arena uses NLP, predictive analytics

techniques, and a variety of machine learning processes to help senior living operators match staff members to specific roles, such as working in particular parts of a building or certain shifts. The solution can point to “where they are most likely to produce the care and quality outcomes that the provider deems most important,” Rosenbaum says. “Arena continually collects and analyzes

data from the world and combines it with data from providers, job applicants and new hires and then uses AI tools to identify patterns related to the outcomes achieved by hires, following them anywhere from months to years, depending on the client.”

they are experiencing burnout or struggling to cope with a resident’s behaviors, before it gets to a point where they’re badly stressed or overwhelmed. “We are looking at ways that we can use

machine learning and artificial intelligence to spot those things long before anybody could ever otherwise see them coming,” Keefe says. “That way we can help a provider maybe

do some interventions with the caregiver to help them overcome whatever challenges they’re facing or maybe better pair residents with caregivers to make a more compatible match.”

Misconceptions and obstacles Paprocki says some misconceptions about AI still persist, partly because of its often-dystopian depiction in movies and TV shows. That can make for good entertainment, but it tends to overshadow “the amazing possibilities for AI to have a deeply positive impact on our world.” And it is clear people are growing more comfortable with the technology and its possibilities.

Electronic health records can end up being more of a burden to caregivers, but natural language processing, NLP, can make recording and tracking health data easier, says Michael Rosenbaum, Arena CEO.

Keeping up with changes When circumstances change, patterns change, Rosenbaum says, and Arena then makes matches in real time to the roles and locations for workers that will be best for those circumstances. Similarly, Keefe says AI solutions such as

MatrixCare’s can help identify otherwise hidden problems individual caregivers might be having and prompt crucial interventions. For instance, AI can be used to analyze

the language that a caregiver enters into their documentation that could indicate

“There are already awesome examples

of AI playing out right now spanning environmental preservation to discovering the medicines of the future to improving access to education,” Paprocki says. “But getting past the misconceptions

of anything new takes time, accumulated familiarity, and appreciable benefits.” Netscher says he believes AI’s short-term

capabilities are often overestimated and its long-term capabilities are underestimated. “I see lots of misconceptions about what

AI is really capable of,” Netscher says. “We're really building software today that


can identify complex patterns and not building anything that looks or feels like common sense. “I do think those misconceptions are

going away as folks just interact with more and more AI on a daily basis. From things like Amazon Alexa to the spam filter for your inbox, you start to get a sense for how these kinds of systems make decisions and get more comfortable with them. It's fundamentally just hard to trust something when you don't know exactly what


capable of.” Paprocki says obstacles

still exist

to limit AI’s impact on senior living, particularly limited data, insufficient Wi-Fi infrastructure and disparate technology systems within buildings and across operators’ communities.

Platforms and privacy “The thorniest and most persistent problem will be the lack of a common platform to ingest, make sense of, and make use of all of the data and insights we collectively generate,” Paprocki says. “Put simply, unless we find a way to make

these insights easily understood and clearly actionable, AI will always be limited in its impact.” Keefe says senior living providers can

have a natural resistance to using AI tools founded on concerns tied to privacy, and she says it is essential for them to ask questions of software providers to ensure that privacy is not being overlooked. In addition, operators and software

providers should ensure that their tools do not act as accidental restraints on residents, making them feel so monitored and watched that they become reluctant to move and behave the way they would like to live. She says many providers have shared

their belief over the years that residents are either not tech savvy or are uncomfortable with tech tools. “During the last nine months or so with

the pandemic, we’ve seen that actually the opposite is true,” Keefe says. “Residents have been very willing to adopt some of these technologies. I think the pandemic has opened eyes to the fact that seniors really are willing to utilize these tools.”

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