Providing Decision Support for Cosmogenic Isotope Dating
Rassbach, Laura (University of Colorado) | Bradley, Elizabeth (University of Colorado) | Anderson, Ken (University of Colorado)
Human experts in scientific fields routinely work with evidence that is noisy and untrustworthy, heuristics that are unproven, and possible conclusions that are contradictory. We present a deployed AI system, Calvin, for cosmogenic isotope dating, a domain that is fraught with these difficult issues. Calvin solves these problems using an argumentation framework and a system of confidence that uses two-dimensional vectors to express the quality of heuristics and the applicability of evidence. The arguments it produces are strikingly similar to published expert arguments.