By Sergejs Bobrovskis, Sr. Director: Technical Product Manager - Twill, United States
As a professional, deeply embedded in the technological environment, I find it particularly intriguing how AI/ML is already capable and will be able to influence the Mental Health Industry in the future. As we can see, existing technologies firmly embedded in supporting users experiencing mental health problems are no longer a fantasy of science fiction writers, but the future that has already arrived.
In this blog, I want to share my experience and opinion on where the AI mental health industry is heading and how technologies will help to realize the plans. As you all know, not a single news item (every day) is deprived of information that companies continue to innovate all aspects of our lives, including mental health.
Today, AI-powered tools offer unprecedented opportunities for mental health care personalization, with timely data to provide dynamically customized and accurate support.
Below is a small list of what many mental health companies are already developing and using in their solutions:
AI-supported platforms capable of dynamically customizing the sequence of screens shown to fully adjust the importance of answers and collect information in real-time. As a result, these systems subsequently also allow dynamically building (adjusting) the system for solving the user's mental health problems. In common parlance, this is called an AI-based dynamic recommendation engine.
Like any respected doctor, first assesses the patient's condition (remember the series "Doctor House"), as a result, a treatment method is proposed, based on all the collected data, their analysis, and representation. Thus, users are divided into clusters within which similar verified methods are used to treat the existing problem.
This is the ability to dynamically adjust the model to decide on the proposed treatment. The key goal is to collect, analyze, and provide clean and accurate data to determine decision-making and provide the user with the environment where maximum effect will be achieved in solving the existing mental health problem.
Naturally, all existing methods are based on serious research, supported by scientific methods, carried out through years of research by the best minds of the planet (different countries). With the advent of digitalization, it became possible to bring these solutions to the masses and make them available to everyone, while dynamically adjusting the solution to the needs of each. We live in a unique time.
For example, AI-driven platforms can provide real-time feedback based on user interaction. The built-in help and ethics feature also allow real-time detection of suicidal tendencies even in those moments when it is not very clear that a person is suffering from deep depression. Analysis of the information entered by users in real-time can influence recommendations, for example, to immediately consult a doctor, and systems with Internet access can offer existing doctors and even their phone numbers and working hours. Thus, these systems become home doctors available at any time.
The ability of the system to adapt to the needs of users is a key "game changer" because by combining Data Science, AI/ML, Engineering, and UX/UI, virtually any solution becomes attractive to each user because the system can understand the needs of a particular person better than anyone else.
Also, the key aspect of these systems was accessibility, which, as I already said, not everyone could afford (price, distance, time). Existing systems may cost some money ($5-10) per month, which is insignificant compared to how much professional therapist’s cost. There are no more financial or geographical barriers.
It is important to note that existing solutions are diverse, these can be special exercises, or games, or joint exercises with other people. Traditional methods of treating mental health will not disappear (even though we increasingly hear that this will happen), because any AI/ML systems rely on professionals in one field or another. AI/ML solutions will remain an auxiliary function capable of freeing up the time of professionals to solve human-related issues, which will positively affect the process of improving problems with mental health.
I want to note that many companies (especially large ones) have long understood that it is necessary to have a function (or department) engaged in helping to solve mental problems. Frankly speaking, each of us goes through many events in life, positive and negative, and as a result, not everyone can independently resolve the current situations, which often affects work functions. Companies are actively investing in digital assistants for their employees who are available at any time of the day. Which also allows for collecting data and providing the necessary physical assistance promptly.
Looking to the future, we can safely say that AI / ML will develop even more rapidly. Existing platforms that allow from A to Z to research, analyze, train, verify, and deploy will turn into full-fledged AI solutions that, even without knowledge of programming, will be able to be implemented like a designer into various aspects of our lives through digital solutions.
In my opinion, the following key trends will be constantly on the horizon:
Given how much data each of us generates every day, these systems will undoubtedly be able to determine the environment in which solutions to mental health problems will be most effective.
There is already an entire ecosystem (for example, Apple), which integrates all its products into a single network. Integration of systems into carriers will allow us to assess your condition at any time and even offer solutions in real-time. For example, if your heartbeat has changed and, according to AI / ML, you fall into a dangerous state for health, then a recommendation may appear on how to get out of this state, or even automatically call an ambulance by accurately indicating your location.
As we know, all AI models are based on "people", accordingly, the decisions made in one way or another depend on a person, and as we know, a person is subject to bias, which will also affect the solutions provided. Some studies identify all aspects of bias and how to counter them. This direction will be an integral part of any AI solutions.
The main goal of AI is to make it accessible and easy to use. Just as Steve Jobs once introduced the iPhone, which became available to almost the entire world, AI will also become ubiquitous, and not something scientific.
Despite all the world's strife, communities from all over the world continue to interact to promote AI in our lives. There is no area or industry where AI cannot be applied, so I look forward to innovations.
Conclusion
The key inference I want to highlight is that AI has already become a part of life, whether we like it or not. Although the main aspect of this article is Mental Health, it is important to note that this is only a small part of what AI will allow us to do. It is critical to note this process of innovation, which, given the pace of development, will surprise more and more and even make today's solutions obsolete. Therefore, it is necessary to be aware of where AI is heading; what discoveries are on the horizon, and how you and I can be an integral part of this “out of this world” journey.
