AIMC Topic: Trust

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Clouds on the horizon: clinical decision support systems, the control problem, and physician-patient dialogue.

Medicine, health care, and philosophy
Artificial intelligence-based clinical decision support systems have a potential to improve clinical practice, but they may have a negative impact on the physician-patient dialogue, because of the control problem. Physician-patient dialogue depends o...

When the bot walks the talk: Investigating the foundations of trust in an artificial intelligence (AI) chatbot.

Journal of experimental psychology. General
The concept of trust in artificial intelligence (AI) has been gaining increasing relevance for understanding and shaping human interaction with AI systems. Despite a growing literature, there are disputes as to whether the processes of trust in AI ar...

Facilitating Trust Calibration in Artificial Intelligence-Driven Diagnostic Decision Support Systems for Determining Physicians' Diagnostic Accuracy: Quasi-Experimental Study.

JMIR formative research
BACKGROUND: Diagnostic errors are significant problems in medical care. Despite the usefulness of artificial intelligence (AI)-based diagnostic decision support systems, the overreliance of physicians on AI-generated diagnoses may lead to diagnostic ...

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...

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...

Entrustment and EPAs for Artificial Intelligence (AI): A Framework to Safeguard the Use of AI in Health Professions Education.

Academic medicine : journal of the Association of American Medical Colleges
In this article, the authors propose a repurposing of the concept of entrustment to help guide the use of artificial intelligence (AI) in health professions education (HPE). Entrustment can help identify and mitigate the risks of incorporating genera...

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, ...

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.

Exploring Nurses' Behavioural Intention to Adopt AI Technology: The Perspectives of Social Influence, Perceived Job Stress and Human-Machine Trust.

Journal of advanced nursing
AIM: This study examines how social influence, human-machine trust and perceived job stress affect nurses' behavioural intentions towards AI-assisted care technology adoption from a new perspective and framework. It also explores the interrelationshi...