AIMC Topic: Trust

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Key Information Influencing Patient Decision-Making About AI in Health Care: Survey Experiment Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI)-enabled devices are increasingly used in health care. However, there has been limited research on patients' informational preferences, including which elements of AI device labeling enhance patient understandi...

Deepening ideas vs. exploring new ones: AI strategy effects in human-AI creative collaboration.

PloS one
As artificial intelligence (AI) increasingly participates in creative processes, designing effective human-AI collaboration is crucial. This study addresses a fundamental question: Should an AI partner prioritize deepening existing ideas (exploitatio...

Investigating How Clinicians Form Trust in an AI-Based Mental Health Model: Qualitative Case Study.

JMIR human factors
BACKGROUND: Trust in artificial intelligence (AI) remains a critical barrier to the adoption of AI in mental health care. This study explores the formation of trust in an AI mental health model and its human-computer interface among clinicians at a w...

Stakeholder Criteria for Trust in Artificial Intelligence-Based Computer Perception Tools in Health Care: Qualitative Interview Study.

Journal of medical Internet research
BACKGROUND: Computer perception (CP) technologies hold significant promise for advancing precision mental health care systems, given their ability to leverage algorithmic analysis of continuous, passive sensing data from wearables and smartphones (eg...

Enhancing clinicians' trust in large language models via transparent source attribution: A randomized controlled evaluation in uro-oncology.

European journal of cancer (Oxford, England : 1990)
INTRODUCTION: Large language models (LLMs) are utilized to answer queries in urology and oncology, yet the performance is limited due to outdated data and missing source transparency, which undermines clinical reliability and therefore adoption. MATE...

Modelling the quantum-like dynamics of human reliability ratings in human-AI interactions by interaction-dependent Hamiltonians.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
We are rapidly moving to a future in which our information environment is saturated by artificial intelligence (AI), and humans and AI agents will routinely engage in shared decision making even in conditions of high uncertainty and risk (such as nat...

Understanding perceived ride safety and trust formation in robotaxi services under day and night conditions.

Scientific reports
This study investigates how passengers perceive ride safety and develop trust in Robotaxi services in the absence of human drivers, with a focus on differences between daytime and nighttime scenarios. Drawing on the Elaboration Likelihood Model (ELM)...

Gender, knowledge, and trust in artificial intelligence: a classroom-based randomized experiment.

Scientific reports
Artificial intelligence (AI) is increasingly utilized to provide real-time assistance and recommendations across a wide range of tasks in both education and workplace settings, especially since the emergence of Generative AI. However, it is unclear h...

Modeling public trust in AI cognitive capabilities using statistical and machine learning approaches.

Scientific reports
As artificial intelligence (AI) systems increasingly perform cognitive functions, assessing public trust in these capabilities is critical. This study investigates the impact of age, gender, and familiarity with AI on confidence in AI's ability to ma...

Compliance with Clinical Guidelines and AI-Based Clinical Decision Support Systems: Implications for Ethics and Trust.

Science and engineering ethics
Artificial intelligence (AI) is gradually transforming healthcare. However, despite its promised benefits, AI in healthcare also raises a number of ethical, legal and social concerns. Compliance by design (CbD) has been proposed as one way of address...