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Trust

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Trustworthy Artificial Intelligence in Dentistry: Learnings from the EU AI Act.

Journal of dental research
Artificial intelligence systems (AISs) gain relevance in dentistry, encompassing diagnostics, treatment planning, patient management, and therapy. However, questions about the generalizability, fairness, and transparency of these systems remain. Regu...

Patient Consent and The Right to Notice and Explanation of AI Systems Used in Health Care.

The American journal of bioethics : AJOB
Given the need for enforceable guardrails for artificial intelligence (AI) that protect the public and allow for innovation, the U.S. Government recently issued a Blueprint for an AI Bill of Rights which outlines five principles of safe AI design, us...

Towards generalizable face forgery detection via mitigating spurious correlation.

Neural networks : the official journal of the International Neural Network Society
The continuous advancement of face forgery techniques has caused a series of trust crises, posing a significant menace to information security and personal privacy. In response, deep learning is being employed to develop effective detection methods t...

Justifying Our Credences in the Trustworthiness of AI Systems: A Reliabilistic Approach.

Science and engineering ethics
We address an open problem in the philosophy of artificial intelligence (AI): how to justify the epistemic attitudes we have towards the trustworthiness of AI systems. The problem is important, as providing reasons to believe that AI systems are wort...

How sociodemographic factors relate to trust in artificial intelligence among students in Poland and the United Kingdom.

Scientific reports
The article aims to determine the sociodemographic factors associated with the level of trust in artificial intelligence (AI) based on cross-sectional research conducted in late 2023 and early 2024 on a sample of 2098 students in Poland (1088) and th...

Care to Explain? AI Explanation Types Differentially Impact Chest Radiograph Diagnostic Performance and Physician Trust in AI.

Radiology
Background It is unclear whether artificial intelligence (AI) explanations help or hurt radiologists and other physicians in AI-assisted radiologic diagnostic decision-making. Purpose To test whether the type of AI explanation and the correctness and...

Why we should talk about institutional (dis)trustworthiness and medical machine learning.

Medicine, health care, and philosophy
The principle of trust has been placed at the centre as an attitude for engaging with clinical machine learning systems. However, the notions of trust and distrust remain fiercely debated in the philosophical and ethical literature. In this article, ...

Machine learning-based prediction models in medical decision-making in kidney disease: patient, caregiver, and clinician perspectives on trust and appropriate use.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This study aims to improve the ethical use of machine learning (ML)-based clinical prediction models (CPMs) in shared decision-making for patients with kidney failure on dialysis. We explore factors that inform acceptability, interpretabi...

Patients' attitudes toward artificial intelligence in dentistry and their trust in dentists.

Oral radiology
OBJECTIVES: This study intended to evaluate patients' attitudes toward the use of AI in dental radiographic detection of occlusal caries and the impact of AI-based diagnosis on their trust in dentists.