Artificial Intelligence and Nursing: Freedom From the Mundane or Subservience to a New Nobility
Abstract
AIM: To explore the notion of post-humanism and the impact of artificial intelligence (AI) on society, nursing and healthcare. DESIGN: Discursive paper. METHODS: Critical reflection on concepts relating to post-humanism and the impact of AI, sourced from contemporary and established literature. DATA SOURCES: Information was drawn from a wide range of empirical and theoretical resources, including health services research through to sociology and philosophy, including newspapers, popular science as well as peer reviewed articles. RESULTS: At the extremes of opinion, AI is either feared as presaging the end of our current civilisation, or lauded as the beginning of a new leisure age. For many, reservations include: a lack of AI intervention transparency, rendering accurate description, replication and implementation impossible; the overwhelming presence of 'spin' overstating impacts for patients; the replacement of relationship-based person-centred fundamental care by 'algorithm-based care' in nursing defined by the language of precision diagnostics and treatment; AI as the new unchallenged "King, Priest and Feudal Lord", leading to professional infantilisation and a loss of critical thinking; the cementation of human exceptionalism and the right to exploit, or destroy, our world. CONCLUSION: AI not only presents a potential benefit but also a severe threat to a model of fundamental nursing care defined by patient/nurse relationships and patient-centredness, carried out by nurses applying the principles of critical reasoning. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Defending nursing in an age of AI will require nurses to reiterate anew the importance of relationship-based person-centred fundamental care. Where AI-based nursing interventions are proposed, nurses, whether registered or not, must remain critical thinkers, appraise the source data and guard against descending into unthinking subservience to machine-generated 'facts' of unchecked provenance. REPORTING METHOD: None required. PATIENT OR PUBLIC CONTRIBUTION: This article did not include patient or public involvement in its design, conduct, or reporting.
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Authors: David Richards
Institutions: University of Exeter, Western Norway University of Applied Sciences