Author Archives: Ryan Watkins

https://psyarxiv.com/jv6rb/ Abstract Algorithms are increasingly employed to provide highly accurate advice and recommendations across domains, yet in many cases people tend to prefer human advisors. Studies to date have focused mainly on the advisor’s perceived competence and the outcome of … Continued

We propose that individuals incorrectly interpret their accuracy in predicting an event as an indication that they understand the event’s underlying mechanism or process. We term this illusion prediction-comprehension bias (PCB) and conceptually locate it within the frameworks of attribute … Continued

Rapid technological advancements and global workforce aging shape the future of work. Drawing on the technology acceptance model, our study aims to connect the literature on aging with the research on technology use in organizations. At its heart, the technology … Continued

arxiv.org/pdf/2205.05682.pdf Human collaboration with systems within the Computational Creativity (CC) field is often restricted to shallow interactions, where the creative processes, of systems and humans alike, are carried out in isolation, without any (or little) intervention from the user, and … Continued

After-effects on cognition—where a prior activity either benefits or hinders subsequent cognitive performance—are empirically inconsistent. Do people have insight into when their subjective energy and cognition will be helped or hurt by engaging in prior activities? Studies 1a and 1b … Continued

Trust calibration is essential in AI-assisted decision-making tasks. If human users understand the reasons for a prediction of an AI model, they can assess whether or not the prediction is reasonable. Especially for high-risk tasks like mushroom hunting (where a … Continued

Much literature has shown that prompt-based learning is an efficient method to make use of the large pre-trained language model. Recent works also exhibit the possibility of steering a chatbot’s output by plugging in an appropriate prompt. Gradient-based methods are … Continued

This work proposes a framework that incorporates trust in an ad hoc teamwork scenario with human-agent teams, where an agent must collaborate with a human to perform a task. During the task, the agent must infer, through interactions and observations, … Continued