This study examines how large language models can be leveraged to combat political misinformation through a two-step prompting approach.

• Models struggled with reliable source identification and evidence grounding
• A chain-of-thought prompting strategy was implemented: first identifying credible sources, then crafting persuasive responses
• Research evaluated performance of ChatGPT, Gemini, and Claude in countering political falsehoods
• Findings have significant security implications for combating misinformation campaigns

By understanding these limitations and capabilities, organizations can better develop AI tools that help maintain information integrity in digital spaces.

An Empirical Analysis of LLMs for Countering Misinformation