CONCEPT
Debiasing
The set of strategies for reducing the influence of cognitive biases on judgment — and Tversky's lesson that none eliminates the biases, but some reduce them enough to matter when the amplifier is on.
Debiasing is the applied discipline of reducing cognitive bias in judgment, developed from the heuristics-and-biases research program. Tversky's work demonstrated that awareness alone provides only modest protection against biases — subjects warned explicitly about anchoring effects still exhibit anchoring. Effective debiasing requires structural interventions: procedures that compensate for biases even when individual biases persist. The strategies fall into four categories: awareness-based (making biases visible), process-based (designing decision procedures that compensate), environment-based (changing the information environment), and collaboration-based (using complementary cognitive systems). In the AI era, a fifth strategy emerges: narrative-based debiasing, which redirects cognitive processes by replacing distorting narratives with more accurate ones. The amplifier metaphor in You On AI is an example.
In The You On AI Field Guide
The key finding that awareness is insufficient was established in Tversky and Kahneman's original experiments and confirmed across decades of replication. Even experts, even subjects offered financial incentives, even subjects warned about specific biases, continued to exhibit them. The mechanism operates below