Artificial Intelligence Could Help Solve America's Impending Mental Health Crisis
Artificial Intelligence Could Help Solve America's Impending Mental
Health Crisis
BY JAMIE DUCHARME NOVEMBER 20,
2019
Five years from now,
the U.S.’ already overburdened mental health system may be short as many as
15,600 psychiatrists as the growth in demand for their services outpaces
supply, according to a
2017 report from the National Council for Behavioral Health. But some
proponents say that, by then, an unlikely tool—artificial intelligence—may be
ready to help mental health practitioners mitigate the impact of the deficit.
Medicine is already a fruitful area for
artificial intelligence; it has shown promise in diagnosing disease, interpreting images and
zeroing in on treatment plans. Though psychiatry is in many ways a uniquely
human field, requiring emotional intelligence and perception that computers
can’t simulate, even here, experts say, AI could have an impact. The field,
they argue, could benefit from artificial intelligence’s ability to analyze
data and pick up on patterns and warning signs so subtle humans might never
notice them. “Clinicians actually get very little time to interact with
patients,” says Peter Foltz, a research professor at the University of Colorado
Boulder who this month published a
paper about AI’s promise in psychiatry. “Patients tend to be remote,
it’s very hard to get appointments and oftentimes they may be seen by a
clinician [only] once every three months or six months.”
AI could be an effective way for clinicians to both make the best of the
time they do have with patients, and bridge any gaps in access, Foltz says.
AI-aided data analysis could help clinicians make diagnoses more quickly and
accurately, getting patients on the right course of treatment faster—but
perhaps more excitingly, Foltz says, apps or other programs that incorporate AI
could allow clinicians to monitor their patients remotely, alerting them to
issues or changes that arise between appointments and helping them incorporate
that knowledge into treatment plans. That information could be lifesaving, since research has shown that
regularly checking in with patients who are suicidal or in mental distress can
keep them safe.
Some mental-health apps and programs already incorporate AI—like Woebot, an app-based mood
tracker and chatbot that combines AI and principles from cognitive behavioral
therapy—but it’ll probably be some five to 10 years before algorithms are
routinely used in clinics, according to psychiatrists interviewed by TIME. Even
then, Dr. John Torous, director of digital psychiatry at Beth Israel Deaconess
Medical Center in Boston and chair of the American Psychiatric Association’s
Committee on Mental Health Information Technology, cautions that “artificial
intelligence is only as strong as the data it’s trained on,” and, he says,
mental health diagnostics have not been quantified well enough to program an
algorithm. It’s possible that will happen in the future, with more and larger
psychological studies, but, Torous says “it’s going to be an uphill challenge.”
Not everyone shares that position. Speech and
language have emerged as two of the clearest applications for AI in psychiatry,
says Dr. Henry Nasrallah, a psychiatrist at the University of Cincinnati
Medical Center who has written about AI’s place in the field. Speech and mental
health are closely linked, he explains. Talking in a monotone can be a sign of
depression; fast speech can point to mania; and disjointed word choice can be
connected to schizophrenia. When these traits are pronounced enough, a human
clinician might pick up on them—but AI algorithms, Nasrallah says, could be
trained to flag signals and patterns too subtle for humans to detect.
Foltz and his team in Boulder are working in this space, as are big-name
companies like
IBM. Foltz and his colleagues designed a mobile app that takes
patients through a series of repeatable verbal exercises, like telling a story
and answering questions about their emotional state. An AI system then assesses
those soundbites for signs of mental distress, both by analyzing how they
compare to the individual’s previous responses, and by measuring the clips
against responses from a larger patient population. The team tested the system
on 225 people living in either Northern Norway or rural Louisiana—two places
with inadequate access to mental health care—and found that the app was at
least as accurate as clinicians at picking up on speech-based signs of mental
distress.
Written language is also a promising area for
AI-assisted mental health care, Nasrallah says. Studies have shown that
machine learning algorithms trained to assess word choice and order are better
than clinicians at distinguishing between real and fake suicide notes, meaning
they’re good at picking up on signs of distress. Using these systems to
regularly monitor a patient’s writing, perhaps through an app or periodic
remote check-in with mental health professionals, could feasibly offer a way to
assess their risk of self-harm.
Even if these applications do pan out, Torous
cautions that “nothing has ever been a panacea.” On one hand, he says, it’s
exciting that technology is being pitched as a solution to problems that have
long plagued the mental health field; but, on the other hand, “in some ways
there’s so much desperation to make improvements to mental health that perhaps
the tools are getting overvalued.”
Nasrallah and Foltz emphasize that AI isn’t
meant to replace human psychiatrists or completely reinvent the wheel. (“Our
brain is a better computer than any AI,” Nasrallah says.) Instead, they say, it
can provide data and insights that will streamline treatment.
Alastair Denniston, an ophthalmologist and
honorary professor at the U.K.’s University of Birmingham who this year published
a research review about AI’s ability to diagnose disease,
argues that, if anything, technology can help doctors focus on the human
elements of medicine, rather than getting bogged down in the minutiae of
diagnosis and data collection.
Artificial intelligence “may allow us to have
more time in our day to spend actually communicating effectively and being more
human,” Denniston says. “Rather than being diagnostic machines… [doctors can]
provide some of that empathy that can get swallowed up by the business of what
we do.”
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