life2vec, is trained on a data set pulled from the entire population of Denmark—6 million people. The data set was made available only to the researchers by the Danish government.
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The Website:
Using sequences of life-events to predict human lives
Here we represent human lives in a way that shares structural similarity to language, and we exploit this similarity to adapt natural language processing techniques to examine the evolution and predictability of human lives based on detailed event sequences. We do this by drawing on a comprehensive registry dataset, which is available for Denmark across several years, and that includes information about life-events related to health, education, occupation, income, address and working hours, recorded with day-to-day resolution. We create embeddings of life-events in a single vector space, showing that this embedding space is robust and highly structured. Our models allow us to predict diverse outcomes ranging from early mortality to personality nuances, outperforming state-of-the-art models by a wide margin. Using methods for interpreting deep learning models, we probe the algorithm to understand the factors that enable our predictions. Our framework allows researchers to discover potential mechanisms that impact life outcomes as well as the associated possibilities for personalized interventions.
Paywalled paper: Using sequences of life-events to predict human lives | Nature Computational Science
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Interesting.
Paywalled paper: Using sequences of life-events to predict human lives | Nature Computational Science
I noticed that the publisher’s page also links to a pre-print at arXiv (freely available). Direct link to that:
[2306.03009] Using Sequences of Life-events to Predict Human Lives.
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The free calculator was fun to talk to and asked a bunch of questions, then it redacted it’s predictions. I begged for awhile then asked why and it said it couldn’t tell me.