=Paper=
{{Paper
|id=Vol-3068/xpreface
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-3068/xpreface.pdf
|volume=Vol-3068
|authors=Thomas E. Doyle,Reza Samavi,Aisling Kelliher
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==None==
https://ceur-ws.org/Vol-3068/xpreface.pdf
Preface: AAAI-HUMAN 2021 Fall Symposium on Human Partnership
with Medical AI: Design, Operationalization, and Ethics
Thomas E. Doyle1,4, Reza Samavi2,4, Aisling Kelliher3
1McMaster University, Canada
2Ryerson University, Canada
3Virginia Tech, USA
4Vector Institute of Artificial Intelligence, Canada
1doylet@mcmaster.ca, 2samavi@ryerson.ca, 3aislingk@vt.edu
Abstract pain, clinician involvement for enhancing trust, and the pa-
The Human Partnership with Medical Artificial Intelligence: tient perspective on AI in their healthcare. In addition, round
Design, Operationalization, and Ethics AAAI symposium table discussions covered the future of medical AI partner-
was held virtually November 4-6, 2021. The goal of the sym- ship, enhancing trust in AI, and improving clinical adoption.
posium was to investigate our human relationship and part-
In addition to the talks, the symposium also ran a rapid mod-
nership with medical artificial intelligence, especially focus-
ing on challenges in design, operationalization, and ethics. ified Delphi to better understand the challenges of medical
AI partnership. Two questions were initially asked: 1) What
aspects (or characteristics) of AI implementation drive, or
Preface help gain, merited trust in clinical adoption?, and 2) How
the aspects (characteristics) identified can be operational-
Human interaction with artificial intelligence takes many
ized in clinical AI implementation? The responses were dis-
forms; however, the risk tolerance in a medical context is
cussed with the symposium participants for consensus and
very low. As academics and practitioners at this intersec-
then ranked based on complexity and importance. Rankings
tion, in fields such as medicine, engineering, computer sci-
were presented for further discussion and synthesis of con-
ence, psychology, and human factors, we each seek to con-
cepts. The outcome is expected to provide the community
tribute to improved clinical outcomes through intelligent de-
with insight and research directions with the greatest impact
cision support and prediction.
in the pursuit of improving human partnership with medical
The symposium brought together researchers and clini-
AI for improved clinical outcomes.
cians from a variety of AI backgrounds and perspectives.
Thomas E. Doyle and Aisling Kelliher served as co-chairs
Topics discussed were privacy preservation concerns using
of this symposium. The papers of the symposium were pub-
the natural language processing Bidirectional Encoder Rep-
lished as a CEUR-WS.org proceedings available through the
resentations from Transformers (BERT) with clinical data,
symposium web site aaai-human.ai.
multimodal explanations for decision support, interpretable
models for survival analysis, experts privileged information
under uncertainty, challenges to AI in clinical practice, au-
tomated medical text translation for different user types, and
intelligent tutoring for anatomical education. Keynotes by
Dr. Jenna Wiens (University of Michigan) and Dr. Jason
Corso (Steven Institute of Technology) presented From Di-
agnosis to Treatment - Augmenting Clinical Decision Mak-
ing with Artificial Intelligence, and Video Understanding in
the Clinic: Progress and Challenges, respectively. Guest
speakers shared their clinical AI experiences in chronic
Copyright © 2021 for this paper by its authors. Use permitted under Crea- its papers are published under the Creative Commons License Attribution
tive Commons License Attribution 4.0 International (CC BY 4.0). Copy- 4.0 International (CC BY 4.0)."
right © 2021 for the volume as a collection by its editors. This volume and