![caregiver and man looking at smartphone](https://www.mcknightsseniorliving.com/wp-content/uploads/sites/3/2023/11/Focuson2_1440X810-1024x576.jpg)
Artificial intelligence is everywhere.
AI promises to create untold efficiencies and, in turn, solutions to so many thorny issues of workforce, care and operations.
Still, caution with this emerging tool is advised, experts say.
“AI is not new,” says Majd Alwan, PhD, chief strategy and growth officer for ThriveWell Tech. “Alan Turing, a computer scientist who is considered the ‘godfather’ of AI, devised what is known as the Turing Test in 1950, which asks, ‘Can a computer convince a human they’re communicating with another human?’”
Recent examples of innovation at work:
- Certainty-based location visibility, which Deric Blattenberger, general manager of senior care for CenTrak, describes as “enterprise visibility with location certainty,” supported by real-time location systems through wearable pendants.
- CarePredict has developed a continuous activity and behavior observation platform that uses AI to learn correlations between particular changes in activity and behaviors and labeled health events, says Satish Movva, the company’s CEO and founder.
Alwan asserts that the “deep learning” promises of AI in senior living and other long-term care settings seem endless — everything from falls detection and medication management to early detection of pressure ulcers.
“AI can play a significant role in early identification of risk,” notes TK King, vice president of healthcare strategy for Accushield. “Its ability to scan data, search for keywords and evaluate trends means it can pinpoint staffing needs and resident risks.”
Still, healthcare experts agree, many issues surrounding risk need to be tested.
Movva urges early adopters to be mindful of privacy and security concerns. And Blattenberger warns of a risky upcoming phase that introduces virtual caregivers and “approximate” outcomes.
Alwan describes current efforts as a significantly acceleration and competitive “race” and warns adopters to protect data from corruption or premature release.
He’s also adamant about ensuring that humans remain in charge of testing and evaluation.