Why expert forecasts often fail to track reality over long periods of time
In short: This video from MIT's Risk and Decision Analysis course introduces porcupine graphs. These visual tools reveal a common failure in expert forecasting: the persistent inability to adjust predictions in response to actual events, leading to consistent bias.
The term porcupine graph refers to a specific way of visualizing forecasting data that highlights how experts often struggle to update their projections. Rather than correcting their models as new information emerges, experts frequently maintain biased forecasts over extended durations.
By examining these patterns, the course material demonstrates that forecasting errors are not always random. Instead, they often reflect a structural difficulty in adapting to unfolding reality, a phenomenon that remains a critical challenge in risk and decision analysis.
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Sources
- Summary by Intellect · source: Unit 2: The Forecast is Always wrong, Video 3: Porcupine Graphs
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