Using comprehensive personal data from Denmark, a team at the Technical University of Denmark developed an AI model, Life2vec, to predict individuals’ risk of death. The model outperformed existing AI models and life tables by 11% and was also able to predict personality outcomes. The study also highlights the ethical considerations surrounding AI’s predictive capabilities.
An AI system predicting the risk of premature death
An AI system developed using comprehensive personal data from Denmark has shown remarkable accuracy in predicting an individual’s risk of death. Sune Lehmann Jørgensen and his team from the Technical University of Denmark created this AI, documented in a study published in Nature Computational Science. They utilized a huge dataset encompassing numerous factors across the Danish population, including education, medical visits, diagnoses, income, and occupation data from six million individuals spanning from 2008 to 2020.
Life2vec Model Development and Testing
They developed the Life2vec model by transforming the data into a format suitable for training a large language model (LLM). This model reviews a person’s life events and forecasts probable future outcomes and has outperformed existing AI models and actuarial life tables by approximately 11%. It was also used to predict personality outcomes, showcasing the model’s ability to map large-scale societal inputs to outputs at the individual level.
Practical Applications
Jørgensen envisions this model as a tool for early detection of health and social issues, potentially aiding governments in reducing health and social inequalities. He cautions against potential business misuse, particularly in the insurance industry. Similarly, there are both benefits and risks associated with using AI to predict important life events such as death.
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