summarizing the article's important points with vicuna-7b: * Modern AI systems require large amounts of data to train, much of which comes from the open web, m

summarizing the article's important points with vicuna-7b: * Modern AI systems require large amounts of data to train, much of which comes from the open web, making them susceptible to data poisoning attacks. * Data poisoning involves adding or modifying information in a training data set to teach an algorithm harmful or undesirable behaviors. * Safety-critical machine-learning systems are usually trained on closed data sets curated and labeled by humans, making poisoned data less likely to go unnoticed. * However, generative AI tools like ChatGPT and DALL-E 2 rely on larger repositories of data scraped directly from the open internet, making them vulnerable to digital poisons injected by anyone with an internet connection. * Researchers from Google, NVIDIA, and Robust Intelligence conducted a study to determine the feasibility of data poisoning schemes in the real world and found that even small amounts of poisoned data could significantly affect an AI's performance. * Some data poisoning attacks can elicit specific reactions in the system, such as causing an AI chatbot to spout untruths or be biased against certain people or political parties. * Ridding training data sets of poisoned material would require companies to know which topics or tasks the attackers are targeting.