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An artificial intelligence called Life2Vec, developed by researchers from Denmark and the US, claims an astonishing 78% accuracy in predicting individual life expectancy and even cause of death, based solely on personal factors such as diet, income or smoking habits. This AI ‘death calculator’ applies advanced transformer algorithms to detect patterns linking lifestyles and mortality in Danish population data. However, direct public access to this emerging tool remains unavailable and likely inadvisable given the unresolved ethical questions.
What exactly is Life2Vec AI?
Life2Vec is a machine learning architecture that encodes human lives into “life vectors”: mathematical representations of health events, career progressions, and demographic factors calibrated to estimate mortality probabilities. The approach is similar to language prediction models such as ChatGPT.
How Life2Vec codes and predicts life outcomes
This AI encodes a lifetime of knowledge into vector dimensions, capturing details such as:
- Date of birth
- Salary trajectory
- Medical history
- Dietary quality
It then compares new vector profiles with historical data to predict personalized probabilities of premature death, future income, diseases and even personality changes related to risk factors.
For example, smoking can increase the likelihood of a specific adverse outcome by a calculated percentage. The researchers claim that Lif2Vec2Vec substantially outperforms previous prediction attempts from modern neural networks. But should we blindly trust its ominous predictions?
Can the public access or log in to Life2Vec?
Despite the intense curiosity surrounding this so-called ‘AI grim reaper’, Life2Vec remains a closely guarded research prototype that is currently inaccessible for individual use or commercial deployment.
The source code for running data modeling experiments is available on GitHub. However, the actual population health data from Denmark that underpins the predictions cannot be released publicly due to strict data protection.
See more: AI Death Prediction Calculator Free with Life2vec AI Tool
What can this AI oracle tell me about my own life expectancy?
If given access, Life2Vec can process your personal health history and habits to estimate a personalized lifespan prediction and risk profile for serious diseases based on statistical life patterns it discovers in the data. However, researchers strongly caution against relying on such AI-generated insights without rigorous external validation.
They argue that responsible development and rigorous testing of such innovations with emotional impact should be prioritized over implementation speed or profit motives. Many experts convened by WHO agree on historical issues that there is bias in algorithmic systems.
Can we trust Life2Vec’s predictions?
Although Life2Vec supposedly boasts remarkable accuracy, some skeptics question whether even massive data and advanced calculations can reliably predict the complexities of real individual lives and health trajectories.
Correlation does not prove causation
Much variability in human life remains mysterious even to science. For example, genetically identical twins often die years apart. Confounding influences obscure many correlations between behavior and mortality that AI could detect.
Risk of continued social prejudice
Importantly, population-level training data is not an objective measure, given the impact of privilege and inequality on the health of groups across generations. Like some facial recognition systems, Life2Vec could potentially spread unfair biases if deployed hastily without extensive evaluation.
In summary, while the Life2Vec AI represents a transformative advance in digital modeling of lifelong personal risk, it remains a tightly controlled academic prototype that requires extensive ethical safeguards around safety and bias before being publicly released. Access to its code intriguingly reveals innovations in AI predictive analytics, but adhering to the Grim Reaper’s predictions requires a lot of caution.
Conclusion: a remarkable but probably unreliable AI Oracle
The Life2Vec mortality calculator shows how machine learning, applied to healthcare data analysis, has achieved stunning new capabilities to computationally connect lifestyle factors and lifespan projections. However, dramatic variability between individuals, including due to social inequality, currently seems to limit the reliability of even the most advanced model for real-world application.
Until strict accountability standards can be put in place and issues of algorithmic bias can be satisfactorily addressed to protect public interests over profits, direct access to this fascinating yet troubling AI innovation will likely remain limited. But such restrictions rightly focus attention on addressing profound ethical dilemmas introduced by emerging technologies before their more ominous potential is unleashed.
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