References for “Algorithms and Other Drugs” and “Is AI Racist?”

Hey there. You might have recently been in the audience for my talk on algorithms and emotional expression selection. If so, thank you for showing up. I hope you learned something. If this is the kind of work that excites you, then you should come hang out with the TRAP lab. www.jointhetrap.com . Also, if you have some work to present, email me (bltphd@vt.edu ). Everyone that presents in the lab this year will get sent a piece of art.

As a personal rule, I don’t weigh my slides down with references, but I do want to make sure that everything I covered is available. So, below is a list of works that I probably covered during the talk:

Race and AI

Yi, Angela, and Broderick Turner. “Representations and Consequences of Race in AI Systems.” Current Opinion in Psychology (2024): 101831. https://doi.org/10.1016/j.copsyc.2024.101831

Angela and I cover this work on the AI Curious Podcast:

Social Media and Video Sharing Platform Background Information

Auxier, Brooke, and Monica Anderson (2021), “Social Media Use in 2021,” Pew Research Center, 1, 1–4.

Cooper, Paige. “How Does the YouTube Algorithm Work in 2021? The Complete Guide,” Last Accessed Jun 2021, https://blog.hootsuite.com/how-the-youtube-algorithm-works/

Miller, Michael (2011), YouTube for Business: Online Video Marketing for Any Business. Pearson Education.

SEC. Quarterly Report Pursuant to Section 13 Or 15(d) of the Securities Exchange Act of 1934, Facebook, Inc. Last Accessed 2021, https://www.sec.gov/Archives/edgar/data/1326801/000132680119000037/fb-03312019x10q.htm

VidCon (2016), Youtube @ vidcon: Susan wojcicki keynote. URL https://www.youtube.com/watch? v=5UVOK4SdVno.

Why Emotions Matter

Baumeister, Roy F., Ellen Bratslavsky, Catrin Finkenauer, and Kathleen D. Vohs (2001), “Bad is Stronger Than Good,” Review of General Psychology, 5(4), 323–70.

Becker, D. V., Anderson, U. S., Mortensen, C. R., Neufeld, S. L., & Neel, R. (2011), “The Face in the Crowd Effect Unconfounded: Happy Faces, Not Angry Faces, Are More Efficiently Detected in Single-And Multiple-Target Visual Search Tasks,” Journal of Experimental Psychology: General, 140(4), 637.

Bell, Paul A. (1978), “Affective State, Attraction, and Affiliation: Misery Loves Happy Company, Too,” Personality and Social Psychology Bulletin, 4(4), 616–19.

Cabanac, Michel (2002), “What is Emotion?” Behavioural Processes, 60 (2), 69–83.

Carroll, James M., and James A. Russell (1996), “Do Facial Expressions Signal Specific Emotions? Judging Emotion From the Face in Context,” Journal of Personality and Social Psychology, 70 (2), 205.

Hatfield, Elaine, John T. Cacioppo, and Richard L. Rapson (1993), “Emotional Contagion,” Current Directions in Psychological Science 2 (3), 96–100.

Kramer, Adam DI, Jamie E. Guillory, and Jeffrey T. Hancock (2014), “Experimental Evidence of Massive-Scale Emotional Contagion Through Social Networks.” Proceedings of the National Academy of Sciences, 111(24), 8788–90.

Kätsyri, Jari, Teemu Kinnunen, Kenta Kusumoto, Pirkko Oittinen, and Niklas Ravaja (2016), “Negativity Bias in Media Multitasking: The Effects of Negative Social Media Messages on Attention to Television News Broadcasts.” PLOS One, 11(5), e0153712.

Goldberg, Marvin E., and Gerald J. Gorn (1987), “Happy and Sad TV Programs: How They Affect Reactions to Commercials.” Journal of Consumer Research, 14 (3), 387–403.

Soroka, Stuart, Patrick Fournier, and Lilach Nir (2019), “Cross-National Evidence of a Negativity Bias in Psychophysiological Reactions to News,” Proceedings of the National Academy of Sciences 116 (38), 18888–92.

Stieglitz, Stefan, and Linh Dang-Xuan (2013), “Emotions and Information Diffusion in Social Media — Sentiment of Microblogs and Sharing Behavior.” Journal of Management Information Systems 29, (4), 217–48.

Emotion Measurement

Betella, Alberto, and Paul FMJ Verschure (2016), “The Affective Slider: A Digital Self-Assessment Scale for the Measurement of Human Emotions,” PLOS One, 11(2), e0148037.

Kahn, Jeffrey H., Renee M. Tobin, Audra E. Massey, and Jennifer A. Anderson (2007), “Measuring Emotional Expression With the Linguistic Inquiry and Word Count,” The American Journal Of Psychology,120 (2), 263–286.

Rhue, Lauren. “Racial influence on automated perceptions of emotions.” Available at SSRN 3281765 (2018).https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3281765

How Algorithms Work

Lu, Xin, Zhe Lin, Hailin Jin, Jianchao Yang, and James Z. Wang (2015), “Rating Image Aesthetics Using Deep Learning,” IEEE Transactions on Multimedia, 17(11), 2021–34.

Hill, Robin K. (2016), “What an Algorithm Is,” Philosophy & Technology,29 (1), 35–59.

Moschovakis, Yiannis N. (2001), “What is an Algorithm?” in Mathematics Unlimited — 2001 and Beyond, pp. 919–36. Springer, Berlin, Heidelberg.

Song, Yale, Miriam Redi, Jordi Vallmitjana, and Alejandro Jaimes (2016), “To Click or Not to Click: Automatic Selection of Beautiful Thumbnails from Videos,” in Proceedings of the 25th ACM International Conference on Information and Knowledge Management, pp. 659–68.

Algorithm Audits

Brown, Shea, Jovana Davidovic, and Ali Hasan (2021), “The Algorithm Audit: Scoring the Algorithms That Score Us.” Big Data & Society 8(1), 2053951720983865.

Ma, Debbie S., Joshua Correll, and Bernd Wittenbrink (2015), “The Chicago Face Database: A Free Stimulus Set of Faces and Norming Data,” Behavior Research Methods 47 (4), 1122–35.

Ma, Debbie S., Justin Kantner, and Bernd Wittenbrink (2021), “Chicago Face Database: Multiracial Expansion,” Behavior Research Methods, 53 (3) 1289–1300.

Raji, Inioluwa Deborah, and Joy Buolamwini (2019), “Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products,” in Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, pp. 429–35.

Sandvig, Christian, Kevin Hamilton, Karrie Karahalios, and Cedric Langbort (2014), “Auditing Algorithms: Research Methods for Detecting Discrimination on Internet Platforms.” Data and Discrimination: Converting Critical Concerns into Productive Inquiry, 22: 4349–57.

Sandvig, Christian, Kevin Hamilton, Karrie Karahalios, and Cedric Langbort (2014), “An Algorithm Audit,” Data and Discrimination: Collected essays, 6–10.

Algorithmic Bias/ Poor Training

Buolamwini, Joy, and Timnit Gebru (2018), “Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification.” In Conference on Fairness, Accountability and Transparency, pp. 77–91. PMLR.

Lambrecht, Anja, and Catherine Tucker (2019), “Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads,” Management Science, 65 (7) 2966–81.