Can AI Help Improve Mental Health in the Workplace?
AI's seemingly boundless reach into the workplace spans industries and use cases. And of the many areas business are looking to apply AI, a slightly unexpected one is in helping to support — and improve — employee mental health.
“With tools such as GPT (Open AI) and Bard (Google); AI in the workplace is inevitable,” said Dr. Vivienne Ming, CEO of Socos Labs. "There are already a number of companies toying with using large language models as mental health resources, benefits advisors and even aspects of employee management.”
But can AI really help improve mental health?
Supporting Better Workplace Mental Health Programs
People are increasingly seeking employment with companies that value mental health, said Chaitali Sinha, head of clinical development and research at Wysa.
A 2023 study found that more than two-thirds of employees want their employers to help them deal with stress and anxiety. In fact, workers want support for the mental health of their whole families, with family mental health now a top workplace priority.
“To attract employees and maintain a healthy staff, organizations need to institute some form of mental health care support,” Sinha explained. “Mental health care is a fundamental need, and if companies ignore their employees’ needs, productivity can plummet along with their employee’s individual wellbeing.”
Technology, said Sinha, drastically increases healthcare access. And when companies invest in mental health tools that support their employees, they can prevent workplace conditions from worsening and maintain productivity levels.
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AI Improves the Workplace, Which Boosts Happiness on the Job
When implemented correctly, AI can improve the workplace. It can streamline operations, erase repetitive tasks from employee to-do lists, increase safety and do a lot more.
One study published in 2022 examined the impact of artificial intelligence on manufacturing workers in China. It found that by improving the workplace, AI can boost mental health.
“Improving the work environment is a powerful way to increase the positive effects of AI on workers’ mental health,” the researchers wrote.
Interestingly, the study found that AI had the most mental health benefits for low-skilled workers and workers born after 1980.
Another 2023 study of generative AI at work found AI greatly improved the performance of novice and low-skilled workers, which resulted in reduced requests for managerial intervention and increased employee retention.
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AI + Sentiment Analysis = Employee Emotion Detector?
Some organizations use AI coupled with specialized technology such as sentiment analysis to better understand how their employees think and feel. Both IBM and Intel use sentiment analysis with that purpose in mind, according to Dr. Ming.
“IBM is using sentiment analysis for employee onboarding during the first 30 to 90 days. The company is a big predictor of long-term employee outcomes,” Ming said. “Intel is using sentiment analysis around work-life balance and even trying to design policies that reflect the results of their sentiment analysis.”
She said Google also uses AI to identify and manage stressors, anxiety and look for signs of depression among its workforce.
“I've actually done collaborative research with them around identifying evidence of depression, for example, in their search tools and so forth. But they don't use them on the consumer side; they're using them internally, and they actually use it to come up with wellness plans for people.”
Grace Chang, founder and CEO of Kintsugi, an AI-backed mental health company, said their platform is currently in a clinical trial with Loma Linda University Health to address and optimize trainee and physician burnout.
They’ve also partnered with a major payor organization in the US to pilot an employee benefit program. The program, she said, will “provide access to our voice journaling app and behavioral insights for employees to better understand, track and optimize their mental wellness journey.”
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AI + Natural Language Processing = More Collaboration?
According to Dr. Ming, her organization is working on a new project using natural language processing (NLP) to listen to employees collaborating with one another in real time.
“We're measuring things such as stress in real-time. But even more excitingly, we're measuring psychological safety. Such as, are employees actually freely sharing their ideas with one another, or are they holding back because they're not getting heard because they're afraid of telling the truth and think it will be used against them?”
With this technology, you can literally see during collaborations where people have the ability to fully participate but choose not to, said Ming.
“What we know is [that] moving one person in a low psychological safety team to another team can double their productivity,” she said. “Surprisingly and suddenly, they're actually adding value, and unsurprisingly, their stress goes down.”
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AI for Employee Mental Health Can Help, But It Comes Down to People
Research dating back to the 1970s describes how voice features — like pitch, prosody and pauses — can indicate the presence of mental health conditions, said Chang.
“With the advent of deep learning, we are able to leverage a more end-to-end approach to identify voice biomarkers indicating signs of mental health conditions, like depression and anxiety, without needing to first identify features like pitch and prosody, or even needing to translate the speech content into text before the prediction is made,” she explained.
Still, said Ming, when it comes to using AI to improve employee mental health, evidence of positive outcomes is mixed. “So much depends on how people use the resources,” she said. “It's one thing to run these sentiment analysis and AI systems in a lab and get a certain remote result. It's another thing when you watch people using it.”
Still, she’s enthusiastic about the use of AI. But, she said, if AI is making a difference in mental health, it’s not about AI but rather about how people are making use of it.
“One of the limitations of sentiment analysis and other AI technology,” she explained, “is that they tend to assume one size fits all. If two different people use the same words, it means exactly the same thing. If using facial analysis and if two people are smiling, then the outcome is they're both happy.”
We all know this isn’t accurate, and research, Ming said, has demonstrated that. “Everybody speaks a different language, even when it’s literally the same language. Most AI approaches — even a relatively simple idea like sentiment analysis — don’t respect the fact that we’re different.”
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AI’s Role in the Future of Workplace Mental Health
There’s no question that AI in the workplace is here to stay. And if used adequately and intentionally, it could play a huge positive role in mental health, Ming said, but only if we respect that everyone is different.
And, she added, no matter how sophisticated, AI remains a tool. “Sentiment analysis can no more cure depression than a stethoscope can cure pneumonia,” she said.
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