False or misleading information created by artificial intelligence (AI) is presented as factual. They are errors generated by AI. These errors are close enough to the truth or logical enough that they appear to be accurate at first glance. These hallucinations occur in large language models (LLMs) and other AI systems.
Some common AI hallucinations include:
Made-up facts or references: This can include nonexistent legal cases, articles, or studies that are made up by LLMs.
Over-generalizations: This is a statement that's true in one context but not in all of them. For example, all chickens lay eggs. This is true. However, male chickens do not lay eggs.
Prompts misunderstood: The AI or LLMs misunderstand the question and give information based on the question that it thinks it heard.
Repeating errors: Errors or misinformation that exist in the AI's learning dataset will continue to be used in the answers given until the information is corrected.
You should be aware that AI hallucinations exist and the ways they may manifest in the information provided in an AI answer or response. AI is only as good as the datasets it uses and the training it's had. AI hallucinations are a significant challenge that need to be corrected as this new technology becomes more widely accepted and used by the general public.
