Day: November 5, 2021

ACSHF Forum, 2pm Monday Nov. 08: Anne Inger Mørtvedt and Lamia Alam (Meese 109 and via Zoom)

The Department of Cognitive and Learning Sciences will host two speakers at the next Applied Cognitive Science and Human Factors forum. Anne Inger Mørtvedt (PhD Student ACSHF) will present, “Information usability evaluation to increase implementation of injury prevention training in sports”, and Lamia Alam (PhD Student ACSHF) will present “Assessing cognitive empathy elements within the context of diagnostic AI chatbots”. The presentations will be from 2:00 to 3:00 p.m. Monday (November 8) in Meese 109 and via Zoom. Abstracts for the two presentations are as follows:

Anne Inger Mørtvedt

“Information usability evaluation to increase implementation of injury prevention training in sports”

Abstract: Several sports related injuries can be prevented through implementation of evidence-based injury prevention training (IPT). However, actual use remains very low – and lowest in rural and resource scarce areas. Coaches’ comprehension of the injury and prevention strategies has been identified as the main modifiable barrier for implementation of IPT. However, there is a lack of accessible and usable information to improve representative understanding or comprehension. We recently developed a brief animated video to fill this gap but formal usability assessment of this informational video has yet to be conducted. In this presentation, we aim to present our initial usability data and tentative next steps for developing a more usable educational animation with the ultimate goal of increasing the likelihood of IPT implementation in the target population.

Lamia Alam

“Assessing cognitive empathy elements within the context of diagnostic AI chatbots”  

Abstract: Empathy is an important element for any social relationship and it is also very important in patient-physician communication. There are many aspects and dimensions of empathy applicable in such communication. As Artificial Intelligence is being heavily deployed in healthcare, it is critical that there is a  shared understanding between patients and the AI systems if patients are directly interacting with those systems. But many of the emotional aspects of empathy may not be achievable by AI systems at present and cognitive empathy is the one that can genuinely be implemented through artificial intelligence in healthcare. We need a better understanding of the elements of cognitive empathy and how these elements can be utilized effectively. In this research, the goal was to investigate whether empathy elements actually make a difference to improve user perception of AI empathy.  We developed a scale “AI Cognitive Empathy Scale (AICES)” for that purpose and conducted a study where the experimental condition had both emotional and cognitive empathy elements together. The AICES scale demonstrated reasonable consistency, reliability, and validity, and overall, empathy elements improve the perceived empathy concern within diagnostic AI chatbots.