Towards Detecting and Mitigating Cognitive Bias in Spoken Conversational Search

Abstract

Spoken Conversational Search (SCS) poses unique challenges in understanding user-system interactions due to the absence of visual cues, and the complexity of less structured dialogue. Tackling the impacts of cognitive bias in today’s information-rich online environment, especially when SCS becomes more prevalent, this paper integrates insights from information science, psychology, cognitive science, and wearable sensor technology to explore potential opportunities and challenges in studying cognitive biases in SCS. It then outlines a framework for experimental designs with various experiment setups to multimodal instruments. It also analyzes data from an existing dataset as a preliminary example to demonstrate the potential of this framework and discuss its implications for future research. In the end, it discusses the challenges and ethical considerations associated with implementing this approach. This work aims to provoke new directions and discussion in the community and enhance understanding of cognitive biases in Spoken Conversational Search.

Publication
Adjunct Publication of the 26th International Conference on Human-Computer Interaction with Mobile Devices and Services