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February 25, 20260 citationsOpen Access

The Black Swan Problem: Why Traditional AI Fails at Prediction

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DGDmytro Grybeniuk Dmytro GrybeniukOIOleh Ivchenko

Key Points

  • The aim is to investigate the limitations of traditional AI in predicting extreme, rare events known as Black Swans.
  • Analysis of prediction algorithms
  • Review of existing literature on AI and risk management
  • Case studies on the failure of AI models in predicting Black Swan events
  • Traditional AI models often ignore rare, high-impact events, leading to inaccurate predictions.
  • The failure to account for extreme uncertainties can result in significant risks.
  • The study emphasizes the need for more robust prediction methods that incorporate Black Swan scenarios.

Abstract

Research article from Stabilarity Research Hub: The Black Swan Problem: Why Traditional AI Fails at Prediction

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Cite This Study

Grybeniuk et al. (2026) studied this question.

synapsesocial.com/papers/699e91eaf5123be5ed04fc01https://doi.org/10.5281/zenodo.18749477
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