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UID:HFESHCS_2024 International Symposium on Human Factors and Ergonomics i
 n Health Care_sess128_POST268@linklings.com
SUMMARY:PS10 - Non-Human AI Personas: Bridging the Gap in AI-UX for Health
 care
DESCRIPTION:Poster Presentation\n\nJohn Brown and Tim Arnold (Department o
 f Veterans Affairs)\n\nAbstract—Advocates for Artificial Intelligence (AI)
  technologies within healthcare systems are promising prospects for enhanc
 ing patient care. Yet, it simultaneously introduces a myriad of challenges
  concerning Human Factors Engineering (HFE) and Human-Computer Interaction
  (HCI). This paper presents a groundbreaking conceptual framework, termed 
 Non-Human AI Personas, to unify the mental models that healthcare provider
 s and patients employ when interacting with AI systems. Through the utiliz
 ation of Non-Human AI Personas, this work identifies solutions to extant c
 hallenges in healthcare AI-UX, such as system explainability, data privacy
  ethics, universal design, and patient safety. By delineating actionable s
 teps derived from the persona-based framework, this paper significantly co
 ntributes to improving the safety, efficacy, and efficiency of AI adoption
  in healthcare settings.\n\nKeywords--Artificial Intelligence, Healthcare,
  Human Factors Engineering (HFE), Human-Computer Interaction (HCI), User E
 xperience (UX), Non-Human AI Personas, Data Privacy, Explainability, Safet
 y, Accessibility\n\nI. INTRODUCTION\nPossible benefits of AI in Healthcare
 \nThe accelerated integration of Artificial Intelligence (AI) into healthc
 are systems marks a significant paradigm shift in the delivery of medical 
 services. AI technologies offer transformative solutions that augment trad
 itional healthcare practices, ranging from predictive analytics in patient
  diagnosis to real-time data interpretation during surgeries (Jiang et al.
 , 2017)[1]. The confluence of AI and healthcare aims to augment clinical d
 ecision-making, optimize workflows, and may ultimately enhance patient out
 comes (Davenport & Kalakota, 2019)[2]. However, these technologies could a
 lso introduce risk to patient safety, healthcare practitioners, organizati
 ons, and national healthcare infrastructure.\n\nStatement of the Problem\n
 Despite the promising advancements and potential pitfalls, the application
  of AI in healthcare faces some complexities and challenges already well d
 escribed and studied in some academic circles. Specifically, issues relate
 d to Human Factors Engineering (HFE) and Human-Computer Interaction (HCI) 
 have surfaced as significant roadblocks to the unbridled utilization of AI
  in clinical settings (Carayon et al., 2015)[3]. The opacity of algorithmi
 c processes, the ethical maze surrounding data privacy, and the overarchin
 g necessity for universal accessibility stand as prominent obstacles (Ribe
 iro et al., 2016)[4].\n\nObjectives\nThis work and paper aims to address t
 hese multi-dimensional challenges by introducing a newer conceptual framew
 ork: Non-Human AI Personas. The paper seeks to validate the efficacy of em
 ploying these personas to enhance the AI-UX (User Experience) in healthcar
 e settings through rigorous research and analysis. The ultimate goal is to
  provide actionable insights on how we might continue to extend the use of
  Human Factors practices and principles in designing, evaluating, and impl
 ementing AI technologies, thereby improving healthcare delivery safety, ef
 ficacy, and efficiency (Holden et al., 2013)[5].\n\nApproach (or Methods)\
 nThis paper employs a multi-method approach to validate the efficacy of No
 n-Human AI Personas in enhancing the AI-UX (User Experience) within health
 care settings. The methodology includes both qualitative and quantitative 
 methods, such as interviews, surveys, and data analytics. We relied on a m
 odified persona creation process by pulling data from multiple sources and
  derived archetypes. We will describe design considerations and challenges
  for distilling draft personas from derived archetypes, validating them wi
 th stakeholders, and publishing them. Future and ongoing work will include
  piloting the personas by using them in journey maps and other processes t
 o improve and assess for risks. The aim is to provide a comprehensive unde
 rstanding of how these personas can be effectively integrated into healthc
 are systems to improve safety, efficacy, and efficiency.\n\nDiscussion\nWh
 ile the research provides promising insights into the application of Non-H
 uman AI Personas, it is essential to acknowledge its limitations. One sign
 ificant constraint is the limited scope of healthcare settings examined, w
 hich may not be universally applicable. Additionally, the study relies on 
 self-reported data, which could introduce bias.\nFuture research should ai
 m to expand the scope of healthcare settings and incorporate more objectiv
 e measures. There is also a need for longitudinal studies to assess the lo
 ng-term impact of implementing Non-Human AI Personas in healthcare systems
 .\n\nTrack: Digital Health, Simulation and Education, Hospital Environment
 s, Medical and Drug Delivery Devices, Patient Safety Research and Initiati
 ves
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