Deep learning artificial intelligence and the law of causation: Application, challenges and solutions

Artificial Intelligence technology has rapidly advanced in this era. Many of the AI appliances nowadays have been infused with abilities to self-develop their knowledge and self-enhance their operational precision through machine learning. The emergence of deep learning technology, a sub-set of mach...

Full description

Saved in:
Bibliographic Details
Main Authors: Lee, Zhao Yan, Karim, Mohammad Ershadul, Ngui, Kevin
Format: Article
Published: Routledge Journals 2021
Subjects:
Online Access:http://eprints.um.edu.my/34958/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.um.eprints.34958
record_format eprints
spelling my.um.eprints.349582022-05-24T02:45:03Z http://eprints.um.edu.my/34958/ Deep learning artificial intelligence and the law of causation: Application, challenges and solutions Lee, Zhao Yan Karim, Mohammad Ershadul Ngui, Kevin K Law (General) Artificial Intelligence technology has rapidly advanced in this era. Many of the AI appliances nowadays have been infused with abilities to self-develop their knowledge and self-enhance their operational precision through machine learning. The emergence of deep learning technology, a sub-set of machine learning, which observes AI mimicking after the way a human brain functions, presents an even more revolutionary step towards perfecting AI's accuracy, precision and efficiency. Similar to a human brain, the cognitive process of the deep learning AI, through its artificial neurons, is not decipherable. This presents a fundamental legal / constitutional problem for most jurisdictions across the world, where any errors or mistakes made by the concerned AI algorithm, are attributable to none other than itself. This research identifies major issues in relation to the application of the law of causation in an AI's case, in effort to propose solutions in this dilemma of justice. Routledge Journals 2021-09 Article PeerReviewed Lee, Zhao Yan and Karim, Mohammad Ershadul and Ngui, Kevin (2021) Deep learning artificial intelligence and the law of causation: Application, challenges and solutions. Information & Communications Technology Law, 30 (3). pp. 255-282. ISSN 1360-0834, DOI https://doi.org/10.1080/13600834.2021.1890678 <https://doi.org/10.1080/13600834.2021.1890678>. 10.1080/13600834.2021.1890678
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic K Law (General)
spellingShingle K Law (General)
Lee, Zhao Yan
Karim, Mohammad Ershadul
Ngui, Kevin
Deep learning artificial intelligence and the law of causation: Application, challenges and solutions
description Artificial Intelligence technology has rapidly advanced in this era. Many of the AI appliances nowadays have been infused with abilities to self-develop their knowledge and self-enhance their operational precision through machine learning. The emergence of deep learning technology, a sub-set of machine learning, which observes AI mimicking after the way a human brain functions, presents an even more revolutionary step towards perfecting AI's accuracy, precision and efficiency. Similar to a human brain, the cognitive process of the deep learning AI, through its artificial neurons, is not decipherable. This presents a fundamental legal / constitutional problem for most jurisdictions across the world, where any errors or mistakes made by the concerned AI algorithm, are attributable to none other than itself. This research identifies major issues in relation to the application of the law of causation in an AI's case, in effort to propose solutions in this dilemma of justice.
format Article
author Lee, Zhao Yan
Karim, Mohammad Ershadul
Ngui, Kevin
author_facet Lee, Zhao Yan
Karim, Mohammad Ershadul
Ngui, Kevin
author_sort Lee, Zhao Yan
title Deep learning artificial intelligence and the law of causation: Application, challenges and solutions
title_short Deep learning artificial intelligence and the law of causation: Application, challenges and solutions
title_full Deep learning artificial intelligence and the law of causation: Application, challenges and solutions
title_fullStr Deep learning artificial intelligence and the law of causation: Application, challenges and solutions
title_full_unstemmed Deep learning artificial intelligence and the law of causation: Application, challenges and solutions
title_sort deep learning artificial intelligence and the law of causation: application, challenges and solutions
publisher Routledge Journals
publishDate 2021
url http://eprints.um.edu.my/34958/
_version_ 1735409639750631424
score 13.188404