Security News > 2023 > January > Threats of Machine-Generated Text

This paper is a good survey of the field: what the threats are, how we might detect machine-generated text, directions for future research.

Abstract: Advances in natural language generation have resulted in machine generated text that is increasingly difficult to distinguish from human authored text.

Powerful open-source models are freely available, and user-friendly tools democratizing access to generative models are proliferating.

Detection of machine generated text is a key countermeasure for reducing abuse of NLG models, with significant technical challenges and numerous open problems.

We provide a survey that includes both 1) an extensive analysis of threat models posed by contemporary NLG systems, and 2) the most complete review of machine generated text detection methods to date.

This survey places machine generated text within its cybersecurity and social context, and provides strong guidance for future work addressing the most critical threat models, and ensuring detection systems themselves demonstrate trustworthiness through fairness, robustness, and accountability.

News URL

https://www.schneier.com/blog/archives/2023/01/threats-of-machine-generated-text.html