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How AI Humanizes Mental Healthcare

The integration of AI into mental healthcare is more advanced than many realize because it’s not always obvious; frequently, it’s providing support to free up clinicians to spend more time with their patients or to get more patients into treatment. 

Despite OpenAI’s most recent news that it’s releasing new AI models with reasoning capabilities to “spend more time thinking through problems before they respond, much like a person would,” AI maintains a synthetic perception. Frequently seen as a technology that creates distance between individuals, people view the medium as one that automates and depersonalizes tasks traditionally done by humans. 

In the realm of mental healthcare, the personal touch is critical. How we relate and interact with people is often a key component of caring for those suffering from mental illness, yet can sometimes be as overlooked as bedside manners. However, AI is starting to demonstrate its potential to overcome long-standing challenges, including the shortage of mental health professionals, the stigma associated with seeking help, and the difficulty of providing personalized care at scale. Multiple pieces of academic research, including this aggregation of papers, have shown that AI can make mental healthcare more accessible.

To truly understand how AI is transforming the present and future of mental healthcare, it’s helpful to look back at the evolution of mental health treatment throughout history. Sadly, mental illness has led to ridicule and stigmatization, with the treatment frequently being rudimentary, and at times even brutal. From trepanation in the Neolithic era — where holes were drilled into skulls to release evil spirits — to the use of asylums in the Middle Ages, mental healthcare has been slow to progress. 

It wasn’t until the 20th century that modern approaches like psychotherapy and psychopharmacology emerged, treating patients with more dignity and compassion. Furthermore, only in the past few years have we as individuals been able to discuss mental health issues as openly as we have physical ones. This need for support, however, proved to be insufficient to meet the growing demand, with mental health systems and services not prepared for the floodgates that have since opened. This has led to unprecedented challenges, particularly in terms of capacity and accessibility.

To help deal with these hurdles, one must start from the early areas in which AI integrates into mental healthcare: the initial assessment process. Traditionally, this process is time-consuming, often requiring trained professionals to spend up to 90 minutes with each new patient, asking rudimentary questions to identify symptoms and plan treatments. Fortunately, AI-driven assessments are able to complete this more quickly without compromising the quality of care. 

Using AI to gather and analyze patient data unburdens already overworked clinicians, allowing them to focus on engaging with their patients and understanding their problems personally rather than asking impersonal assessment questions. Physical healthcare has seen similar benefits through the use of AI-powered transcription, with AI freeing up for doctors to focus more on patient engagement.

Another crucial way AI is enhancing mental healthcare is through patient engagement between therapy sessions. Moments of anxiety and stress can affect us at any time, but nighttime, weekends, and holidays are commonly identified as the most stressful. Patients frequently find themselves disoriented without support, with a lack of coping mechanisms leading to increasing feelings of loneliness and helplessness in these vulnerable moments.

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AI-powered care companions play a hugely valuable role in interacting with patients in the days between sessions and outside office hours. They help patients stay engaged with their treatment protocols, reminding them to complete wellness exercises, mitigate stress, and monitor their progress. Consistent engagement helps patients advance through their treatment more quickly and effectively, providing them with a sense of support and continuity even when they are not in direct contact with their therapist.

Clinicians are not immune to mental health issues themselves; they are a growing contingent of the industry in need of support. Burnout has recently been included as a disease in the 11th revision of the International Classification of Diseases (ICD-11) “as an occupational phenomenon indicates that it is an issue of concern in the workplace for which people may need professional attention.” AI can alleviate some of this burden by taking over administrative tasks such as clinical note-taking and data entry, while transcribing recordings of therapy sessions into text and summarizing key points for the therapist’s notes.

Perhaps the most impactful role that AI can play in mental healthcare is in improving accessibility. Huge economic, cultural, and societal barriers permeate the mental health space to this day: In 2022, the Hispanic population had the highest uninsured rates at 19.1%, with the Black population at 10.0% and the White population at 6.6%. Given this data, it can be no surprise that the American Psychiatric Association reported that only one in three Black adults experiencing mental illness receive treatment — and they are less frequently included in mental health research.

This is perhaps the most impactful way in which AI can help make mental healthcare more human. Ironically, by removing humans from the intake process, the non-judgmental nature of AI can create a more welcoming environment for those who might otherwise feel stigmatized or uncomfortable seeking help from an individual. 

AI can improve accessibility, clinician efficiency, and patient assessment and support by taking humans out of the automated processes. By using AI to remove the admin burden on clinicians, we’re allowing them to spend more time with their patients. By using AI to support patients outside normal office hours, we’re helping people feel less lonely. By using AI to intake patients, we’re allowing patients to feel less judged. All of these uses are enhancing the personal side of mental health treatment.  

Where concerns about AI in other sectors focus on AI taking people’s jobs, creating fake experiences, or becoming “much like a person,” within mental healthcare, AI is a catalyst for making the experience more human. The integration of AI into mental healthcare is more advanced than many realize because it’s not always obvious; frequently, it’s providing support to free up clinicians to spend more time with their patients or to get more patients into treatment. 

AI will never replace people in mental healthcare because mental healthcare is about dealing with profoundly human issues. People created AI to help free them up from those things that can be better done by machines: computation, task management and process automation. People are wonderfully more creative, complex and unpredictable. 

In mental healthcare, we are increasingly thankful to AI for doing those things that allow us to be more … human.

Photo: metamorworks, Getty Images

Ross Harper, CEO of Limbic, is a distinguished Ph.D. in computational neuroscience and a Master's in Mathematical Modelling from University College London and a Master’s in Natural Sciences from the University of Cambridge. Ross possesses an intricate understanding of the overlap between math, technology, and the human mind. He launched Limbic in 2020 to enable large language models and GenAI to aid processes in the mental health space, supporting clinicians and patients within the NHS and the U.S.

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