AIMC Topic: Trust

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The Impact of Information Relevancy and Interactivity on Intensivists' Trust in a Machine Learning-Based Bacteremia Prediction System: Simulation Study.

JMIR human factors
BACKGROUND: The exponential growth in computing power and the increasing digitization of information have substantially advanced the machine learning (ML) research field. However, ML algorithms are often considered "black boxes," and this fosters dis...

Peer or tutor? The congruity effects of service robot role and service type on usage intention.

Acta psychologica
The invention of service robots has reduced the labor cost and improved enterprises' efficiency and service quality. However, it is still difficult to enhance consumers' intention to use robot-by-robot design efficiently. Based on social roles of ant...

The role of saliency maps in enhancing ophthalmologists' trust in artificial intelligence models.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: Saliency maps (SM) allow clinicians to better understand the opaque decision-making process in artificial intelligence (AI) models by visualising the important features responsible for predictions. This ultimately improves interpretability a...

Gender Differences in Letters of Recommendations and Personal Statements for Neurotology Fellowship over 10 Years: A Deep Learning Linguistic Analysis.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
OBJECTIVE: Personal statements (PSs) and letters of recommendation (LORs) are critical components of the neurotology fellowship application process but can be subject to implicit biases. This study evaluated general and deep learning linguistic diffe...

Trust criteria for artificial intelligence in health: normative and epistemic considerations.

Journal of medical ethics
Rapid advancements in artificial intelligence and machine learning (AI/ML) in healthcare raise pressing questions about how much users should trust AI/ML systems, particularly for high stakes clinical decision-making. Ensuring that user trust is prop...

AI-teaming: Redefining collaboration in the digital era.

Current opinion in psychology
Integrating artificial intelligence (AI) into human teams, forming human-AI teams (HATs), is a rapidly evolving field. This overview examines the complexities of team constellations and dynamics, trust in AI teammates, and shared cognition within HAT...

When Trustworthiness Meets Face: Facial Design for Social Robots.

Sensors (Basel, Switzerland)
As a technical application in artificial intelligence, a social robot is one of the branches of robotic studies that emphasizes socially communicating and interacting with human beings. Although both robot and behavior research have realized the sign...

Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: the role of human/artificial intelligence interaction.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Computer-aided diagnosis (CADx) for the optical diagnosis of colorectal polyps is thoroughly investigated. However, studies on human-artificial intelligence interaction are lacking. Our aim was to investigate endoscopists' trust ...

Emotional and cognitive trust in artificial intelligence: A framework for identifying research opportunities.

Current opinion in psychology
This article briefly summarizes trust as a multi-dimensional construct, and trust in AI as a unique but related construct. It argues that because trust in AI is couched within an economic landscape, these two frameworks should be combined to understa...

Clinicians and AI use: where is the professional guidance?

Journal of medical ethics
With the introduction of artificial intelligence (AI) to healthcare, there is also a need for professional guidance to support its use. New (2022) reports from National Health Service AI Lab & Health Education England focus on healthcare workers' und...