A Review of International Policymaking in the Field of Artificial Intelligence
DOI:
https://doi.org/10.69760/gsrh.010120250013Keywords:
Afghanistan, refugees, Taliban, America, International LawAbstract
Based on the Doha Agreement signed on February 29, 2020 between the Taliban and the United States of America, the two parties committed to stopping attacks on each other. The United States committed to withdrawing all its military and civilian forces and those of its allies from Afghanistan within 14 months. The Taliban also pledged to cut off cooperation with terrorist groups, including al-Qaeda, and pledged to reduce the intensity of its attacks and to advance peace talks with the Afghan government.
While this agreement was expected to end nearly two decades of military conflict in Afghanistan. However, the Taliban’s increased attacks on military and civilian targets have continued to the point where Afghan cities have fallen one after another; The then Afghan president fled to Abu Dhabi, and Kabul fell to the Taliban within hours. Meanwhile, despite assurances issued by the Taliban, many Afghans were trying to leave the country.
This has caused the world to once again face an international refugee crisis, raising the question of how international law can manage such a situation; what are the commitments of member states of the international community, and what are the potential gaps and challenges.
References
Asimov, I. (1941). Three laws of robotics. Asimov, I. Runaround.
Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., . . . Rahwan, I. (2018). The moral machine experiment. Nature, 563, 59–64.
Barnett, H. M., & Levine, K. (1965). Mr. Justice Potter Stewart. NYUL Rev., 40, 526.
Benko, A., & Lányi, C. S. (2009). History of artificial intelligence. In Encyclopedia of Information Science and Technology, Second Edition (pp. 1759–1762). IGI Global.
Brock, J. K.-U., & Von Wangenheim, F. (2019). Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence. California Management Review, 61, 110–134.
Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society, 3, 2053951715622512.
Campbell, M., Hoane Jr, A. J., & Hsu, F.-h. (2002). Deep blue. Artificial intelligence, 134, 57–83.
Carleton, A. D., Harper, E., Menzies, T., Xie, T., Eldh, S., & Lyu, M. R. (2020). The AI Effect: Working at the Intersection of AI and SE. IEEE Software, 37, 26-35. doi:10.1109/MS.2020.2987666
Conger, K., Fausset, R., & Kovaleski, S. F. (2019). San Francisco bans facial recognition technology. The New York Times, 14.
Hebb, D. O. (1949). The organization of behavior; a neuropsycholocigal theory. A Wiley Book in Clinical Psychology, 62, 78.
Hutson, M. (2018). How researchers are teaching AI to learn like a child. Science, 10.
Kaplan, A. M., & Haenlein, M. (2009). The fairyland of Second Life: Virtual social worlds and how to use them. Business horizons, 52, 563–572.
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62, 15-25. doi:https://doi.org/10.1016/j.bushor.2018.08.004
Kaplan, A., & Haenlein, M. (2020). Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Business Horizons, 63, 37–50.
Kosinski, M., Stillwell, D., & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the national academy of sciences, 110, 5802–5805.
Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J. (2019). Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, 61, 135–155.
Lighthill, J., & others. (1973). Artificial intelligence: a paper symposium. Science Research Council, London.
Markoff, J. (2011). Armies of expensive lawyers replaced by cheaper software. The New York Times, 4.
McCarthy, J., & Hayes, P. J. (1981). Some philosophical problems from the standpoint of artificial intelligence. In Readings in artificial intelligence (pp. 431–450). Elsevier.
Metcalf, L., Askay, D. A., & Rosenberg, L. B. (2019). Keeping humans in the loop: pooling knowledge through artificial swarm intelligence to improve business decision making. California Management Review, 61, 84–109.
Minsky, M. (1970). Form and Content in Computer Science (1970 ACM turing lecture). Journal of the ACM (JACM), 17, 197–215.
Minsky, M., & Papert, S. A. (1970). Proposal to ARPA for Research on Artificial Intelligence at MIT, 1970-1971.
Minsky, M., & Papert, S. A. (1972). Artificial intelligence progress report.
Mishra, M., & Srivastava, M. (2014). A view of Artificial Neural Network. 2014 International Conference on Advances in Engineering Technology Research (ICAETR - 2014), (pp. 1-3).n doi:10.1109/ICAETR.2014.7012785
Natale, S. (2019). If software is narrative: Joseph Weizenbaum, artificial intelligence and the biographies of ELIZA. new media & society, 21, 712–728.
Overgoor, G., Chica, M., Rand, W., & Weishampel, A. (2019). Letting the computers take over: Using AI to solve marketing problems. California Management Review, 61, 156–185.
Rajaraman, V. (2014). JohnMcCarthy—Father of artificial intelligence. Resonance, 19, 198–207.
Roland, A., Shiman, P., Aspray, W., & others. (2002). Strategic computing: DARPA and the quest for machine intelligence, 1983-1993. MIT Press.
Shrestha, Y. R., Ben-Menahem, S. M., & Von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61, 66–83.
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., . . . others. (2016). Mastering the game of Go with deep neural networks and tree search. nature, 529, 484–489
Suwajanakorn, S., Seitz, S. M., & Kemelmacher-Shlizerman, I. (2017). Synthesizing obama: learning lip sync from audio. ACM Transactions on Graphics (ToG), 36, 1–13.
Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61, 15–42.
Thomson, J. J. (1976). Killing, letting die, and the trolley problem. The Monist, 59, 204–217.
Thys, S., Van Ranst, W., & Goedemé, T. (2019). Fooling automated surveillance cameras: adversarial patches to attack person detection. Proceedings of the IEEE/CVF Conference on Computer
Toyama, K. (2018). The Great Digital China. China Review International, 25, 265–269.
Turing, A., & Haugeland, J. (1950). Computing machinery and intelligence. MIT Press Cambridge, MA.
Vision and Pattern Recognition Workshops, (pp. 0–0).
Voigt, P., & Von dem Bussche, A. (2017). The eu general data protection regulation (gdpr). A Practical Guide, 1st Ed., Cham: Springer International Publishing, 10, 3152676.
Wilson, B., Hoffman, J., & Morgenstern, J. (2019). Predictive inequity in object detection. arXiv preprint arXiv:1902.11097.
Zuckerberg, M. (2019). The Internet needs new rules. Let’s start in these four areas.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Global Spectrum of Research and Humanities
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
