- Title
- Artificial Intelligence in nursing: trustworthy or reliable?
- Creator
- Higgins, Oliver; Chalup, Stephan K.; Wilson, Rhonda L.
- Relation
- Journal of Research in Nursing Vol. 29, Issue 2, p. 143-153
- Publisher Link
- http://dx.doi.org/10.1177/17449871231215696
- Publisher
- Sage
- Resource Type
- journal article
- Date
- 2024
- Description
- Background: Trustworthiness in Artificial Intelligence (AI) innovation is a priority for governments, researchers and clinicians; however, clinicians have highlighted trust and confidence as barriers to their acceptance of AI within a clinical application. While there is a call to design and develop AI that is considered trustworthy, AI still lacks the emotional capability to facilitate the reciprocal nature of trust. Aim: This paper aims to highlight and discuss the enigma of seeking or expecting trust attributes from a machine and, secondly, reframe the interpretation of trustworthiness for AI through evaluating its reliability and validity as consistent with the use of other clinical instruments. Results: AI interventions should be described in terms of competence, reliability and validity as expected of other clinical tools where quality and safety are a priority. Nurses should be presented with treatment recommendations that describe the validity and confidence of prediction with the final decision for care made by nurses. Future research should be framed to better understand how AI is used to deliver care. Finally, there is a responsibility for developers and researchers to influence the conversation about AI and its power towards improving outcomes. Conclusion: The sole focus on demonstrating trust rather than the business-as-usual requirement for reliability and validity attributes during implementation phases may result in negative experiences for nurses and clinical users. Implications for practice: This research will have significant implications for the way in which future nursing is practised. As AI-based systems become a part of routine practice, nurses will be faced with an increasing number of interventions that require complex trust systems to operate. For any AI researchers and developers, understanding the complexity of trust and creditability in the use of AI in nursing will be crucial for successful implementation. This research will contribute and assist in understanding nurses’ role in this change.
- Subject
- artificial intelligence; machine learning; mental health; nursing; psychosis; technology
- Identifier
- http://hdl.handle.net/1959.13/1517654
- Identifier
- uon:57141
- Identifier
- ISSN:1744-9871
- Rights
- x
- Language
- eng
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