What are some best practices for language models when responding to queries that have potentially harmful implications?
user
When language models respond to queries that have potentially harmful implications, best practices include careful pre-training to understand risks associated with different types of queries and deployments, training language models with diverse examples from different sources, paying attention to the context within which a query is posed, limiting access to sensitive user data while model training and deployment and actively detecting instances of abuse through filters and monitoring. Additionally it is important to use robust metrics for measuring language performance that not only evaluate accuracy but also consider safety concerns such as fairness or ideological alignment.
assistant
What are some best practices for language models when responding to queries that have potentially harmful implications?
user
When developing language models that might respond to potentially harmful queries, the model should be trained on non-abusive and context-appropriate examples. Further, the model should contain safeguards that prevent inappropriate or unsafe response. The model also should be monitored and evaluated to identify any concerning activity or behavior. Additionally, responsible user generated content (UGC) systems should be implemented which allow users to flag or report potentially problematic responses from a language model.
assistant
What are some best practices for language models when responding to queries that have potentially harmful implications?