Building a better critic-recent empirical results

Critic engineering advances a theory of errors and repair strategies that helps a system collaborate with an expert during knowledge acquisition. The result is an expert critiquing system, or critic, designed to improve the collected knowledge. An implementable version of the critic-engineering methodology that includes first principles, generic question sets, and a library of error triggers and correction strategies is defined, and lessons learned about the methodology from applications and experiments in diverse domains are presented. The implementation of influencers, which offer positive criticisms before or during a task to help prevent biases before they occur, and debiasers, which use negative criticisms during or after a task to help correct a bias or error after it occurs, are discussed. Other implementations of critic engineering are also discussed.<>