Ethical issues in using ambient intelligence in health-care settings

Nicole Martinez-Martin; Zelun Luo; Amit Kaushal; Ehsan Adeli; Albert Haque; Sara S Kelly; Sarah Wieten; Mildred K Cho; David Magnus; Li Fei-Fei; Kevin Schulman; Arnold Milstein

doi:10.1016/S2589-7500(20)30275-2

Ethical issues in using ambient intelligence in health-care settings

Lancet Digit Health. 2021 Feb;3(2):e115-e123. doi: 10.1016/S2589-7500(20)30275-2. Epub 2020 Dec 21.

Authors

Nicole Martinez-Martin¹, Zelun Luo², Amit Kaushal³, Ehsan Adeli⁴, Albert Haque², Sara S Kelly⁵, Sarah Wieten⁶, Mildred K Cho⁶, David Magnus⁶, Li Fei-Fei⁷, Kevin Schulman⁵, Arnold Milstein⁵

Affiliations

¹ Center for Biomedical Ethics, Stanford University, Stanford, CA, USA. Electronic address: [email protected].
² Department of Computer Science, Stanford University, Stanford, CA, USA.
³ Department of Bioengineering, Stanford University, Stanford, CA, USA.
⁴ Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Department of Computer Science, Stanford University, Stanford, CA, USA.
⁵ Clinical Excellence Research Center, Department of Medicine, Stanford University, Stanford, CA, USA.
⁶ Center for Biomedical Ethics, Stanford University, Stanford, CA, USA.
⁷ Stanford Institute for Human-Centered Artificial Intelligence, Stanford University, Stanford, CA, USA.

Abstract

Ambient intelligence is increasingly finding applications in health-care settings, such as helping to ensure clinician and patient safety by monitoring staff compliance with clinical best practices or relieving staff of burdensome documentation tasks. Ambient intelligence involves using contactless sensors and contact-based wearable devices embedded in health-care settings to collect data (eg, imaging data of physical spaces, audio data, or body temperature), coupled with machine learning algorithms to efficiently and effectively interpret these data. Despite the promise of ambient intelligence to improve quality of care, the continuous collection of large amounts of sensor data in health-care settings presents ethical challenges, particularly in terms of privacy, data management, bias and fairness, and informed consent. Navigating these ethical issues is crucial not only for the success of individual uses, but for acceptance of the field as a whole.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Review

MeSH terms

Algorithms
Ambient Intelligence*
Bioethical Issues*
Data Collection
Data Management / ethics*
Digital Technology
Documentation / methods
Health Personnel
Humans
Informed Consent
Machine Learning
Patient Care / ethics*
Patient Care / methods
Patient Safety
Practice Guidelines as Topic
Privacy
Quality of Health Care
Telemedicine / ethics*
Telemedicine / methods
Telemetry / ethics*
Telemetry / methods
Wearable Electronic Devices

Abstract

Publication types

MeSH terms

Grants and funding