A new AI-driven app called Death Clock is making waves among health enthusiasts and economists alike. Launched in July, the app has already been downloaded 125,000 times, according to market research firm Sensor Tower. The app uses artificial intelligence to predict a user's likely date of death, based on factors like diet, exercise, sleep patterns, and stress levels.
Death Clock's AI has been trained on over 1,200 life expectancy studies, involving 53 million participants. The app promises more personalized and accurate predictions than traditional actuarial tables, which are commonly used to estimate life expectancy. Developer Brent Franson claims the app's results offer a significant improvement over traditional methods.
Despite its somewhat dark premise, featuring a "fond farewell" death-day card and a countdown to the end of life, the app has gained popularity in the Health and Fitness app category. Users are drawn to its potential to help them live healthier lives by understanding their individual risks and making lifestyle changes.
Beyond personal health, Death Clock's AI-powered predictions could have broader implications, especially in finance and economics. Life expectancy is a critical factor in financial calculations, from retirement planning to life insurance and pension funding. The new AI technology could offer more accurate data for these industries, potentially transforming how policies and personal financial strategies are developed.
In the U.S., where life expectancy has lagged behind other developed nations in recent years, the Social Security Administration uses mortality rate tables to make projections. For instance, it estimates that an 85-year-old man has a 10% chance of dying within a year, with an average life expectancy of 5.6 years. However, Franson argues that such averages can be misleading and that AI offers a more tailored approach to life expectancy predictions.
The growing interest in AI-driven life expectancy tools is highlighted by recent research from the National Bureau of Economic Research (NBER). One study, titled "On the Limits of Chronological Age," challenges the idea that chronological age is an accurate measure of an individual's ability to function. The researchers suggest that policies based on age, such as retirement, may overlook other factors that influence economic behavior.
Another NBER paper, focused on the "value per statistical life" (VSL), examines how older Americans are willing to spend on medical services to reduce mortality risk. The study found that those in better health are willing to spend significantly more, which could impact economic policies related to healthcare and insurance.
Financial planners, too, are taking notice. Ryan Zabrowski, a financial planner at Krilogy, believes that AI-driven life expectancy tools could drastically improve retirement planning. According to Zabrowski, many retirees worry about outliving their savings, and more accurate life expectancy predictions would help guide decisions about savings, investments, and withdrawals.
As AI technology and advancements in healthcare continue to extend life expectancy, the need for more precise financial strategies will only grow. Death Clock and similar innovations could reshape how people plan for their financial futures and how policymakers approach the challenges of aging populations.
