Research Article
College Students’ Perceptions of AI-based Bullying Prevention: Ethical Safeguards, Human Oversight, and Responsible System Design
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 187 - Issue 133 |
| Published: August 2026 |
| Authors: Suhair Amer, Seth Turner |
10.5120/ijca6781965f3c1f
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Suhair Amer, Seth Turner . College Students’ Perceptions of AI-based Bullying Prevention: Ethical Safeguards, Human Oversight, and Responsible System Design. International Journal of Computer Applications. 187, 133 (August 2026), 32-39. DOI=10.5120/ijca6781965f3c1f
@article{ 10.5120/ijca6781965f3c1f,
author = { Suhair Amer,Seth Turner },
title = { College Students’ Perceptions of AI-based Bullying Prevention: Ethical Safeguards, Human Oversight, and Responsible System Design },
journal = { International Journal of Computer Applications },
year = { 2026 },
volume = { 187 },
number = { 133 },
pages = { 32-39 },
doi = { 10.5120/ijca6781965f3c1f },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2026
%A Suhair Amer
%A Seth Turner
%T College Students’ Perceptions of AI-based Bullying Prevention: Ethical Safeguards, Human Oversight, and Responsible System Design%T
%J International Journal of Computer Applications
%V 187
%N 133
%P 32-39
%R 10.5120/ijca6781965f3c1f
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Artificial Intelligence (AI) systems increasingly influence communication, education, and decision-making processes. While these systems can promote positive interaction, they also risk enabling or amplifying bullying behaviors—either by generating harmful content, reinforcing social biases, or allowing harassment on AI-driven platforms. This paper examines analytical and ethical strategies to prevent bullying in AI systems. It explores design considerations, dataset ethics, moderation mechanisms, and alignment methods aimed at fostering empathetic, safe, and equitable AI interactions. Recommendations include ethical data curation, multi-layered safety filters, human-in-the-loop moderation, and digital literacy initiatives to ensure AI supports rather than harms users.
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