AI-driven advertising is often presented as one of the main successes of deep learning, after heavy investments in machine learning algorithms that discover and exploit patterns in consumer behaviour. In a new project financed the Marcus and Marianne Wallenberg Foundation, researchers from Umeå University, Malmö University, Stockholm School of Economics, and the University of Gothenburg collaborate to understand the implications for citizens and society linked to different types of targeting methods used in online advertising.
The team focus in particular on contextual targeting, where ads are placed based on the media content that is being viewed, in contrast to personalised targeting, where the ads are placed based on who is reading the content. The aim is to provide an empirically validated theory of the dynamics of contextual targeting, in itself and in combination with personalised targeting. The findings will help inform consumers about the type of argumentation they are exposed to, and function as input to an on-going discussion about internal and external regulation of the advertising market.
Read more on https://www.umu.se/en/news/awarded-4-million-sek-for-developing-new-deep-learning-methods–_9767583/ or contact Johanna Björklund, email@example.com, to discuss collaboration opportunities.