Approaches to Generative Artificial Intelligence, A Social Justice Perspective

TL;DR

This paper examines the societal impacts of generative AI, focusing on issues of bias, fairness, and justice, especially in education and intellectual property, amidst rapid technological adoption.

Contribution

It offers a social justice perspective on generative AI, analyzing biases, ethical concerns, and challenges in detection and fairness, which are often overlooked in technical discussions.

Findings

Generative AI models exhibit inherent biases affecting marginalized groups.

AI detection methods face challenges due to evolving AI writing capabilities.

Social justice issues are critical in shaping equitable AI policies and practices.

Abstract

In the 2023-2024 academic year, the widespread availability of generative artificial intelligence, exemplified by ChatGPT's 1.6 billion monthly visits, is set to impact academic integrity. With 77% of high school students previously reporting engagement in dishonest behaviour, the rise of AI-driven writing assistance, dubbed 'AI-giarism' by Chan (arXiv:2306.03358v2), will make plagiarism more accessible and less detectable. While these concerns are urgent, they also raise broader questions about the revolutionary nature of this technology, including autonomy, data privacy, copyright, and equity. This paper aims to explore generative AI from a social justice perspective, examining the training of these models, the inherent biases, and the potential injustices in detecting AI-generated writing.