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Rosen, D., Oh, Y., Chesebrough, C., Zhang, F. Z., & Kounios, J. (2024). Creative flow as optimized processing: Evidence from brain oscillations during jazz improvisations by expert and non-expert musicians. Neuropsychologia, 108824.
Rosen, D., Oh, Y., Chesebrough, C., Zhang, F. Z., & Kounios, J. (2024). Creative flow as optimized processing: Evidence from brain oscillations during jazz improvisations by expert and non-expert musicians. Neuropsychologia, 108824.
#Creativity#Neuroscience#Brain Science#BCI#Paper#PDF#Behavior
·pdf.sciencedirectassets.com·
Rosen, D., Oh, Y., Chesebrough, C., Zhang, F. Z., & Kounios, J. (2024). Creative flow as optimized processing: Evidence from brain oscillations during jazz improvisations by expert and non-expert musicians. Neuropsychologia, 108824.
Pan, C. A., Yakhmi, S., Iyer, T. P., Strasnick, E., Zhang, A. X., & Bernstein, M. S. (2022). Comparing the perceived legitimacy of content moderation processes: Contractors, algorithms, expert panels, and digital juries. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW1), 1-31.
Pan, C. A., Yakhmi, S., Iyer, T. P., Strasnick, E., Zhang, A. X., & Bernstein, M. S. (2022). Comparing the perceived legitimacy of content moderation processes: Contractors, algorithms, expert panels, and digital juries. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW1), 1-31.
Digital juries.
#Social Media#Moderation#Legitimacy#Paper#PDF#Democracy
·dl.acm.org·
Pan, C. A., Yakhmi, S., Iyer, T. P., Strasnick, E., Zhang, A. X., & Bernstein, M. S. (2022). Comparing the perceived legitimacy of content moderation processes: Contractors, algorithms, expert panels, and digital juries. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW1), 1-31.
Gordon, M. L., Lam, M. S., Park, J. S., Patel, K., Hancock, J., Hashimoto, T., & Bernstein, M. S. (2022, April). Jury learning: Integrating dissenting voices into machine learning models. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1-19).
Gordon, M. L., Lam, M. S., Park, J. S., Patel, K., Hancock, J., Hashimoto, T., & Bernstein, M. S. (2022, April). Jury learning: Integrating dissenting voices into machine learning models. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1-19).
(How is a juror instructed to eliminate implicit bias? What would be the specifics of a course that changed their minds? This is fairly easy to trigger in practice, e.g. as subtext to invoke irony.)
#Machine Learning#Legal#Bias#Paper#PDF
·dl.acm.org·
Gordon, M. L., Lam, M. S., Park, J. S., Patel, K., Hancock, J., Hashimoto, T., & Bernstein, M. S. (2022, April). Jury learning: Integrating dissenting voices into machine learning models. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1-19).
Ferreira, R., & Vardi, M. Y. (2021, March). Deep tech ethics: An approach to teaching social justice in computer science. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (pp. 1041-1047).
Ferreira, R., & Vardi, M. Y. (2021, March). Deep tech ethics: An approach to teaching social justice in computer science. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (pp. 1041-1047).
#Computer Science#Ethics#Academics#Paper#PDF#Digital Humanism
·cs.rice.edu·
Ferreira, R., & Vardi, M. Y. (2021, March). Deep tech ethics: An approach to teaching social justice in computer science. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (pp. 1041-1047).