Artificial city

Artificial intelligence developed by Harvard University determines the shortest path to human happiness

Researchers have created a digital psychology model that aims to improve mental health. The system offers superior customization and outlines the shortest path to a set of mental stability for any individual.

Deep Longevity, in collaboration with Harvard Medical School, offers a deep learning approach to mental health.

Deep Longevity published an article in Aging-US describing a machine learning approach to human psychology in collaboration with Nancy Etcoff, Ph.D., Harvard Medical School, Authority over happiness and beauty.

The authors created two numerical models of human psychology based on data from a US Midlife Study.

The first model is a set of deep neural networks that predict respondents’ chronological age and psychological well-being over 10 years using information from psychological surveys. This model describes the trajectories of the human mind as it ages. It also shows that the ability to form meaningful bonds, as well as mental autonomy and mastery of the environment, develop with age. He also notes that the focus on personal progress steadily decreases, but the sense of having a purpose in life fades after only 40 to 50 years. These findings add to the growing body of knowledge about social and emotional selectivity and tasteful adaptation in the context of adult personality development.

The article describes an AI-based recommendation engine that can estimate an individual’s future psychological age and well-being based on a generated psychological survey. The AI ​​uses the respondent’s information to put them on a 2D map of all possible psychological profiles and devise ways to improve their long-term well-being. This human psychology model can be used in digital self-help applications and in therapist sessions. Credit: Michelle Keeler

The second model is a self-organizing map created to serve as the basis for a recommendation engine for mental health apps. This unsupervised learning algorithm divides all responders into groups based on the likelihood of developing depression and identifies the shortest path to a set of mental stability for any individual. Alex Zhavoronkov, Director of Sustainability at Deep Longevity, explains, “Existing mental health apps offer general advice that applies to everyone but doesn’t work for anyone. We’ve built a scientifically sound system that offers ultra-customization.

To demonstrate the capabilities of this system, Deep Longevity launched the FuturSelf web service, a free online application that allows users to take the psychological test described in the original post. At the end of the assessment, users receive a report with insights aimed at improving their long-term mental health and can enroll in a mentorship program that provides them with a steady stream of AI-chosen recommendations. Data obtained from FuturSelf will be used to further develop Deep Longevity’s digital approach to mental health.

FuturSelf is a free online mental health service that provides counseling based on psychological profile assessment by artificial intelligence. The core of FuturSelf is represented by a self-organized map that ranks respondents and identifies the most appropriate ways to improve an individual’s well-being. Credit: Fedor Galkin

Leading bioscientist Professor Vadim Gladyshev of Harvard Medical School comments on the potential of FuturSelf:

“This study offers intriguing insight into psychological age, future well-being, and risk of depression, and demonstrates a novel application of machine learning approaches to mental health issues. It also broadens our view of aging and changes life stages and emotional states.

The authors plan to continue studying human psychology in the context of aging and long-term well-being. They are working on a follow-up study on the effect of happiness on physiological measures of aging.

The study was funded by the National Institute on Aging.

Reference: “Improving Future Wellbeing Using Artificial Intelligence: Self-Organizing Maps (SOM) to Identify Islands of Emotional Stability” By Fedor Galkin, Kirill Kochetov, Michael Keeler, Alex Zavoronkov, and Nancy Etkoff, June 20, 2022, The Aging United States.
DOI: 10.18632/age.204061