Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/170526
Title: Content-filtering AI systems–limitations, challenges and regulatory approaches
Authors: Marsoof, Althaf
Luco, Andrés
Tan, Harry
Joty, Shafiq
Keywords: Business::Law
Engineering::Computer science and engineering
Issue Date: 2023
Source: Marsoof, A., Luco, A., Tan, H. & Joty, S. (2023). Content-filtering AI systems–limitations, challenges and regulatory approaches. Information and Communications Technology Law, 32(1), 64-101. https://dx.doi.org/10.1080/13600834.2022.2078395
Journal: Information and Communications Technology Law
Abstract: Online service providers, and even governments, have increasingly relied on Artificial Intelligence (‘AI’) to regulate content on the internet. In some jurisdictions, the law has incentivised, if not obligated, service providers to adopt measures to detect, track, and remove objectionable content such as terrorist propaganda. Consequently, service providers are being pushed to use AI to moderate online content. However, content-filtering AI systems are subject to limitations that affect their accuracy and transparency. These limitations open the possibility for legitimate content to be removed and objectionable content to remain online. Such an outcome could endanger human well-being and the exercise of our human rights. In view of these challenges, we argue that the design and use of content-filtering AI systems should be regulated. AI ethics principles such as transparency, explainability, fairness, and human-centricity should guide such regulatory efforts.
URI: https://hdl.handle.net/10356/170526
ISSN: 1360-0834
DOI: 10.1080/13600834.2022.2078395
Schools: School of Computer Science and Engineering 
Nanyang Business School 
School of Humanities 
Rights: © 2022 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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