Contradicted by the Brain: Predicting Individual and Group Preferences via Brain-Computer Interfacing

Abstract

We investigate inferring individual preferences and the contradiction of individual preferences with group preferences through direct measurement of the brain. We report an experiment where brain activity collected from 31 participants produced in response to viewing images is associated with their self-reported preferences. First, we show that brain responses present a graded response to preferences, and that brain responses alone can be used to train classifiers that reliably estimate preferences. Second, we show that brain responses reveal additional preference information that correlates with group preference, even when participants self-reported having no such preference. Our analysis of brain responses carries significant implications for researchers in general, as it suggests an individual's explicit preferences are not always aligned with the preferences inferred from their brain responses. These findings call into question the reliability of explicit and behavioral signals. They also imply that additional, multimodal sources of information may be necessary to infer reliable preference information.

Crowdsourcing Affective Annotations Via fNIRS-BCI

“…For example, combining the affective data with browsing behavior and comparing that to the data of other individuals' behavior and affective responses. Moreover, subliminal probing could be used beyond the annotation task for predicting unwanted user characteristics [21] and compared to other individuals' data to reveal even social or political views. Preventing unintended use of these signals requires future research for protecting the privacy of data.…”