Deep Cover HCI

The growing popularity of methodologies that turn "to the wild" for real world data creates new ethical issues for the HCI community. For investigations questioning interactions in public or transient spaces, crowd interaction, or natural behaviour, uncontrolled and uninfluenced (by the experimenter) experiences represent the ideal evaluation environment. We argue that covert research can be completed rigorously and ethically to expand our knowledge of ubiquitous technologies. Our approach, which we call Deep Cover HCI, utilises technology-supported observation in public spaces to stage completely undisturbed experiences for evaluation. We complete studies without informed consent and without intervention from an experimenter in order to gain new insights into how people use technology in public settings. We argue there is clear value in this approach, reflect on the ethical issues of such investigations, and describe our ethical guidelines for completing Deep Cover HCI Research

Combined Effects of Knowledge About Others' Opinions and Anticipation of Group Discussion on Confirmatory Information Search

There is conclusive evidence that information search processes are typically biased in favor of the information seeker’s own opinion (confirmation bias). Less is known about how knowledge about others’ opinions affects this confirmatory information search. In the present study, the authors manipulated feedback about others’ opinions and anticipation of group interaction. As predicted, the effect of knowledge about others’ opinions on confirmatory information search depended on whether participants anticipated interacting with these others. Specifically, minority members anticipating a group discussion exhibited a particularly strong confirmation bias, whereas minority members who did not anticipate a discussion predominantly sought information opposing their opinion. For participants not anticipating group interaction, confidence about the correctness of one’s decision mediated the impact of knowledge about others’ opinions on confirmatory information search. Results are discussed with regard to the debiasing effect of preference heterogeneity on confirmatory information search in groups

Learning for a Change: Exploring the Relationship Between Education and Sustainable Development

Whether we view sustainable development as our greatest challenge or a subversive litany, every phase of education is now being urged to declare its support for education for sustainable development (ESD). In this paper, we explore the ideas behind ESD and, building on work by Foster and by Scott and Gough, we argue that it is necessary now to think of two complementary approaches: ESD 1 and ESD 2. We see ESD 1 as the promotion of informed, skilled behaviours and ways of thinking, useful in the short-term where the need is clearly identified and agreed, and ESD 2 as building capacity to think critically about what experts say and to test ideas, exploring the dilemmas and contradictions inherent in sustainable living. We note the prevalence of ESD 1 approaches, especially from policy makers; this is a concern because people rarely change their behaviour in response to a rational call to do so, and more importantly, too much successful ESD 1 in isolation would reduce our capacity to manage change ourselves and therefore make us less sustainable. We argue that ESD 2 is a necessary complement to ESD 1, making it meaningful in a learning sense. In this way we avoid an either-or debate in favour of a yes-and approach that constantly challenges us to understand what we are communicating, how we are going about it and, crucially, why we are doing it in the first place

Psychological Safety and Norm Clarity in Software Engineering Teams

In the software engineering industry today, companies primarily conduct their work in teams. To increase organizational productivity, it is thus crucial to know the factors that affect team effectiveness. Two team-related concepts that have gained prominence lately are psychological safety and team norms. Still, few studies exist that explore these in a software engineering context. Therefore, with the aim of extending the knowledge of these concepts, we examined if psychological safety and team norm clarity associate positively with software developers' self-assessed team performance and job satisfaction, two important elements of effectiveness. We collected industry survey data from practitioners (N = 217) in 38 development teams working for five different organizations. The result of multiple linear regression analyses indicates that both psychological safety and team norm clarity predict team members' self-assessed performance and job satisfaction. The findings also suggest that clarity of norms is a stronger (30\% and 71\% stronger, respectively) predictor than psychological safety. This research highlights the need to examine, in more detail, the relationship between social norms and software development. The findings of this study could serve as an empirical baseline for such, future work.Comment: Submitted to CHASE'201

Biased Information Search in Homogeneous Groups: Confidence as a Moderator for the Effect of Anticipated Task Requirements

When searching for information, groups that are homogeneous regarding their members’ prediscussion decision preferences show a strong bias for information that supports rather than conflicts with the prevailing opinion (confirmation bias). The present research examined whether homogeneous groups blindly search for information confirming their beliefs irrespective of the anticipated task or whether they are sensitive to the usefulness of new information for this forthcoming task. Results of three experiments show that task sensitivity depends on the groups’ confidence in the correctness of their decision: Moderately confident groups displayed a strong confirmation bias when they anticipated having to give reasons for their decision but showed a balanced information search or even a disconfirmation bias (i.e., predominately seeking conflicting information) when they anticipated having to refute unterarguments. In contrast, highly confident groups demonstrated a strong confirmation bias independent of the anticipated task requirements

The Misprediction of emotions in Track Athletics.: Is experience the teacher of all things?

People commonly overestimate the intensity of their emotions toward future events. In other words, they display an impact bias. This research addresses the question whether people learn from their experiences and correct for the impact bias. We hypothesize that athletes display an impact bias and, counterintuitively, that increased experience with an event increases this impact bias. A field study in the context of competitive track athletics supported our hypotheses by showing that athletes clearly overestimated their emotions toward the outcome of a track event and that this impact bias was more pronounced for negative events than for positive events. Moreover, with increased athletic experience this impact bias became larger. This effect could not be explained by athletes’ forecasted emotions, but it could be explained by the emotions they actually felt following the race. The more experience athletes had with athletics, the less they felt negative emotions after unsuccessful goal attainment. These findings are discussed in relation to possible underlying emotion regulation processes

Weight stability in adults with obesity initiating medical marijuana treatment for other medical conditions

Few studies have evaluated weight change in patients who initiate medical marijuana treatment to address diagnosed health concerns. The objective of this study was to examine whether patients initiating medical marijuana use for a qualifying health condition experienced changes in health and biopsychosocial functioning over time, including weight gain or loss. Specifically, this observational, longitudinal study evaluated changes in the body mass index (BMI) of adults with co-morbid obesity (body mass index [BMI] ≥ 30 kg/m2) and severe obesity (BMI ≥ 40 kg/m2) who were starting medical marijuana treatment for any of the 23 qualifying medical conditions at one of three dispensaries in Pennsylvania. Height and weight measurements were collected at baseline (prior to medical marijuana use) and then 90 days (± 14 days) later. Participants included in analyses (n = 52, M = 55.0 ± 13.6 years, 59.6% female) had a mean baseline BMI of 36.2 ± 5.4 kg/m2 and the majority sought medical marijuana for chronic pain (73.1%). No significant change in BMI was observed from baseline to month three (p \u3e 0.05) in the sample. Additionally, no significant change in BMI was observed in the subset of patients with severe obesity (n = 12, p \u3e 0.05). Our findings are limited by low follow-up rates and convenience sampling methodology but may help to mitigate weight gain concerns in the context of medical marijuana use

Data Portraits and Intermediary Topics: Encouraging Exploration of Politically Diverse Profiles

In micro-blogging platforms, people connect and interact with others. However, due to cognitive biases, they tend to interact with like-minded people and read agreeable information only. Many efforts to make people connect with those who think differently have not worked well. In this paper, we hypothesize, first, that previous approaches have not worked because they have been direct -- they have tried to explicitly connect people with those having opposing views on sensitive issues. Second, that neither recommendation or presentation of information by themselves are enough to encourage behavioral change. We propose a platform that mixes a recommender algorithm and a visualization-based user interface to explore recommendations. It recommends politically diverse profiles in terms of distance of latent topics, and displays those recommendations in a visual representation of each user's personal content. We performed an "in the wild" evaluation of this platform, and found that people explored more recommendations when using a biased algorithm instead of ours. In line with our hypothesis, we also found that the mixture of our recommender algorithm and our user interface, allowed politically interested users to exhibit an unbiased exploration of the recommended profiles. Finally, our results contribute insights in two aspects: first, which individual differences are important when designing platforms aimed at behavioral change; and second, which algorithms and user interfaces should be mixed to help users avoid cognitive mechanisms that lead to biased behavior.Comment: 12 pages, 7 figures. To be presented at ACM Intelligent User Interfaces 201

Sensory imagery in craving: From cognitive psychology to new treatments for addiction

Sensory imagery is a powerful tool for inducing craving because it is a key component of the cognitive system that underpins human motivation. The role of sensory imagery in motivation is explained by Elaborated Intrusion (EI) theory. Imagery plays an important role in motivation because it conveys the emotional qualities of the desired event, mimicking anticipated pleasure or relief, and continual elaboration of the imagery ensures that the target stays in mind. We argue that craving is a conscious state, intervening between unconscious triggers and consumption, and summarise evidence that interfering with sensory imagery can weaken cravings. We argue that treatments for addiction can be enhanced by the application of EI theory to maintain motivation, and assist in the management of craving in high-risk situations