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Game-Oriented Ethics in AI: The Types of Games

Created for the Good Systems Initiative (http://goodsystems.utexas.edu/) This is Part 2 of a 3-part mini-series envisioning how and why the current flagships of AI are hyperfocused on game-oriented AI models, and how those models are likely to be used for implementing ethics. Part 1:    • Game-Oriented Ethics in AI: Mu-Zero a...   Part 2:    • Game-Oriented Ethics in AI: The Types...   Part 3:    • Game-Oriented Ethics in AI: The Future   Citations: Ananny, M. (2016). Toward an Ethics of Algorithms: Convening, Observation, Probability, and Timeliness. Science, Technology, & Human Values, 41(1), 93–117. https://doi.org/10.1177/0162243915606523 Hauer, T. (2022). Incompleteness of moral choice and evolution towards fully autonomous AI. Humanities and Social Sciences Communications, 9(1), 1–9. https://doi.org/10.1057/s41599-022-01... Mökander, J., & Floridi, L. (2021). Ethics-Based Auditing to Develop Trustworthy AI. Minds and Machines, 31(2), 323–327. https://doi.org/10.1007/s11023-021-09... Schrittwieser, J., Antonoglou, I., Hubert, T., Simonyan, K., Sifre, L., Schmitt, S., Guez, A., Lockhart, E., Hassabis, D., Graepel, T., Lillicrap, T., & Silver, D. (2020). Mastering Atari, Go, chess and shogi by planning with a learned model. Nature, 588(7839), 604–609. https://doi.org/10.1038/s41586-020-03... Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., Lillicrap, T., Simonyan, K., & Hassabis, D. (2018). A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science, 362(6419), 1140–1144. https://doi.org/10.1126/science.aar6404 Ziewitz, M. (2016). Governing Algorithms: Myth, Mess, and Methods. Science, Technology, & Human Values, 41(1), 3–16. https://doi.org/10.1177/0162243915608948