Summary of Llm Echo Chamber: Personalized and Automated Disinformation, by Tony Ma
LLM Echo Chamber: personalized and automated disinformation
by Tony Ma
First submitted to arxiv on: 24 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Recent advancements in Large Language Models (LLMs) like GPT4 and Llama2 have demonstrated capabilities in tasks such as summarization, translation, and content review. However, their widespread use raises concerns about the potential for LLMs to spread persuasive, humanlike misinformation at scale, significantly influencing public opinion. This study examines these risks by investigating the ability of LLMs to propagate misinformation as factual. The researchers built a controlled digital environment, simulating social media chatrooms where misinformation often spreads, called the LLM Echo Chamber. By studying malicious bots spreading misinformation in this environment, the authors can better understand this phenomenon. The study reviewed current LLMs, explored misinformation risks, and applied state-of-the-art (SOTA) finetuning techniques using Microsoft’s phi2 model, finetuned with a custom dataset to generate harmful content for the Echo Chamber. This setup was evaluated by GPT4 for persuasiveness and harmfulness, shedding light on ethical concerns surrounding LLMs and emphasizing the need for stronger safeguards against misinformation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at how Large Language Models can spread false information. These models are very good at pretending to be human and can write articles, emails, and even entire books that sound real. But this means they could also be used to spread lies and tricks. The researchers created a special computer program to see how well the models could do this. They found that these models are very good at spreading false information and could potentially cause big problems if not controlled. |
Keywords
» Artificial intelligence » Summarization » Translation
