Live Like Nobody Is Watching

Author:

Ho Anita1

Affiliation:

1. Clinical Associate Professor at the Centre for Applied Ethics, University of British Columbia

Abstract

Abstract Respect for patient autonomy and data privacy is generally accepted as one of the foundational Western bioethical values. Nonetheless, as our society embraces expanding forms of personal and health monitoring, particularly in the context of an aging population and the increasing prevalence of chronic diseases, questions abound how artificial intelligence (AI) may change the way we define or understand what it means to live a free and healthy life. Drawing on different use cases of AI health monitoring, this book explores the socio-relational contexts that frame the promotion of AI health monitoring, as well as the potential consequences of such monitoring for people’s autonomy. It argues that the evaluation, design, and implementation of AI health monitoring should be guided by a relational conception of autonomy, which addresses both people’s capacity to exercise their agency and broader issues of power asymmetry and social justice. It explores how interpersonal and socio-systemic conditions shape the cultural meanings of personal responsibility, healthy living/aging, trust, and caregiving. These norms in turn structure the ethical space within which expectations regarding predictive analytics, risk tolerance, privacy, self-care, and trust relationships are expressed. Through an analysis of home health monitoring for older and disabled adults, direct-to-consumer health monitoring devices, and medication adherence monitoring, this book proposes ethical strategies at both the professional and systemic levels that can help preserve and promote people’s relational autonomy in the digital era.

Publisher

Oxford University PressNew York

Reference517 articles.

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2. Binyam Negussie Desta, Ashok Chaurasia, and Shanil Ebrahim. “The Use of Artificially Intelligent Self-Diagnosing Digital Platforms by the General Public: Scoping Review.”;JMIR Medical Informatics

3. Defining and Measuring Primary Medication Nonadherence: Development of a Quality Measure.;Journal of Managed Care & Specialty Pharmacy

4. Machine Learning and Health Care Disparities in Dermatology.;JAMA Dermatology,2018

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