AIMC Topic: Trust
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Trustworthy and ethical AI-enabled cardiovascular care: a rapid review.
BMC medical informatics and decision making
Sep 4, 2024
BACKGROUND: Artificial intelligence (AI) is increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite the potential for AI to improve care, ethical concerns and mistrust in AI-enabled healthcare exist ...
Overtrust in AI Recommendations About Whether or Not to Kill: Evidence from Two Human-Robot Interaction Studies.
Scientific reports
Sep 4, 2024
This research explores prospective determinants of trust in the recommendations of artificial agents regarding decisions to kill, using a novel visual challenge paradigm simulating threat-identification (enemy combatants vs. civilians) under uncertai...
Encompassing trust in medical AI from the perspective of medical students: a quantitative comparative study.
BMC medical ethics
Sep 2, 2024
BACKGROUND: In the years to come, artificial intelligence will become an indispensable tool in medical practice. The digital transformation will undoubtedly affect today's medical students. This study focuses on trust from the perspective of three gr...
In human-machine trust, humans rely on a simple averaging strategy.
Cognitive research: principles and implications
Sep 2, 2024
With the growing role of artificial intelligence (AI) in our lives, attention is increasingly turning to the way that humans and AI work together. A key aspect of human-AI collaboration is how people integrate judgements or recommendations from machi...
Gaining Trust: Lessons and Opportunities for Artificial Intelligence in Health Care.
The Permanente journal
Aug 8, 2024
Navigating artificial intelligence in care homes: Competing stakeholder views of trust and logics of care.
Social science & medicine (1982)
Aug 5, 2024
The COVID-19 pandemic shed light on systemic issues plaguing care (nursing) homes, from staff shortages to substandard healthcare. Artificial Intelligence (AI) technologies, including robots and chatbots, have been proposed as solutions to such issue...
The Impact of Information Relevancy and Interactivity on Intensivists' Trust in a Machine Learning-Based Bacteremia Prediction System: Simulation Study.
JMIR human factors
Aug 1, 2024
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
Jul 31, 2024
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.)
Jul 26, 2024
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
Jul 25, 2024
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...
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