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