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Between Skepticism and Uncritical Acceptance – How an Optimal Level of Trust in Artificial Intelligence Can Ease the Burden on Healthcare

Identification

Public canonical key
doi:10.5771/2701-4193-2025-2-143
Authors
Florian Zimmermann · Svenja Pelgrim · Andi Hamza
Reported year
2025
Reported language
en
Source type
article
First detected
2026-11-09T19:10:05.536740+00:00
Last metadata observation
2026-11-09T19:10:05.536740+00:00
Last HTTP verification
Not checked

Documentary abstract — original language

Artificial Intelligence (AI) is a key driver of the ongoing transformation in healthcare. It can support physicians in making diagnoses and help reduce medical errors. Studies indicate that the correct use of AI enhances the efficiency and performance of healthcare systems, thereby alleviating the burden on medical professionals, improving access to healthcare for all social groups, and strengthening public welfare. At the same time, many physicians exhibit limited trust in AI, preventing the full realization of its potential. However, excessive trust in AI also poses risks, such as the uncritical adoption of erroneous medical recommendations. In this context, this paper explores how an appropriate level of trust in AI can be established to optimize its performance while mitigating risks, ultimately contributing to a sustainable improvement in healthcare.

Identifiers

OPENALEX
W4412141192
DOI
10.5771/2701-4193-2025-2-143

Documentary context

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Scholarship
Source-reported types
article

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Sources

OpenAlex · Record 1 · Record 2

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Cite this reference

Florian Zimmermann; Svenja Pelgrim; Andi Hamza. Between Skepticism and Uncritical Acceptance – How an Optimal Level of Trust in Artificial Intelligence Can Ease the Burden on Healthcare. 2025. https://doi.org/10.5771/2701-4193-2025-2-143

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APA
Florian Zimmermann; Svenja Pelgrim; Andi Hamza. (2025). Between Skepticism and Uncritical Acceptance – How an Optimal Level of Trust in Artificial Intelligence Can Ease the Burden on Healthcare. https://doi.org/10.5771/2701-4193-2025-2-143
Chicago
Florian Zimmermann; Svenja Pelgrim; Andi Hamza. Between Skepticism and Uncritical Acceptance – How an Optimal Level of Trust in Artificial Intelligence Can Ease the Burden on Healthcare. 2025. https://doi.org/10.5771/2701-4193-2025-2-143
ISO 690
Florian Zimmermann; Svenja Pelgrim; Andi Hamza. Between Skepticism and Uncritical Acceptance – How an Optimal Level of Trust in Artificial Intelligence Can Ease the Burden on Healthcare. 2025. https://doi.org/10.5771/2701-4193-2025-2-143

UDTR Global Rights of Nature Legal Library. Between Skepticism and Uncritical Acceptance – How an Optimal Level of Trust in Artificial Intelligence Can Ease the Burden on Healthcare. Documentary record: https://www.declarationuniverselledesdroitsdelarbre.org/global-rights-of-nature-radar/reference/r-e6b44dfc0ac4ba273043cacda2edcb9a/ · Last HTTP verification: not performed

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Field provenance and record version

Version bed0382fd0b1057d · udtr-reference-1.1.2

Title
OpenAlex · source · 2026-11-09T19:10:05.536740+00:00
Authors
OpenAlex · source · 2026-11-09T19:10:05.536740+00:00
Year
OpenAlex · source · 2026-11-09T19:10:05.536740+00:00
Identifiers
OpenAlex · source · 2026-11-09T19:10:05.536740+00:00
Source URL
OpenAlex · source · 2026-11-09T19:10:05.536740+00:00
Source-reported author ORCID
OpenAlex · source · 2026-11-09T19:10:05.536740+00:00

History tracks record metadata and does not certify the state of the law.

668422f2bf0efadf · 2026-11-09T19:10:05.536740+00:00

2c5224b0ba227dfd · 2026-11-09T19:10:05.536740+00:00

75e4a8130aa3a6b7 · 2026-11-09T19:10:05.536740+00:00

bed0382fd0b1057d · 2026-11-09T19:10:05.536740+00:00

Frozen-version metadata

Research dossiers and documentary relations

Andi Hamza

Florian Zimmermann

Svenja Pelgrim

Source roles

Discovery source · https://doi.org/10.5771/2701-4193-2025-2-143

Discovery source · https://openalex.org/W4412141192

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