typo fix (#1524)

malevolent

Author: meg-huggingface

red-teaming.md

@@ -62,7 +62,7 @@ Here is a list of ideas for jailbreaking a LLM according to ChatGPT itself.
 
 Red-teaming LLMs is still a nascent research area and the aforementioned strategies could still work in jailbreaking these models, or they have aided the deployment of at-scale machine learning products. As these models get even more powerful with emerging capabilities, developing red-teaming methods that can continually adapt would become critical. Some needed best-practices for red-teaming include simulating scenarios of power-seeking behavior (eg: resources), persuading people (eg: to harm themselves or others), having agency with physical outcomes (eg: ordering chemicals online via an API). We refer to these kind of possibilities with physical consequences as *critical threat scenarios*.
 
-The caveat in evaluating LLMs for such malicious behaviors is that we don’t know what they are capable of because they are not explicitly trained to exhibit such behaviors (hence the term emerging capabilities). Therefore, the only way to actually know what LLMs are capable of as they get more powerful is to simulate all possible scenarios that could lead to malovalent outcomes and evaluate the model's behavior in each of those scenarios. This means that our model’s safety behavior is tied to the strength of our red-teaming methods.
+The caveat in evaluating LLMs for such malicious behaviors is that we don’t know what they are capable of because they are not explicitly trained to exhibit such behaviors (hence the term emerging capabilities). Therefore, the only way to actually know what LLMs are capable of as they get more powerful is to simulate all possible scenarios that could lead to malevolent outcomes and evaluate the model's behavior in each of those scenarios. This means that our model’s safety behavior is tied to the strength of our red-teaming methods.
 
 Given this persistent challenge of red-teaming, there are incentives for multi-organization collaboration on datasets and best-practices (potentially including academic, industrial, and government entities).
 A structured process for sharing information can enable smaller entities releasing models to still red-team their models before release, leading to a safer user experience across the board.