Co-creating Humanistic AI AgeTech to Support Dynamic Care Ecosystems: A Preliminary Guiding Model.

Journal: The Gerontologist
PMID:

Abstract

As society rapidly digitizes, successful aging necessitates using technology for health and social care and social engagement. Technologies aimed to support older adults (e.g., smart homes, assistive robots, wheelchairs) are increasingly applying artificial intelligence (AI), and thereby creating ethical challenges to technology development and use. The international debate on AI ethics focuses on implications to society (e.g., bias, equity) and to individuals (e.g., privacy, consent). The relational nature of care, however, warrants a humanistic lens to examine how "AI AgeTech" will shape, and be shaped by, social networks or care ecosystems in terms of their care actors (i.e., older adults, care partners, service providers); inter-actor relations (e.g., care decision making) and relationships (e.g., social, professional); and evolving care arrangements. For instance, if an older adult's reduced functioning leads actors to renegotiate their risk tolerances and care routines, smart homes or robots become more than tools that actors configure; they become semiautonomous actors, in themselves, with the potential to influence functioning and interpersonal relationships. As an experientially diverse, transdisciplinary working group of older adults, care partners, researchers, clinicians, and entrepreneurs, we co-constructed intersectional care experiences, to guide technology research, development, and use. Our synthesis contributes a preliminary guiding model for AI AgeTech innovation that delineates humanistic attributes, values, and design orientations, and captures the ethical, sociological, and technological nuances of dynamic care ecosystems. Our visual probes and recommended tools and techniques offer researchers, developers/innovators, and care actors concrete ways of using this model to promote successful aging in AI-enabled futures.

Authors

  • Amy S Hwang
    Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, Ontario, Canada.
  • Thomas Tannou
    Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud de l'Ile de Montréal, Montréal, Québec, Canada.
  • Jarshini Nanthakumar
    Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, Ontario, Canada.
  • Wendy Cao
    Independent Research Consultant, Toronto, Ontario, Canada.
  • Charlene H Chu
    Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada.
  • Ceren Zeytinoglu Atici
    Başlangıç Noktası (Be Node), Turkish Informatics Foundation, Istanbul, Turkey.
  • Kerseri Scane
    Independent Research Consultant, Toronto, Ontario, Canada.
  • Amanda Yu
    Independent Research Consultant, Toronto, Ontario, Canada.
  • Winnie Tsang
    Good Works Collective Inc., Toronto, Ontario, Canada.
  • Jennifer Chan
    Independent Research Consultant, Toronto, Ontario, Canada.
  • Paul Lea
    Independent Research Consultant, Toronto, Ontario, Canada.
  • Zelda Harris
    Independent Research Consultant, Toronto, Ontario, Canada.
  • Rosalie H Wang
    Intelligent Assistive Technology and Systems Lab,Dept. of Occupational Science & Occupational Therapy,University of Toronto,Toronto,Ontario M5G 1V7,Canada.