Bibliography
- Armstrong, S., A. Sandberg, and N. Bostrom. ‘Thinking inside the Box: Controlling and Using an Oracle AI’. Minds Machines (2012): 22:299–324.
- Barrett, A.M., and S.D. Baum. ‘A Model of Pathways to Artificial Superintelligence Catastrophe for Risk and Decision Analysis’. Journal of Experimental and Theoretical Artificial Intelligence 29 (2017): 397–414. doi:https://doi.org/10.1080/0952813X.2016.1186228.
- Baum, S. ‘A Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy’. Global Catastrophic Risk Institute Working Paper (2017): 1–17.
- Bostrom, N. Superintelligence: Paths, Dangers, Strategies. New York, NY, USA: Oxford University Press Inc, 2014.
- Bradley, P. ‘Risk Management Standards and the Active Management of Malicious Intent in Artificial Superintelligence’. AI and Society 35 (2020): 319–328. doi:https://doi.org/10.1007/s00146-019-00890-2.
- Claudino, J.G., D. de Oliveira Capanema, T.V. de Souza, J.C. Serrão, A.C.M. Pereira, and G.P. Nassis. ‘Current Approaches to the Use of Artificial Intelligence for Injury Risk Assessment and Performance Prediction in Team Sports: A Systematic Review’. Sports Medicine-open (2019): 5 (1): 1–12.
- Firt, E. ‘The Missing G’. AI and Society 35 (2020): 995–1007. doi:https://doi.org/10.1007/s00146-020-00942-y.
- Fjelland, R. ‘Why General Artificial Intelligence Will Not Be Realized’. Humanities Social Sciences Communications (2020): 7 (1): 1–9.
- Forster, J. ‘Global Sports Governance and Corruption’. Palgrave Communications (2016): 2 (1): 1–4.
- Gardiner, S., J. Parry, and S. Robinson. ‘Integrity and the Corruption Debate in Sport: Where Is the Integrity?’. European Sport Management Quarterly 17 (2017): 6–23. doi:https://doi.org/10.1080/16184742.2016.1259246.
- Goertzel, B., and J. Pitt. ‘Nine Ways to Bias Open-source Artificial General Intelligence toward Friendliness’. Intelligence Unbound (2014): 22 (1): 61–89.
- Hancock, P.A. ‘Imposing Limits on Autonomous Systems’. Ergonomics 60 (2017): 284–291. doi:https://doi.org/10.1080/00140139.2016.1190035.
- Hancock, P.A. Avoiding Autonomous Agents’ Adverse Actions. Journal of Human Computer Interaction. In Press.
- Kaplan, A., and M. Haenlein. ‘Siri, Siri, in My Hand: Who’s the Fairest in the Land? On the Interpretations, Illustrations, and Implications of Artificial Intelligence’. Business Horizons 62, no. 1 (2019): 15–25. doi:https://doi.org/10.1016/j.bushor.2018.08.004.
- Kihl, L.A., J. Skinner, and T. Engelberg. ‘Corruption in Sport: Understanding the Complexity of Corruption’. European Sport Management Quarterly 17, no. 1 (2017): 1–6. doi:https://doi.org/10.1080/16184742.2016.1257553.
- Kurzweil, R. The Singularity Is Near: When Humans Transcend Biology. New York: Penguin, 2005.
- Livingston, S., and M. Risse. ‘The Future Impact of Artificial Intelligence on Humans and Human Rights’. Ethics & International Affairs 33 (2019): 141–158. doi:https://doi.org/10.1017/S089267941900011X.
- McLean, S., D. Rath, S. Lethlean, M. Hornsby, J. Gallagher, D. Anderson, and P.M. Salmon. ‘With Crisis Comes Opportunity: Redesigning Performance Departments of Elite Sports Clubs for Life after a Global Pandemic’. Frontiers in Psychology 11 (2021). doi:https://doi.org/10.3389/fpsyg.2020.588959.
- Mortimer, H., J. Whitehead, M. Kavussanu, B. Gürpınar, and C. Ring. ‘Values and Clean Sport’. Journal of Sports Sciences (2020): 39 (5): 533–541.
- Müller, V.C., and N. Bostrom. ‘Future Progress in Artificial Intelligence: A Survey of Expert Opinion’. Fundamental Issues of Artificial Intelligence (2016): 555–572.
- Naudé, W., and N. Dimitri. ‘The Race for an Artificial General Intelligence: Implications for Public Policy’. AI and Society 35 (2020): 367–379. doi:https://doi.org/10.1007/s00146-019-00887-x.
- Salmon, P.M., and S. McLean. ‘Complexity in the Beautiful Game: Implications for Football Research and Practice’. Science Medicine in Football 4 (2020): 162–167. doi:https://doi.org/10.1080/24733938.2019.1699247.
- Salmon, P.M., T. Carden, and P. Hancock. ‘Putting the Humanity into Inhuman Systems: How Human Factors and Ergonomics Can Be Used to Manage the Risks Associated with Artificial General Intelligence’. Human Factors and Ergonomics in Manufacturing & Service Industries 31 (2021): 223–236. doi:https://doi.org/10.1002/hfm.20883.
- Silver, D., A. Huang, C.J. Maddison, A. Guez, L. Sifre, G. Van Den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, and M. Lanctot. ‘Mastering the Game of Go with Deep Neural Networks and Tree Search’. Nature 529 (2016): 484–489. doi:https://doi.org/10.1038/nature16961.
- Sotala, K., and R.V. Yampolskiy. ‘Responses to Catastrophic AGI Risk: A Survey’. Physica Scripta (2015). 90 (1): 1–33.
- Torres, P. ‘The Possibility and Risks of Artificial General Intelligence’. Bulletin of the Atomic Scientists 75 (2019): 105–108. doi:https://doi.org/10.1080/00963402.2019.1604873.
- Verschuuren, P. ‘Integrity Washing? The Implementation of Reporting Mechanisms by International Sports Organisations’. Journal of Global Sport Management (2021): 1–23. doi:https://doi.org/10.1080/24704067.2021.1882204.
- Von Clausewitz, C. On War. Princeton: Princeton University Press, 2008.
- Ward, P., A.M. Williams, and P.A. Hancock. ‘Simulation for Performance and Training’. In The Cambridge Handbook of Expertise Expert Performance, ed. K.A. Ericsson, N. Charness, R. Hoffman, and P. Feltovich, Cambridge: Cambridge University Press, 2006.