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Default nudges successfully guide choices across multiple domains. Online use cases for defaults range from promoting sustainable purchases to inducing acceptance of behavior tracking scripts, or “cookies.” However, many scholars view defaults as unethical due to the covert ways in which they influence behavior. Hence, opt-outs and other digital decision aids are progressively being regulated in an attempt to make them more transparent. The current practice of transparency boils down to saturating the decision environment with convoluted legal information. This approach might be informed by researchers, who hypothesized that nudges could become less effective once they are clearly laid out: People can retaliate against influence attempts if they are aware of them. A recent line of research has shown that such concerns are unfounded when the default-setters proactively discloses the purpose of the intervention. Yet, it remained unclear whether the effect persists when defaults reflect the current practice of such mandated transparency boils down to the inclusion of information disclosures, containing convoluted legal information. In two empirical studies (N = 364), respondents clearly differentiated proactive from mandated transparency. Moreover, they choose the default option significantly more often when the transparency disclosure was voluntary, rather than mandated. Policy implications and future research directions are discussed.
Machine intelligence, a.k.a. artificial intelligence (AI) is one of the most prominent and relevant technologies today. It is in everyday use in the form of AI applications and has a strong impact on society. This article presents selected results of the 2020 Dagstuhl workshop on applied machine intelligence. Selected AI applications in various domains, namely culture, education, and industrial manufacturing are presented. Current trends, best practices, and recommendations regarding AI methodology and technology are explained. The focus is on ontologies (knowledge-based AI) and machine learning.
Abstract
Brand placements are omnipresent in video games, but their overall effect on brand attitudes is small and varies substantially between studies. The present research takes an evaluative conditioning perspective to explain when and how brand placements in video games influence brand attitudes. In two experiments with a 3D first‐person video game, we show that only brands encountered during positive in‐game experiences benefit from the placement, but not those encountered during negative in‐game experiences. Building on the cognitive processes underlying evaluative conditioning, we also show that brand attitudes largely depend on the memory for the pairing of a brand with positive/negative in‐game experiences. Pairing memory and thus also evaluative conditioning effects increase when players attend to the pairing of brands and positive/negative experiences, for example, when such pairings are a central part of the game's storyline. Overall, our findings show that evaluative conditioning and its cognitive mechanisms can be utilized to explain and predict advertising effects in applied settings, such as brand placements in video games.