Evaluating the quality of machine learning explanations: A survey on methods and metrics
The most successful Machine Learning (ML) systems remain complex black boxes to end-
users, and even experts are often unable to understand the rationale behind their decisions …
users, and even experts are often unable to understand the rationale behind their decisions …
Trustworthy AI and robotics: Implications for the AEC industry
Human-technology interaction is concerned with trust as an inevitable user acceptance
requirement. As the applications of artificial intelligence (AI) and robotics emerge in the …
requirement. As the applications of artificial intelligence (AI) and robotics emerge in the …
How to evaluate trust in AI-assisted decision making? A survey of empirical methodologies
The spread of AI-embedded systems involved in human decision making makes studying
human trust in these systems critical. However, empirically investigating trust is challenging …
human trust in these systems critical. However, empirically investigating trust is challenging …
Understanding the effect of accuracy on trust in machine learning models
We address a relatively under-explored aspect of human-computer interaction: people's
abilities to understand the relationship between a machine learning model's stated …
abilities to understand the relationship between a machine learning model's stated …
When confidence meets accuracy: Exploring the effects of multiple performance indicators on trust in machine learning models
Previous research shows that laypeople's trust in a machine learning model can be affected
by both performance measurements of the model on the aggregate level and performance …
by both performance measurements of the model on the aggregate level and performance …
A case for humans-in-the-loop: Decisions in the presence of erroneous algorithmic scores
The increased use of algorithmic predictions in sensitive domains has been accompanied
by both enthusiasm and concern. To understand the opportunities and risks of these …
by both enthusiasm and concern. To understand the opportunities and risks of these …
It's complicated: The relationship between user trust, model accuracy and explanations in AI
Automated decision-making systems become increasingly powerful due to higher model
complexity. While powerful in prediction accuracy, Deep Learning models are black boxes …
complexity. While powerful in prediction accuracy, Deep Learning models are black boxes …
[HTML][HTML] Do you feel safe with your robot? Factors influencing perceived safety in human-robot interaction based on subjective and objective measures
Safety in human-robot interaction can be divided into physical safety and perceived safety,
where the latter is still under-addressed in the literature. Investigating perceived safety in …
where the latter is still under-addressed in the literature. Investigating perceived safety in …
Adaptive folk theorization as a path to algorithmic literacy on changing platforms
MA DeVito - Proceedings of the ACM on Human-Computer …, 2021 - dl.acm.org
The increased importance of opaque, algorithmically-driven social platforms (eg, Facebook,
YouTube) to everyday users as a medium for self-presentation effectively requires users to …
YouTube) to everyday users as a medium for self-presentation effectively requires users to …
Measuring and understanding trust calibrations for automated systems: a survey of the state-of-the-art and future directions
Trust has been recognized as a central variable to explain the resistance to using automated
systems (under-trust) and the overreliance on automated systems (over-trust). To achieve …
systems (under-trust) and the overreliance on automated systems (over-trust). To achieve …