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Modeling how people interact with search interfaces is core to the field of Interactive Information Retrieval. While various models have been proposed ranging from conceptual (e.g., Belkin’s ASK[12], Berry picking[11], Everyday-life information seeking, etc.) to theoretical (e.g., Information foraging theory[50], Economic theory[4], etc.), more recently there has been a body of working explore how people’s biases and the heuristics that they take influence how they search. This has led to the development of new models of the search process drawing upon Behavioural Economics and Psychology. This half day tutorial will provide a starting point for researchers seeking to learn more about information searching under uncertainty. The tutorial will be structured into two parts. First, we will provide an introduction of the biases and heuristics program put forward by Tversky and Kahneman [59] which assumes that people are not always rational. The second part of the tutorial will provide an overview of the types and space of biases in search [6, 42], before doing a deep dive into several specific examples and the impact of biases on different types of decisions (e.g., health/medical, financial etc.). The tutorial will wrap up with a discussion of some of the practical implication for how we can better design and evaluate IR systems in the light of cognitive biases.
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Search under Uncertainty: Cognitive Biases and Heuristics: A Tutorial on Testing, Mitigating and Accounting for Cognitive Biases in Search Experiments
Understanding how people interact with search interfaces is core to the field of Interactive Information Retrieval (IIR). While various models have been proposed (e.g., Belkin's ASK, Berry picking, Everyday-life information seeking, Information foraging theory, Economic theory, etc.), they have largely ignored the impact of cognitive biases on search behaviour and performance. A growing body of empirical work exploring how people's cognitive biases influence search and judgments, has led to the development of new models of search that draw upon Behavioural Economics and Psychology. This full day tutorial will provide a starting point for researchers seeking to learn more about information seeking, search and retrieval under uncertainty. The tutorial will be structured into three parts. First, we will provide an introduction of the biases and heuristics program put forward by Tversky and Kahneman [60] (1974) which assumes that people are not always rational. The second part of the tutorial will provide an overview of the types and space of biases in search,[5, 40] before doing a deep dive into several specific examples and the impact of biases on different types of decisions (e.g., health/medical, financial). The third part will focus on a discussion of the practical implication regarding the design and evaluation human-centered IR systems in the light of cognitive biases - where participants will undertake some hands-on exercises.
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- Award ID(s):
- 2106152
- PAR ID:
- 10543489
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400704314
- Page Range / eLocation ID:
- 3013 to 3016
- Format(s):
- Medium: X
- Location:
- Washington DC USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3626772.3661382
