When people use web search engines to find information on debated topics, the search results they encounter can influence opinion formation and practical decision-making with potentially far-reaching consequences for the individual and society. However, current web search engines lack support for information-seeking strategies that enable responsible opinion formation, e.g., by mitigating confirmation bias and motivating engagement with diverse viewpoints. We conducted two preregistered user studies to test the benefits and risks of an intervention aimed at confirmation bias mitigation. In the first study, we tested the effect of warning labels, warning of the risk of confirmation bias, combined with obfuscations, hiding selected search results per default. We observed that obfuscations with warning labels effectively reduce engagement with search results. These initial findings did not allow conclusions about the extent to which the reduced engagement was caused by the warning label (reflective nudging element) versus the obfuscation (automatic nudging element). If obfuscation was the primary cause, this would raise concerns about harming user autonomy. We thus conducted a follow-up study to test the effect of warning labels and obfuscations separately. According to our findings, obfuscations run the risk of manipulating behavior instead of guiding it, while warning labels without obfuscations (purely reflective) do not exhaust processing capacities but encourage users to actively choose to decrease engagement with attitude-confirming search results. Therefore, given the risks and unclear benefits of obfuscations and potentially other automatic nudging elements to guide engagement with information, we call for prioritizing interventions that aim to enhance human cognitive skills and agency instead.

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An essential characteristic for unbiased and diligent information-seeking that can enable informed opinion formation and decision-making is intellectual humility (IH), the awareness of the limitations of one's knowledge and opinions. While researchers have recognized the potential to boost IH in individuals, the effect of such interventions on their search behavior, along with the broader significance of IH in the context of web search on debated topics remains unexplored. In this paper, we present the results of a preregistered user study (N = 299) that we conducted to (1) test the effect of three interventions that boost self-reported IH on opinionated individuals' search behavior and (2) explore the role of IH in the search process of opinionated individuals more broadly. IH-boosting interventions did not affect search behavior; we attribute this to the high familiarity of the search environment, prompting searchers to default to their usual search behavior. Still, explorations of the role of IH in the search process indicate that IH and IH-related search intentions should be considered as relevant factors in the pursuit of supporting unbiased and diligent search on debated topics. Based on our exploratory findings, we argue that future research should investigate interventions that are more directly integrated into the search process, as well as such that combine boosting IH with encouraging searchers to approach the search task in an IH-driven way and promoting transparency for appropriate reliance on the search system and ranking.

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People of low literacy could benefit from automated support when learning about societal participation. We design an Embodied Conversational Agent (ECA) ‘coach’ that can provide effective learning support to low-literate learners, develop a prototype virtual learning environment, and evaluate this prototype with low-literate end users. First, we inventory the learning support benefits of ECA coaching. Second, we update existing requirements to better specify functional demands for the coach ECA. Third, we write use cases and develop the prototype. Finally, we evaluate the prototype with low-literate users in a mixed-method within-subjects experiment. Results show that the coach influences the subjective learning experience: Participants report higher positive affect, higher user-system engagement, and increased self-efficacy regarding online banking. These results particularly apply to the domain of challenging information skills exercises. Caveats apply: One of four exercises was significantly more difficult than the other three; and coach support rules were not clearly formalized.

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Online debates allow for large-scale participation by users with different opinions, values, and backgrounds. While this is beneficial for democratic discourse, such debates often tend to be cognitively demanding due to the high quantity and low quality of non-expert contributions. High cognitive demand, in turn, can make users vulnerable to cognitive biases such as confirmation bias, hindering well-informed attitude forming. To facilitate interaction with online debates, counter confirmation bias, and nudge users towards engagement with online debate, we propose (1) summaries of the arguments made in the debate and (2) personalized persuasive suggestions to motivate users to engage with the debate summaries. We tested the effect of four different versions of the debate display (without summary, with summary and neutral suggestion, with summary and personalized persuasive suggestion, with summary and random persuasive suggestion) on participants' attitude-opposing argument recall with a preregistered user study (N = 212). The user study results show no evidence for an effect of either the summary or the personalized persuasive suggestions on participants' attitude-opposing argument recall. Further, we did not observe confirmation bias in participants' argument recall, regardless of the debate display. We discuss these observations in light of additionally collected exploratory data, which provides some pointers towards possible causes for the lack of significant findings. Motivated by these considerations, we propose two new hypotheses and ideas for improving relevant properties of the study design for follow-up studies.

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We have defined an interdisciplinary program for training a new generation of researchers who will be ready to leverage the use of Artificial Intelligence (AI)-based models and techniques even by non-expert users. The final goal is to make AI self-explaining and thus contribute to translating knowledge into products and services for economic and social benefit, with the support of Explainable AI systems. Moreover, our focus is on the automatic generation of interactive explanations in natural language, the preferred modality among humans, with visualization as a complementary modality.

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Cognitive biases in the context of consuming online information filtered by recommender systems may lead to sub-optimal choices. One approach to mitigate such biases is through interface and interaction design. This survey reviews studies focused on cognitive bias mitigation of recommender system users during two processes: 1) item selection and 2) preference elicitation. It highlights a number of promising directions for Natural Language Generation research for mitigating cognitive bias including: the need for personalization, as well as for transparency and control.@en

During online information search, users tend to select search results that confirm previous beliefs and ignore competing possibilities. This systematic pattern in human behavior is known as confirmation bias. In this paper, we study the effect of obfuscation (i.e., hiding the result unless the user clicks on it) with warning labels and the effect of task on interaction with attitude-confirming search results. We conducted a preregistered, between-subjects crowdsourced user study (N=328) comparing six groups: Three levels of obfuscation (targeted, random, none) and two levels of task (joint, two separate) for four debated topics. We found that both types of obfuscation influence user interactions, and in particular that targeted obfuscation helps decrease interaction with attitude-confirming search results. Future work is needed to understand how much of the observed effect is due to the strong influence of obfuscation, versus the warning label or the task design. We discuss design guidelines concerning system goals such as decreasing consumption of attitude-confirming search results, versus nudging users toward a more analytical mode of information processing. We also discuss implications for future work, such as the effects of interventions for confirmation bias mitigation over repeated exposure. We conclude with a strong word of caution: measures such as obfuscations should only be used for the benefit of the user, e.g., when they explicitly consent to mitigating their own biases.

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