From SERPs to Sound: How Search Engine Result Pages and AI-generated Podcasts Interact to Influence User Attitudes on Controversial Topics

TL;DR

This study explores how the interaction between traditional search engine result pages and AI-generated podcasts influences user attitudes on controversial topics, revealing that sequence and bias significantly affect opinion change.

Contribution

It provides empirical evidence on the combined impact of SERPs and AI podcasts on user attitudes, highlighting the importance of exposure sequence and bias in shaping opinions.

Findings

Sequence of media exposure affects attitude change

Viewpoint bias influences user opinions

Controversiality degree moderates attitude shifts

Abstract

Compared to search engine result pages (SERPs), AI-generated podcasts represent a relatively new and relatively more passive modality of information consumption, delivering narratives in a naturally engaging format. As these two media increasingly converge in everyday information-seeking behavior, it is essential to explore how their interaction influences user attitudes, particularly in contexts involving controversial, value-laden, and often debated topics. Addressing this need, we aim to understand how information mediums of present-day SERPs and AI-generated podcasts interact to shape the opinions of users. To this end, through a controlled user study (N=483), we investigated user attitudinal effects of consuming information via SERPs and AI-generated podcasts, focusing on how the sequence and modality of exposure shape user opinions. A majority of users in our study corresponded to attitude change outcomes, and we found an effect of sequence on attitude change. Our results further revealed a role of viewpoint bias and the degree of topic controversiality in shaping attitude change, although we found no effect of individual moderators.