This episode introduces journal article originally published in Journal of the Association for Information Science and Technology. This is joint work with Rahilsadat Hosseini and Shouyi Wang from UT Arlington and Michael Cole from Rutgers Uni / Lexis-Nexis.

Gwizdka, J., Hosseini, R., Cole, M., & Wang, S. (2017). Temporal dynamics of eye-tracking and EEG during reading and relevance decisions. Journal of the Association for Information Science and Technology, 68(10), 2299–2312. https://doi.org/10.1002/asi.23904

This podcast discusses a research paper investigating how people determine online information relevance. Researchers used eye-tracking and EEG to monitor brain activity and eye movements while participants read news articles and answered questions. The study revealed that relevance isn't immediately apparent but develops over time, with more accurate predictions possible as reading progresses. Key findings included pupil dilation correlating with relevant information and identifiable patterns in eye movements during "aha" moments. The discussion also explores potential applications of this research in improving technology's interaction with human brains and the ethical implications of personalized information systems.

IX Lab website: https://ixlab.us/

Dr. Jacek Gwizdka website: https://jacekg.ischool.utexas.edu/

The audio for this conversation has been generated by AI using: https://notebooklm.google/

Music intro created by a human (C) Jacek Gwizdka