1. 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 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.

2. 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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. Bayesian Network History/proband Age: child
History/mother family history of deafness: no
Genotype/mother one abnormal copy of gene GJB2
Genotype/father 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 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

11. 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