Can Artificial Intelligence Predict Loneliness and Inspire Care for the Elderly?

One of
the most significant worries seniors express when they live alone is that they
might fall over in their home, and no one will even realize it. AI-powered
devices that can predict and prevent falls are evolving every day. This might
present seniors with the self-confidence to leave the house, instead of fearing
to fall and being a prisoner at home.

have applied artificial intelligence to predict loneliness in tenants at a
senior housing community accurately. Publishing in the American Journal of
Psychiatryresearchers could embrace the power of natural
language processing (NLP) and machine learning models to analyze speech
sentiments and emotions.

the coronavirus pandemic is pushing people towards social isolation, this study
could prove critical in serving the society to evaluate and address widespread
loneliness. Nevertheless, while technology provides ever-more-potent ways of
recognizing societal issues like loneliness, it remains uncertain whether
technology alone can resolve such concerns related to senior citizens and COVID
19 pandemic.

For the
study’s objectives, the researchers questioned nearly 80 tenants, and they
asked questions intended to measure several aspects of loneliness, with the
answers being deciphered and then analyzed through “expressed emotions and
quantify sentiment.”

Analyzing Loneliness

analytic approaches work by scanning for the frequency of phrases and words
used in responses and giving scores for the sentiment (-1.0 to 1.0) and emotion
(0.0 to 1.0). The scores given by AI in the research were analyzed against
manual assessments to evaluate their efficiency.

In their
discussion of the outcomes, the researchers observed that the machine learning
models they employed were surprisingly accurate. These models could foretell
qualitative loneliness with nearly 94% accuracy and quantitative loneliness
with nearly 76% precision.

Implications of AI for the Future

other words, AI in research is almost as good as certified clinicians in
predicting isolation. As the authors state, in conclusion, this could have
significant implications for the future: “NLP and machine learning models
can be scaled up to manage thousands of interviews and can present consistent
ratings that might not be feasible with human raters.”

authors also envisioned a future situation where artificial intelligence-driven
services could prove helpful to individuals, without any direct involvement of
humans. Ultimately, complicated AI-based systems could intervene in real-time
to help individuals reduce their loneliness by managing social stress, adopting
positive cognitions, and engaging in meaningful social activities.

while AI in research certainly has a future in the large-scale discovery of
loneliness (and other emotional states) in citizens and populations, it’s
debatable whether it can be a meaningful part of the remedy.

Shortcomings of AI Technology

research paper affirms that the overall rate of loneliness among participants
was nearly 45%, with numerous reporting a shortage of instrumental and
emotional support. This lack isn’t something that AI-driven systems can solve.
Indeed, loneliness is a fundamentally social concern, and it can only be
resolved with social solutions and transformations.

put, it’s excellent that AI in research could theoretically recognize every
single isolated or lonely person on the planet. But what can a tech-driven
approach do to overcome such isolation? The answer is “minimal,”
though it could be debated.

point is critical as we all frequently see technological innovations in mental
health examinations–or physiological health examinations–championed as if they
were genuinely treating the associated conditions. But while virtual reality,
AI in research, and other technologies can undoubtedly be applied to detect
problems, we must also remember that a tech shortage doesn’t cause most of our problems.

most of our problems arise from a complicated network of events and
circumstances. Most of these conditions and circumstances are economic, social,
and political. As such, they will only admit solutions that are similarly
economic, social, and political.

Another use for artificial intelligence

AI in
research can also help discover illness in older adults, empowering them to
live more freely and more extended periods. Researchers are also building
prototype living spaces, called smart homes, to study how they might look and
operate shortly for older adults, people with physical inabilities, and those
who have chronic diseases. 

purpose is to enable people to live safely, freely, and conveniently for longer
in assisted living with technology. 

Final Thoughts

refers to loneliness, which is not only on the rise but probably a symptom of
life in the more increasingly competitive and individualistic approach in the
21st Century. If we’re truly serious about loneliness, we must look cautiously
at what aspects of our age cause isolation and change them subsequently. Or
else, merely applying AI in research-driven approaches to determine and
diagnose loneliness will result in a little more than another money-making


  • 10 October, 2020
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