Combating Misinformation in the Age of LLMs: Opportunities and Challenges

TL;DR

This paper reviews the potential and challenges of using Large Language Models to fight misinformation, emphasizing opportunities for leveraging their knowledge and reasoning, while addressing risks of LLM-generated false information.

Contribution

It provides a systematic review of misinformation mitigation strategies before LLMs and discusses future directions for utilizing LLMs to combat misinformation and LLM-generated falsehoods.

Findings

LLMs offer promising tools for misinformation detection and correction.

LLMs can be exploited to generate convincing misinformation at scale.

Interdisciplinary efforts are needed to address LLM-related misinformation challenges.

Abstract

Misinformation such as fake news and rumors is a serious threat on information ecosystems and public trust. The emergence of Large Language Models (LLMs) has great potential to reshape the landscape of combating misinformation. Generally, LLMs can be a double-edged sword in the fight. On the one hand, LLMs bring promising opportunities for combating misinformation due to their profound world knowledge and strong reasoning abilities. Thus, one emergent question is: how to utilize LLMs to combat misinformation? On the other hand, the critical challenge is that LLMs can be easily leveraged to generate deceptive misinformation at scale. Then, another important question is: how to combat LLM-generated misinformation? In this paper, we first systematically review the history of combating misinformation before the advent of LLMs. Then we illustrate the current efforts and present an outlook for these two fundamental questions respectively. The goal of this survey paper is to facilitate the progress of utilizing LLMs for fighting misinformation and call for interdisciplinary efforts from different stakeholders for combating LLM-generated misinformation.