Bibliography: Bias in Artificial Intelligence
NIST A.I. Reference Library Bibliography: Bias in Artificial Intelligence Abdollahpouri, H., Mansoury, M., Burke, R., & Mobasher, B. (2019). The unfairness of popularity bias in recommendation. arXiv preprint arXiv:1907.13286. Abebe, R., Barocas, S., Kleinberg, J., Levy, K., Raghavan, M., & Robinson, D. G. (2020, January). Roles for computing in social change. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 252-260. Aggarwal, A., Shaikh, S., Hans, S., Haldar, S., Ananthanarayanan, R., & Saha, D. (2021). Testing framework for black-box AI models. arXiv preprint. Retrieved from https://arxiv.org/pdf/2102.06166.pdf Ahmed, N., & Wahed, M. (2020). The De-democratization of AI: Deep learning and the compute divide in artificial intelligence research. arXiv preprint arXiv:2010.15581. Retrieved from https://arxiv.org/ftp/arxiv/papers/2010/2010.15581.pdf. AI Now Institute. Algorithmic Accountability Policy Toolkit. (2018). Retrieved from: https://ainowinstitute.org/aap-toolkit.html. Aitken, M., Toreini, E., Charmichael, P., Coopamootoo, K., Elliott, K., & van Moorsel, A. (2020, January). Establishing a social licence for Financial Technology: Reflections on the role of the private sector in pursuing ethical data practices. Big Data & Society. doi:10.1177/2053951720908892 Ajunwa, I. (2016). Hiring by Algorithm. SSRN Electronic Journal. doi:10.2139/ssrn.2746078 Ajunwa, I. (2020, Forthcoming). The Paradox of Automation as Anti-Bias Intervention, 41 Cardozo, L. Rev. Amini, A., Soleimany, A. P., Schwarting, W., Bhatia, S. N., & Rus, D. (2019, January). Uncovering and mitigating algorithmic bias through learned latent structure. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 289-295. Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., & Mané, D.
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