Communicating Algorithmic Process in Online Behavioral Advertising
Many advertising platforms now give users the opportunity to learn about ad tailoring processes by showing more information when users click on a question like "Why am I seeing this ad?". However, algorithmic transparency is not straightforward. Explaining a complex algorithm's behavior accurately, comprehensively, and briefly in a non-technical way is challenging. Even in cases where it is easy to provide users with an interpretable explanation about an algorithmic curation process, providing explanations is not an unmitigated good. For example, providing students with too much or too little information about a grading algorithm both diminished students' trust in the grading system. Explanations are more challenging in behavioral advertising because revealing curation processes may create new privacy concerns. How revealing aspects of the algorithmic ad curation process will affect user perception of behavioral advertising remains an open question.
In this proect, we exposed 32 users to why an ad is shown to them, what advertising algorithms infer about them, and how advertisers use this information. Users preferred interpretable, non-creepy explanations about why an ad is presented, along with a recognizable link to their identity. We further found that exposing users to their algorithmically-derived attributes led to algorithm disillusionment-users found that advertising algorithms they thought were perfect were far from it.
M. Eslami, S. R. Krishna Kumaran, C. Sandvig, K. Karahalios. Communicating Algorithmic Process in Online Behavioral Advertising. To Appear at Human Factors in Computing Systems Conference (CHI), 2018 pdf