ALIED: Humans as adaptive lie detectors

People make for poor lie detectors. They have accuracy rates comparable to a coin toss, and come with a set of systematic biases that sway the judgment. This pessimistic view stands in contrast to research showing that people make informed decisions that adapt to the context they operate in. The current article proposes a new theoretical direction for lie detection research. I argue that lie detectors make informed, adaptive judgments in a low-diagnostic world. This Adaptive Lie Detector (ALIED) account is outlined by drawing on supporting evidence from across various psychological literatures. The account is contrasted with longstanding and more recent accounts of the judgment process, which propose that people fall back on default ways of thinking. Limitations of the account are considered, and future research directions are outlined

Inferring Others' Hidden Thoughts: Smart Guesses in a Low Diagnostic World

People are biased toward believing that what others say is what they truly think. This effect, known as the truth bias, has often been characterized as a judgmental error that impedes accuracy. We consider an alternative view: that it reflects the use of contextual information to make the best guess when the currently available information has low diagnosticity. Participants learnt the diagnostic value of four cues, which were present during truthful statements between 20% and 80% of the time. Afterwards, participants were given contextual information: either that most people would lie or that most would tell the truth. We found that people were biased in the direction of the context information when the individuating behavioral cues were nondiagnostic. As the individuating cues became more diagnostic, context had less to no effect. We conclude that more general context information is used to make an informed judgment when other individuating cues are absent. That is, the truth bias reflects a smart guess in a low diagnostic world