Assessing Risks of Language Models in Real-World Scenarios
Recent advancements in language models (LMs) and their usage in various tools have paved the way for semi-autonomous agents that operate in real-world scenarios. While these agents bring about exciting possibilities and enhanced capabilities, they also pose significant risks if not properly managed. Failures to follow instructions could lead to serious consequences such as financial losses, property damage, and even life-threatening situations. It is crucial, therefore, to thoroughly assess and identify any potential risks associated with these language models before deploying them.
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