Lael Schooler will introduce the simple heuristics research program that studies decision strategies that can make effective decisions in an uncertain world,with limited time and information.These heuristics will be illustrated with examples that emphasize their real-world applicability.He will start by focusing on fast and frugal trees (FFT),which classify objects into one of two categories through a sequence of tests.He will then discuss two projects carried out in collaboration with Shenghua Luan and Gerd Gigerenzer.The first explores how signal detection theory can help us to better understand the performance of FFT’s.The second project introduces Δ-Inference,a new lexicographic model for paired comparison,which stops cue search when the difference between the cue values of the two options exceeds an aspiration level Δ.In simulated and real task environments,we found that the accuracy of Δ-Inference peaks at a value of Δ that on average is close to zero.Furthermore,despite rarely searching more than one cue,Δ-Inference achieves as high a level of prediction accuracy as linear regression.Both FFT’s and Δ-Inference illustrate that when making inferences in the real world,it can pay to ignore information.