AI reading list
Hello all, pls see the reading list; this is an ongoing list, with more comprehensive list to be added.
Meanwhile, please check the section with links first:
AI-Algorithm Reading List
Mozilla Foundation, Responsible Computing
Howard University, 2024
Dr. Yong Jin Park, PI
Dr. Liu, & Prof Sturgis, Co-I
Algorithm Data Surveillance
Park, Y. J., & Jones-Jang, S. M. (2023). Surveillance, security, and AI as technological acceptance. AI & society, 38(6), 2667-2678.
Park, Y. J. (2021). The future of digital surveillance: why digital monitoring will never lose its appeal in a world of algorithm-driven AI. University of Michigan Press.
Park, Y. J., Sang, Y., Lee, H., & Jones-Jang, S. M. (2020). The ontology of digital asset after death: policy complexities, suggestions and critique of digital platforms. Digital Policy, Regulation and Governance, 22(1), 1-14.
Andrew Guthrie Ferguson. (2017). The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement. New York: New York University Press. Read Ch. 1-3, 5-6, and conclusion.
· Publisher Page: https://nyupress.org/9781479892822/the-rise-of-big-data-policing/
AI, Algorithm, and Bias
Park, Y. J. (2023). How we can create the global agreement on generative AI bias: lessons from climate justice. AI & SOCIETY, 1-3.
Bao, M., Zhou, A., Zottola, S. A., Brubach, B., Desmarais, S., Horowitz, A., Lum, K., & Venkatasubramanian, S. (2021). It’s COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks. ArXiv. https://arxiv.org/abs/2106.05498
· https://arxiv.org/abs/2106.05498
Shin, D., Hameleers, M., Park, Y. J., Kim, J. N., Trielli, D., Diakopoulos, N., ... & Baumann, S. (2022). Countering algorithmic bias and disinformation and effectively harnessing the power of AI in media. Journalism & Mass Communication Quarterly, 99(4), 887-907.
Park, Y.J. (2023). Let me tell you, ChatGPT-like AI will not change our world.
Internet Policy Review, https://policyreview.info/articles/news/
Peng, K., Mathur, A., & Narayanan, A. (2021). Mitigating Dataset Harms Requires Stewardship: Lessons from 1000 Papers. ArXiv. http://arxiv.org/abs/2108.02922
· https://arxiv.org/abs/2108.02922
AI, Algorithm, and Individual Behavior
Jones-Jang, S. M., & Park, Y. J. (2023). How do people react to AI failure? Automation bias, algorithmic aversion, and perceived controllability. Journal of Computer-Mediated Communication, 28(1), zmac029.
Park, Y. J., Lee, H., Jones-Jang, S. M., & Oh, Y. W. (2022). Digital assistants: Inequalities and social context of access, use, and perceptual understanding. Poetics, 93, 101689.
Shin, D., & Park, Y. J. (2019). Role of fairness, accountability, and transparency in algorithmic affordance. Computers in Human Behavior, 98, 277-284.
Park, Y. J. (2022). Personal data concern, behavioral puzzle and uncertainty in the age of digital surveillance. Telematics and Informatics, 66, 101748.
AI, Institution, and Policy Issues
Park, Y. J. (2021). Structural logic of Ai surveillance and its normalisation in the public sphere. Javnost-The Public, 28(4), 341-357.
Park, Y. J., Chung, J. E., & Shin, D. H. (2018). The structuration of digital ecosystem, privacy, and big data intelligence. American Behavioral Scientist, 62(10), 1319-1337.
Shin, D. H., & Jin Park, Y. (2017). Understanding the Internet of Things ecosystem: multi-level analysis of users, society, and ecology. Digital Policy, Regulation and Governance, 19(1), 77-100.
Pasquale, Frank. (2015). The Black Box Society: The Secret Algorithms That Control Money and Information. Cambridge: Harvard University Press.
· Harvard BKC Page: https://cyber.harvard.edu/events/luncheon/2015/04/Pasquale
