Ethics Testing: Proactive Identification of Generative AI System Harms
Generative Artificial Intelligence (GAI) systems that can automatically generate content in the form of source code or other contents (e.g., images) has seen increasing popularity due to the emergence of tools such as ChatGPT which rely on Large Language Models (LLMs). Misuse of the automatically generated content can incur serious consequences due to potential harms in the generated content. Despite the importance of ensuring the quality of automatically generated content, there is little to no approach that can systematically generate tests for identifying software harms in the content generated by these GAI systems. In this article, we introduce the novel concept of ethics testing whic...
| Authors | Shin Hwei Tan, Haibo Wang, Heng Li |
|---|---|
| Primary category | cs.SE |
| Published | 23 April 2026 |
| Last updated at source | 23 April 2026 |
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