CAREER: Intelligent Generation of Text and Information Graphics* Motivation: vital technical information involving scientific or medical arguments may be difficult for lay person to grasp Proposal: use AI to help technical experts produce “user-friendly” arguments in text and/or graphics use HCI methods to ensure effectiveness build demonstration system (GenIE) for genetic counselors *This material is based upon work supported by the National Science Foundation under Grant No. 0132821. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

The Genetic Counselor Meets with clients Informational/educational role Explanation of diagnosis of genetic condition Explanation of inheritance risks General explanation of background on genetics Counseling role Writes summary letter (1-2 pages) for client

Client Issues Complex Subject Emotional Distress probability and statistics hypothetical outcomes causality scientific and medical terminology diagrams may help Emotional Distress Reader’s ability to comprehend (innumeracy) Rapidly changing information

GenIE: Genetics Intelligent Editor Goals: NOT to replace human counselor Reduce counselor’s effort artificial intelligence creates 1st draft of letter human counselor may revise or reject GenIE’s draft Design online presentation; client benefits: supplementary graphics and animation links to other resources automatic updates

Multiple Research Methods Goal: Evaluate presentation techniques under controlled conditions in lab HCI Experiments Computational Model Building GenIE Goal: concrete implementation of ideas for demonstration and evaluation Goal: develop widely applicable computational (AI) techniques for generating arguments Corpus Analysis Goal: study corpus to understand how human authors communicate technical arguments

Research Methods: HCI Experiments Before: Formally evaluate effectiveness of communication techniques before computational models created, e.g.: How does layout of document affect comprehension of arguments? What types of information to present in text, in graphics, or both? Graphical depiction of argument structure After: Evaluate communicative effectiveness of presentations created by GenIE ablation experiments to identify which factors contribute or detract from communicative effectiveness

Research Methods: Corpus Analysis Corpus Acquisition (text and graphics) genetic counseling summary letters, client education documents (print and web) Qualitative Analysis types of information & graphic techniques analysis of argumentation (ex. predictive, diagnostic, value-based, Toulmin-style, dialectical) Computational Linguistics Analysis develop coding scheme with intercoder reliability manually encode corpus manual and automated discovery of communication techniques “evolved” by human authors

Research Methods: Computational Models Develop AI methods to represent the underlying scientific arguments and reasoning of the experts predict the audience’s potential problems in understanding, e.g., complexity of causal explanation emotionally disturbing information reason about content (both text & graphics), organization, and layout to avoid predicted problems generate text and graphics based on above

Analysis of Argumentation in Corpus Argumentation: discourse that weighs evidence and presents multiple points of view An important dimension of argumentation in letters in corpus: diagnostic and predictive reasoning hearing loss was caused by mutation in gene (GJB2) if HD, then chance that others in family are affected Those parts of letter can be represented by Bayesian (belief) network

Bayesian Network History/proband Age: child History/mother family history of deafness: no Genotype/mother one abnormal copy of gene GJB2 Genotype/father 2 abnormal copies of gene GJB2 Observable - predispositional Observable -evidential Non-Observable Node Key: 50% 50% Genotype/proband 2 abnormal copies of gene GJB2 Genotype/sibling 2 abnormal copies of gene GJB2 May increase risk Causal Links: Biochemistry/proband Connexin 26: abnormal Test/proband Physiology/probandnormal chemical equilibrium:no Result/proband GJB2 test positive Symptom/proband deafness Finding/proband facial defects: no Symptom/sibling deafness Symptom/father deafness

GenIE Project Summary Building demonstration system (GenIE) to help genetic counselors write letters Using HCI to ensure effectiveness of general argument presentation techniques Using AI to to model expert’s reasoning and argumentation strategies Techniques will be applicable in many domains to problem of computer-assisted or automatic multimedia generation of effective technical arguments for lay audience