The official term in the field of AI is "hallucination." This refers to the fact that it sometimes "makes stuff up." This is because these systems are probabilistic, not deterministic. When you prompt it, it draws on all the data it has been fed and looks for patterns. It produces an answer based on the probability that it is the correct answer based on your prompt and the data on which it has been trained.
GPT-4 (the more capable model behind ChatGPT Plus and Microsoft Copilot) has improved and is less prone to hallucination. According to OpenAI, it's "40% more likely to produce factual responses than GPT-3.5 on our internal evaluations." But it's still not perfect. So verification of the output is still needed.
One area where ChatGPT usually gives fictional answers is when asked to create a list of sources. See this CNBC story for an explanation: AI Chatbots Can 'Hallucinate' and Make Things Up--Why it Happens and How to Spot it.
Generative AI tools can create answers that are plausible but incorrect. Luckily, there is progress in making these systems more truthful by grounding them in external sources of knowledge, which means some chatbots are beginning to link their answers to sources from which they got the information. Some examples are Microsoft Copilot and Perplexity AI, which use internet search results to ground answers. However, the Internet sources used, could also contain misinformation or disinformation. But at least with Copilot and Perplexity you can link to the sources used to begin verification.
Image Attribution: "Mastering the Art of Persuasion: Sales + Marketing" by webartgallery, Deviant Art is licensed under CC BY 3.0
There are also systems that combine language models with scholarly sources. For example: