An app promises to do what humans have wondered about forever: tell you the exact day you’ll die. The Death Clock, launched in July, claims to predict your death date using artificial intelligence.
It has already pulled in over 125,000 downloads, according to Sensor Tower, and it’s backed by data from over 1,200 life expectancy studies covering 53 million participants.
You plug in details like your diet, exercise habits, sleep schedule, and stress levels. The result? A personalized death date—morbid, maybe, but apparently accurate.
The app charges $40 a year and isn’t shy about its theme. Users get a “fond farewell” death card complete with the Grim Reaper, and a countdown timer that ticks off your remaining life by the second. Brent Franson, the app’s creator, says this is no gimmick.
It’s a serious upgrade from the actuarial tables insurance companies and governments have used for centuries. Life expectancy isn’t just a personal concern. It’s the backbone of critical financial systems.
Insurance companies, pension funds, and governments use it to decide everything from policy premiums to Social Security payouts. The United States, already lagging behind other developed countries in life expectancy, could see its outdated mortality models upended by AI.
Is there actually a need for Death Clock?
For years, mortality data has been frustratingly broad. The Social Security Administration, for example, predicts that an 85-year-old man in the U.S. has a 10% chance of dying within a year, with an average 5.6 years left to live. That might work for general estimates, but Franson says it’s useless for individuals.
Death Clock’s AI skips the averages and tailors predictions based on your unique inputs. It claims to be a “significant” improvement over traditional methods.
The app’s approach has already sparked interest in academic and economic circles. In recent months, the National Bureau of Economic Research (NBER) published two papers exploring mortality and its economic impact.
One, titled On the Limits of Chronological Age, argues that age-based policies, like mandatory retirement, are outdated. People age differently, and their capabilities don’t always align with their calendar years. Death Clock’s personalized predictions could help shift the focus from age to actual functionality.
Another NBER study looked at the “value per statistical life” (VSL), a calculation used in cost-benefit analysis for things like environmental regulations and workplace safety. Typically, VSL is estimated based on compensation for dangerous jobs.
The researchers behind The Value of Statistical Life for Seniors used a different approach: how much older Americans spend on healthcare to lower their risk of dying. They found that a healthy 67-year-old values their life at $2 million, compared to $600,000 for someone in poorer health.
How AI predictions could reshape economics
The implications of accurate mortality predictions are massive. For regular folks, it could mean smarter financial planning. Decisions about saving, investing, and withdrawing retirement funds often rely on rough estimates. Death Clock’s precision could make those plans less of a guessing game.
For governments and corporations, the stakes are even higher. Pension funds, life insurance, and Social Security programs all depend on life expectancy estimates. If people live longer than expected, funds run dry. If they die earlier, resources are wasted.
But there’s a catch. Extended life expectancies bring their own problems. Longer lives mean longer retirements, which require more savings. Investment strategies may need to move toward higher-risk, higher-return assets like stocks.
Traditional fixed-income approaches may not cut it for people planning to live well into their 90s. It’s not just about investments though. AI-powered mortality predictions could influence public policies, from healthcare to labor laws.
Age-based benchmarks like statutory retirement might become irrelevant if personalized data becomes the norm. Governments might need to rethink how they structure everything from taxes to pensions.
Longevity gaps and the role of money
Not everyone will benefit equally from these advances. Longevity isn’t just about health, it’s about wealth. Rich Americans live significantly longer than poor ones. Research by the American Medical Association found that at age 40, the richest 1% of men live 15 years longer than the poorest 1%.
For women, the gap is 10 years. Angus Deaton, a Nobel-winning economist, linked this disparity to “deaths of despair” caused by economic inequality.
AI tools like Death Clock could expose these gaps even further. A person’s ability to change their predicted death date depends largely on their resources.
The app suggests lifestyle changes to extend your life, but not everyone can afford healthier food, gym memberships, or stress-reducing vacations. Without addressing these inequalities, AI predictions might widen the gap instead of closing it.
There are also intangibles that AI can’t account for. Loneliness, for example, is known to shorten life expectancy. Gratitude, on the other hand, may extend it.
A Harvard study found that women who reported feeling the most grateful had a 9% lower risk of dying within three years. These factors aren’t easily quantifiable, but they matter.
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