DAMAG e R : Deploying Automatic and Manual Approaches to G en AI Red-teaming (2025)

Abstract: In this tutorial, we will review and apply current automatic and manual red-teaming techniques for GenAI models(including LLMs and multimodal models). In doing so, we aim to emphasize the importance of using a mixture of techniques and establishing a balance between automatic and manual approaches. Lastly, we aim to engage tutorial participants in live red-teaming activities to collaboratively learn impactful red-teaming strategies and share insights.

## diversity and inclusion we perceive red-teaming as an exercise that is best conducted with a diverse crowd. as such, we intend to tap into the affinity groups that attend the *acl conferences, such as women in nlp, lat-inx in ai, black in ai, and queer in ai, and encourage them to participate. we believe that researchers with different lived experiences lead to different and effective ways for red-teaming. this is supported by prior work which argues for more stakeholder and marginalized community inclusion upon discovering genai issues such as stereotype reinforcement or lack of support for low-resource languages (e.g., @xcite ). ideally, we could strive to create a community of red-teamers that could meet periodically to conduct virtual red-teaming exercises and write-up our findings. this would be a first step of creating a community that periodically red-teams the latest models. infrastructure such as chat arena ( https://lmarena.ai/ ) can facilitate such exercises. ## ethics statement we recognize that participants will be exposed to harmful and dangerous content in both passive and active manners. before showing any harmful text, we will provide the proper disclaimers and continually let participants know that they may step out at any time if the content is too upsetting. additionally, when the participants are actively red-teaming the models, we will encourage them to take breaks and understand that they are explicitly trying to elicit harmful outputs. our cycling of around 15 minutes on and off for active red-teaming is intentional, so as to reduce mental fatigue as well encourage communal dialogue.