Trusting a Virtual Driver That Looks, Acts, and Thinks Like You.

OBJECTIVE: We examined whether participants would trust an agent that was similar to them more than an agent that was dissimilar to them. BACKGROUND: Trust is an important psychological factor determining the acceptance of smart systems. Because smart systems tend to be treated like humans, and similarity has been shown to increase trust in humans, we expected that similarity would increase trust in a virtual agent. METHODS: In a driving simulator experiment, participants (N = 111) were presented with a virtual agent that was either similar to them or not. This agent functioned as their virtual driver in a driving simulator, and trust in this agent was measured. Furthermore, we measured how trust changed with experience. RESULTS: Prior to experiencing the agent, the similar agent was trusted more than the dissimilar agent. This effect was mediated by perceived similarity. After experiencing the agent, the similar agent was still trusted more than the dissimilar agent. CONCLUSION: Just as similarity between humans increases trust in another human, similarity also increases trust in a virtual agent. When such an agent is presented as a virtual driver in a self-driving car, it could possibly enhance the trust people have in such a car. APPLICATION: Displaying a virtual driver that is similar to the human driver might increase trust in a self-driving car.

Brightness differences influence the evaluation of affective pictures.

We explored the possibility of a general brightness bias: brighter pictures are evaluated more positively, while darker pictures are evaluated more negatively. In Study 1 we found that positive pictures are brighter than negative pictures in two affective picture databases (the IAPS and the GAPED). Study 2 revealed that because researchers select affective pictures on the extremity of their affective rating without controlling for brightness differences, pictures used in positive conditions of experiments were on average brighter than those used in negative conditions. Going beyond correlational support for our hypothesis, Studies 3 and 4 showed that brighter versions of neutral pictures were evaluated more positively than darker versions of the same picture. Study 5 revealed that people categorised positive words more quickly than negative words after a bright picture prime, and vice versa for negative pictures. Together, these studies provide strong support for the hypotheses that picture brightness influences evaluations.

Living behind dikes: mimicking flooding experiences.

Delta areas like the Netherlands are threatened by global climate change. Awareness is, however, rather low. Our research objective was to investigate whether coping responses to flooding risks could be enhanced in a virtual environment (VE). A laboratory experiment was conducted in which participants were exposed to a simulated dike breach and consequent flooding of their virtual residence. We tested the hypothesis that an interactive 3D flood simulation facilitates coping responses compared to noninteractive film and slide simulations. Our results showed that information search, the motivation to evacuate, and the motivation to buy flood insurance increased after exposure to the 3D flood simulation compared to the film and slide simulations. Mediation analyses revealed that some of these presentation mode effects were mediated by a greater sense of being present in the VE. Implications to use high-end flood simulations in a VE to communicate real-world flooding risks and coping responses to threatened residents will be discussed.

Trust in smart systems: sharing driving goals and giving information to increase trustworthiness and acceptability of smart systems in cars.

OBJECTIVE: We examine whether trust in smart systems is generated analogously to trust in humans and whether the automation level of smart systems affects trustworthiness and acceptability of those systems. BACKGROUND: Trust is an important factor when considering acceptability of automation technology. As shared goals lead to social trust, and intelligent machines tend to be treated like humans, the authors expected that shared driving goals would also lead to increased trustworthiness and acceptability of adaptive cruise control (ACC) systems. METHOD: In an experiment, participants (N = 57) were presented with descriptions of three ACCs with different automation levels that were described as systems that either shared their driving goals or did not. Trustworthiness and acceptability of all the ACCs were measured. RESULTS: ACCs sharing the driving goals of the user were more trustworthy and acceptable than were ACCs not sharing the driving goals of the user. Furthermore, ACCs that took over driving tasks while providing information were more trustworthy and acceptable than were ACCs that took over driving tasks without providing information. Trustworthiness mediated the effects of both driving goals and automation level on acceptability of ACCs. CONCLUSION: As when trusting other humans, trusting smart systems depends on those systems sharing the user's goals. Furthermore, based on their description, smart systems that take over tasks are judged more trustworthy and acceptable when they also provide information. APPLICATION: For optimal acceptability of smart systems, goals of the user should be shared by the smart systems, and smart systems should provide information to their user.

The role of trust in the affective evaluation of novel risks: the case of CO2 storage.

There is general recognition that trust and affect are closely connected concepts. Usually, affect is modeled as an antecedent of trust. In the present research, we will argue that, particularly in new situations, trust can also evoke affect toward a risky object. Using structural equation modeling, support was found for the hypothesis that trust influences attitudes through this process. In the present study, we analyzed attitudes toward (carbon dioxide) CO(2) storage. The role of affect appears to be moderated by the level of self-relevance. In the case of high self-relevance (storage nearby), people's attitudes appeared to be merely based on affective reactions and trust. This effect is much weaker under low self-relevance (CO(2) storage in general). In such a case, cognitive factors, more particularly beliefs concerning perceived benefits, were also taken into account in attitude formation.