Deep Longevity collaborates with Harvard Medical School's happiness and beauty authority Nancy Etcoff, Ph. D. The authors focused on Aging-US, outlining a machine learning approach to human psychology. Based on the published paper, the two authors created digital models of human psychology using the data from a study on Midlife in the United States.

Deep Longevity Artificial Intelligence (AI) Models

The first model uses data from a psychology survey. It is an ensemble of deep neural networks predicting the psychological well-being of the respondents in 10 years and their chronological age. The trajectory of the aging human mind is shown in the model. It also shows the ability to make meaningful connections, such as environmental mastery and mental autonomy.

It also implies a constant decline in a person's personal progress. However, the sense of having a purpose in life only gradually disappears over the force of 40 to 50 years. These findings contribute to the growing body of literature on hedonic adaptability and socioemotional selectivity in the context of adult personality development.

On the other hand, the second model serves as a self-organizing map. It was developed as a basis for a recommendation engine for mental health applications.

The second model is an unsupervised learning algorithm. Its goal is to divide the respondents into clusters based on the likelihood that they would experience depression. It also determines the shortest way toward a cluster of the mental stability of an individual.

"Existing mental health applications offer generic advice that applies to everyone yet fits no one. We have built a system that is scientifically sound and offers superior personalization," said Chief longevity officer of Deep Longevity, Alex Zhavoronkov.

Artificial Intelligence FuturSelf

In support of the author's project, FuturSelf was launched. The free web service enables users to perform the psychological test outlined in the original publication.

Users receive a report with recommendations after completing the evaluation. The recommendation aims to enhance the individual's long-term mental health. It also gives an individual and option to participate in a guiding program. These programs are made by artificial intelligence (AI) and sent to them regularly.

Professor Vadim Gladyshev, a renowned biogerontology expert from Harvard University, weighed in on the study. According to him, it provides an unusual perspective on psychological age, depression risk, and future well-being.

The study shows a new usage of machine learning techniques for psychological health issues. Gladyshev also added that it broadens people's perspective on aging and changes in emotional states during transitions between life periods.

The author plans to find the relation between long-term health and aging in human psychology.

A follow-up study investigating how happiness impacts the physiological signs of aging is presently being conducted.

Jamie Gibson, Chief Executive Officer of Endurance Longevity, said they are thrilled to achieve the remarkable milestone with the well-known scientists. Gibson added that they are confident about the integration of deep learning AI technologies and human psychology in the future and the development of digital solutions to improve people's mental health and overall well-being.

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