The pursuit of happiness is one of the main goals people have in life, and it’s understandable. It’s something that each person seeks naturally, as it’s not just an idea inoculated by the media. But forgetting our inherent worth, comparison, worrying too much about the future, living in our heads, a lack of gratitude, depression, and stress are all common causes that prevent people from being happy.
Nancy Etcoff, Ph.D., Harvard Medical School, who’s especially interested in fields like happiness and beauty, has teamed up with Deep Longevity to present human psychology packed up with machine learning, giving the chance to create digital models of the former.
SciTechDaily brings the news about the collaboration. The first model is based on a psychological survey to predict psychological well-being in the long run for those who are surveyed. The model brought the sad conclusion that people lose their focus on personal progress with age. After 40 to 50 years, even their sense of having a purpose in life goes away.
The second model is used by a learning algorithm for applications regarding mental health. The responders are split into groups depending on their chances of suffering from depression, which we all know is perhaps the biggest enemy of happiness. The algorithm also tells the shortest road to get to mental stability for each of those people.
Deep Longevity explains about FutureSelf in the following video:
Vadim Gladyshev, a professor from Harvard Medical School, explained as SciTechDaily quotes:
This study offers an interesting perspective on psychological age, future well-being, and risk of depression, and demonstrates a novel application of machine learning approaches to the issues of psychological health. It also broadens how we view aging and transitions through life stages and emotional states.
The new study paper was published in Aging-US.