Representing Normative Arguments in Genetic Counseling

Argumentation for Consumers of Healthcare

Volume

Papers from the 2006 AAAI Spring Symposium

Contents

Our research is on developing artificial intelligence-based approaches to help lay audiences to understand medical and other scientific arguments. Currently, we are developing a natural language generation system that will synthesize patient-tailored genetic counseling documents. In this position paper, we focus on two forms of internal representation to be used by the system: a qualitative causal probabilistic model for domain reasoning, and the representation of normative arguments, based upon the Toulmin model, in document planning.