The “turkey problem” is a thought experiment posed by author Nassim Nicholas Taleb to illustrate the dangers of inductive reasoning and generalization from limited data. The name refers to the experience of a turkey being fed by a farmer every day, leading it to inductively conclude that this feeding routine will continue indefinitely. However, its induction proves faulty on the day before Thanksgiving, when the farmer kills and eats the turkey.

Taleb uses this story to argue that many real-world risks and “black swan” events cannot be predicted by projecting the past into the future. Just as the turkey’s belief that it will continue to be fed is reasonable but catastrophically wrong, many human predictions based on past data are also susceptible to rare, unexpected disruptions.

Key aspects of the turkey problem:

  • Inductive reasoning from limited evidence can lead to false conclusions. The turkey generalizes from its daily feedings to a rule that feeding will always occur. But this induction ignores contextual factors like the approaching holiday.
  • Statistical models and forecasts often fail to account for unpredictable disruptions. The turkey’s model assumes the system is stationary, not accounting for a looming regime change.
  • Fragility to black swan events. The turkey’s fate exemplifies fragility to unforeseen nonlinear impacts that lie outside a model’s purview. One unexpected event upends its forecasts entirely.
  • Human susceptibility to the problem. Taleb argues that many domains, from finance to science, demonstrate this same flaw. Models derived from limited past data often miss future discontinuities.


  • Critical thinking is needed about the assumptions and limitations of forecasting models. Validity should not be assumed based on past performance alone.
  • Black swan robustness requires building in buffers and redundancy rather than optimizing systems for efficiency alone. Fragility to rare events needs to be actively guarded against.
  • Induction has value but deductive, theoretical knowledge plays a key role in identifying possible model weaknesses. Pure empiricism has its own blind spots.

The turkey problem serves as an important reminder of the fallibility of inductive reasoning and data-driven forecasting. While such models have value, a comprehensive perspective requires theorizing about their fragilities as well, lest we become complacent turkeys awaiting a Black Swan surprise.

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