New AI can shockingly predict how successful you'll be in life

A new artificial intelligence program is being harnessed to help individuals anticipate the stages of their life, including their death.

Researchers in Denmark want to highlight technology's power and perils, so they created life2vec to help them explore patterns that deep-learning programmes can uncover to predict a range of health of social "life-events". The artificial intelligence program is being fed data from millions of people to help its predictions.

"It's a very general framework for making predictions about human lives. It can predict anything where you have training data," Sune Lehmann, a professor at the Technical University of Denmark, and one of the authors of the study, told AFP.

The algorithm uses a similar process to ChatGPT, but instead analyses variables impacting life such as birth, education, and social benefits.

Lehmann sees the program as having endless capacity, saying: "It could predict health outcomes. So it could predict fertility or obesity, or you could maybe predict who will get cancer or who doesn't get cancer. But it could also predict if you're going to make a lot of money."

Whilst the innovation is impressive, it has unfortunately resulted in claims that it can offer life expectancy prediction, with dupes being created and advertised as a "death calculator". The false sites often offer this data in exchange for personal information.

Researchers have stated that the software is private and unavailable to the wider community currently.

"For now, it's a research project where we're exploring what's possible and what's not possible," Lehmann said.

The programme analyses the sequences of events by pressing the anonymised data of roughly six million Danes, collected by the official Statistics Denmark agency.

The algorithm is right in 78 per cent of cases when It comes to predicting death. When predicting if a person will move to another city or country, it is correct in 73 per cent of cases.

"We look at early mortality. So we take a very young cohort between 35 and 65. Then we try to predict, based on an eight-year period from 2008 to 2016, if a person dies in the subsequent four years," Lehmann said.

"The model can do that really well, better than any other algorithm that we could find," he said.

According to the researchers, focusing on an age bracket where deaths are infrequent, allows them to verify the algorithm's reliability.

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