Artificial intelligence as a better constraint against war

In this paper, the author explores the potential application of Artificial Intelligence to decision-making in war, as a means of constraining it. Such emerging technology will only become more prominent and should be evaluated thoroughly. The paper first discusses the principles of jus ad bellum and...

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Main Author: Lim, Nicholas Ding Feng
Other Authors: Andrew T. Forcehimes
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/180877
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1808772024-11-02T17:01:16Z Artificial intelligence as a better constraint against war Lim, Nicholas Ding Feng Andrew T. Forcehimes School of Humanities forcehimes@ntu.edu.sg Arts and Humanities In this paper, the author explores the potential application of Artificial Intelligence to decision-making in war, as a means of constraining it. Such emerging technology will only become more prominent and should be evaluated thoroughly. The paper first discusses the principles of jus ad bellum and jus in bello from just war theory. While intended to reduce the harm of war, the theory’s claim weakens our intuition about morality. The author also discusses issues faced by human decision-makers when considering how past costs should affect subsequent decisions. The author put forward the impartiality feature of such technology, taking in collective considerations as the key difference in reducing the harms of war. Artificial Intelligence in decision-making represents an opportunity to leverage in the ethical conduct of war. It has the potential as the next step of development in just war theory, seeking to minimize harm as the primary goal. Bachelor's degree 2024-10-31T10:58:35Z 2024-10-31T10:58:35Z 2024 Final Year Project (FYP) Lim, N. D. F. (2024). Artificial intelligence as a better constraint against war. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/180877 https://hdl.handle.net/10356/180877 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Arts and Humanities
spellingShingle Arts and Humanities
Lim, Nicholas Ding Feng
Artificial intelligence as a better constraint against war
description In this paper, the author explores the potential application of Artificial Intelligence to decision-making in war, as a means of constraining it. Such emerging technology will only become more prominent and should be evaluated thoroughly. The paper first discusses the principles of jus ad bellum and jus in bello from just war theory. While intended to reduce the harm of war, the theory’s claim weakens our intuition about morality. The author also discusses issues faced by human decision-makers when considering how past costs should affect subsequent decisions. The author put forward the impartiality feature of such technology, taking in collective considerations as the key difference in reducing the harms of war. Artificial Intelligence in decision-making represents an opportunity to leverage in the ethical conduct of war. It has the potential as the next step of development in just war theory, seeking to minimize harm as the primary goal.
author2 Andrew T. Forcehimes
author_facet Andrew T. Forcehimes
Lim, Nicholas Ding Feng
format Final Year Project
author Lim, Nicholas Ding Feng
author_sort Lim, Nicholas Ding Feng
title Artificial intelligence as a better constraint against war
title_short Artificial intelligence as a better constraint against war
title_full Artificial intelligence as a better constraint against war
title_fullStr Artificial intelligence as a better constraint against war
title_full_unstemmed Artificial intelligence as a better constraint against war
title_sort artificial intelligence as a better constraint against war
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/180877
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