Mental health problems are becoming increasingly common around the world. Health systems receive millions of patients. How AI can be used in this context.
is a global epidemic that has been quietly brewing for the last few decades. This pandemic is nothing less than an exponential growth of mental health problems across the globe, which is now garnering significant attention due to its dire consequences.
The US Department of Health and Human Services’ Substance Abuse and Mental Health Services Administration (SAMHSA) released a groundbreaking report in 2020 highlighting the devastating effects of mental and substance use disorders (M/SUDs). SAMHSA’s analysis found that “M/SUD treatment spending from all public and private sources is expected to increase from $171.7 billion in 2009 to a total of $280.5 billion in 2020.”
Mental health ailments have become one of the main problems globally
More importantly, mental health problems impose a significant burden on patients themselves, pose incalculable challenges to families and care structures, and sadly lead to the loss of many lives due to irreversible illnesses. In fact, no amount of money or economic analysis can quantify the physical and emotional cost of mental health illness.
Earlier this month, US Surgeon General Vivek Murthy released an advisory report titled “Our Epidemic of Loneliness and Isolation,” highlighting the significant public health concerns caused by mental health problems. He specifically addresses loneliness and lack of social connection among the top concerns and looks back on his journey to recognizing them as issues.
“Loneliness is much more than a bad feeling: it harms both personal and social health. It is associated with an increased risk of heart disease, dementia, stroke, depression, anxiety and premature death. The effect on mortality is similar to that caused by smoking up to 15 cigarettes a day and even more is associated with obesity and physical inactivity,” explains Murthy. And he adds: “And the harmful consequences of a society that lacks social connection can be felt in our schools, workplaces and civic organizations where demonstrations take place.”
Use of artificial intelligence in mental health
Fortunately, growing awareness of mental health has led to significant innovation and investment in new approaches and treatment modalities. One such new concept is the use of artificial intelligence in the field of mental health.
With the advent of generative AI, conversational AI, and natural language processing, the idea of using artificial intelligence systems to provide human companionship has become commonplace.
Google Cloud, which is at the forefront of developing scalable AI solutions, offers an in-depth look at what conversational AI is: “Conversational AI works using a combination of Natural Language Processing (NLP) and Machine Learning (ML) Conversational AI systems are trained on large amounts of data, such as text and voice. This data is used to teach the system how to understand and process human language. The system then uses this knowledge to to interact with humans in a natural way. You’re constantly learning from your interactions and improving the quality of your responses over time.”
Mental health
This means that with enough data, training and interaction, it is within the realm of plausible reality that these systems could replicate not only human language, but potentially billions of data points and evidence to provide medical advice and treatment. -based guidelines.
There is no doubt that companies such as Google, Amazon, and Microsoft are investing billions of dollars in this technology, realizing that they are only steps away from mimicking human speech and language. Once these companies can perfect this, the potential is limitless: everything from customer service to human interactions could be AI-powered.
In fact, there are already test systems out there. Take for example Pi, a personal artificial intelligence system developed by the company Inflection AI. “Pi was created for people to express themselves, share their curiosities, explore new ideas, and experience relatable personal AI,” says Mustafa Suleiman, CEO and co-founder of Inflection AI. He explains: “Pi is a new kind of AI, which is not only intelligent but also a good equalizer. We think of Pi as a digital companion, whenever you want to learn something new, when you need to go through your day. I need a sounding board to talk about a difficult moment in the U.S., or just to spend time with a curious and compassionate counterpart”.
Along with Suleiman, Inflection AI’s other co-founder is Reid Hoffman, who also co-founded the professional networking company, LinkedIn. Inflection AI has raised hundreds of millions of dollars in seed funding to support its technology.
However, this amazing technology brings with it a number of potential concerns. While artificial intelligence certainly has the potential to solve potential access disparities, easily provide health care services, and even provide companionship to those who need it most, it is needed for a number of reasons. should be developed keeping in mind the safety measures.
On the one hand, in a sensitive area like mental health, patient privacy and data protection should be of paramount importance. The use of artificial intelligence technology in this capacity means that a significant amount of sensitive patient information will also be collected. Developers must ensure that this data is never compromised and patient privacy is always a top priority, especially amid the growing cyber security threat landscape.
Beyond that, perhaps the most important concern is existential: how far must humanity go with this? While the benefits of AI are certainly numerous, innovators must be mindful of the limitations of these systems. In particular, systems are only as good as the models and data sets they can learn from, meaning that in the wrong hands, these systems can provide inaccurate or dangerous recommendations to vulnerable populations. Therefore, corporations must implement stricter practices around responsible development.
Finally, as a general social commentary, combating the epidemic of mental health problems and loneliness through the use of artificial intelligence systems sets a dangerous precedent. No system can (yet) replicate the complexities of human nature, interaction, emotion and feeling. Healthcare leaders, regulators and innovators should remember this underlying principle and prioritize viable and sustainable measures to address the mental health crisis, such as training more mental health professionals and increasing patient access to information.
