Reduce Bias In Analysis: Why Should We Care? (Or: The Effects Of Evidence Weighting On Cognitive Bias And Forecasting Accuracy) | Writing, Research, Applied Thinking and Applied Theory: Solutions with Interesting Implications, Problem Solving, Teaching and Research driven solutions | Scoop.it

We have done much work in the past on mitigating the effects of cognitive biases in intelligence analysis, as have others. This post, however, is indicative of where we think cognitive bias research should go (and in our case, is going) in the future.  Bottomline: Reducing bias in intelligence analysis is not enough and may not be important at all. 
What analysts should focus on is forecasting accuracy. In fact, our current research suggests that a less biased forecast is not necessarily a more accurate forecast.  More importantly, if indeed bias does not correlate with forecasting accuracy, why should we care about mitigating its effects? In a recent experiment with 115 intel students, I investigated a mechanism that I think operates at the root of the cognitive bias polemic: Evidence weightin


Via Bonnie Hohhof