We study user attitudes and behaviour to understand the implications for individuals, and by extension, for society as a whole. Our research questions concern (i) matters of privacy and trust; (ii) the individuals’ self-expected and actual responses to contextual communication; (iii) communication efficiency in terms of information transfer, conversion rates, brand recall, etc.; and (iv) the functioning and soundness of democratic processes.
In each case, we contrast contextual communication with personalised communication. Simply put, the former matches messages with media contexts, whereas the latter matches messages with data about recipients. Personalised advertising is currently the dominating form in digital advertising, but has severe problems related to personal integrity, stereotyping, and democracy. Contextual communication is expected to solve many of these problems, but may in doing so introduce new and potentially worse problems.
The project establishes AI-driven contextual communication as a new research field. It is a multidisciplinary undertaking, engaging researchers from computer science, behavioural science, media and communication studies, and business management. We use a combination of quantitative and qualitative methods, conducting experiments and longitudinal data collection on real-world advertising platforms, and complement these with studies involving, e.g., eye-tracking, walk-through techniques, and emotional response analysis. The scientific outcome is an empirically validated theory of AI-driven contextual communication.