Data Skeptic
LLMs for Evil
Sep 25, 2023
Maximilian Mozes, PhD student at the University College, London, specializing in NLP and adversarial machine learning, discusses the potential malicious uses of Large Language Models (LLMs), challenges of detecting AI-generated harmful content, reinforcement learning with Human Feedback, limitations and safety concerns of LLMs, threats of data poisoning and jailbreaking, and approaches to avoid issues with LLMs.
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Quick takeaways
- The use of large language models (LLMs) for illicit purposes, such as generating phishing emails and malware, highlights the need for preventive measures and safeguards.
- Two major threats associated with LLMs are personalization, which can result in both helpful and harmful content tailored to individual users, and the generation of misinformation that challenges the ability to distinguish between credible and fabricated information, impacting society and trust in online content.
Deep dives
Illicit Uses of Large Language Models
Large language models (LLMs) have the potential to be misused for illicit purposes. One example is the generation of phishing emails, where LLMs can automatically generate convincing scam emails. Additionally, LLMs can be used to generate malware, as demonstrated in research. Another concern is the generation of misinformation, where LLMs can fabricate false information that is difficult to distinguish from credible sources. These illicit uses highlight the need for preventive measures and safeguards.
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