Towards Detecting and Mitigating Cognitive Bias in Spoken Conversational Search

被引:0
|
作者
Ji, Kaixin [1 ]
Cherumanal, Sachin Pathiyan [1 ]
Trippas, Johanne R. [1 ]
Hettiachchi, Danula [1 ]
Salim, Flora D. [2 ]
Scholer, Falk [1 ]
Spina, Damiano [1 ]
机构
[1] RMIT Univ, Melbourne, Vic, Australia
[2] Univ New South Wales, Sydney, NSW, Australia
来源
PUBLICATION OF THE 26TH ACM INTERNATIONAL CONFERENCE ON MOBILE HUMAN-COMPUTER INTERACTION, MOBILEHCI 2024 ADJUNCT PROCEEDINGS | 2024年
基金
澳大利亚研究理事会;
关键词
Cognitive Bias; Spoken Conversational Search; Information Seeking; Physiological Signals; Wearable Sensors; Experimental Design; INFORMATION; EEG; COMPREHENSION; DISSONANCE; NEUROIS;
D O I
10.1145/3640471.3680245
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页数:10
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