Close Encounters of the Digital Kind: Motivated Search, Selection and Decision-Making in an Interactive Digital Context

Interactive digital contexts have become ubiquitous and indispensable, capturing hours of attention and influencing everyday decision-making, content consumption, purchasing behaviors, and the formation and updating of attitudes in a variety of domains. These carefully designed environments interact with human motivation to influence behaviors and beliefs, including in impactful domains such as science and public policy. Digital information contexts such as the newly released AI ChatGPT and Google may or have become the de facto standard for information search and content delivery, however search results in these contexts arrive either devoid of editorial filtering or with limited procedural transparency, or both. The potential societal costs of “wild information” are immense, especially for areas such as scientific technology that can provide significant benefits with low and manageable risk (i.e. vaccines, or genetically modified foods (GM). Using GM foods as a focal topic, we designed and implemented a custom search engine and content delivery system to identify the stages at which human motivation operates and its effects on search and selection behavior, attitude updating and decision-making in the context of widely-used interactive digital technology. Results demonstrate Google format searching often reflects prior beliefs and background media sentiment about GM foods, while menu-style searching reflects only prior attitudes. Prior attitudes influence search and content selection and in turn, content selection influences both attitudes about GM foods and decision-making in a food selection task. These results demonstrate when and how motivation covertly operates during digital information search and selection, and how search-based interactive technology interacts with motivational and cognitive systems to influence belief and real-world decision-making.