When a confident answer is confidently wrong
AI models can write answers that sound clear, detailed, and sure of themselves, but they do not check facts the way a careful researcher does. They predict the most likely next words from patterns they learned in training, so they sometimes produce claims that sound believable and are simply wrong, or even entirely made up. In this lesson you will learn to tell the difference between fluent language and accurate information, and you will practise catching mistakes that are dressed up to look correct.
You will meet real examples of AI getting things wrong, from a chatbot that promised a customer a brand-new car for one pound, to AI inventing court evidence that landed real lawyers in trouble. Some experts prefer the word confabulation to hallucination, because AI has no senses to misread, it simply fills gaps with plausible-sounding detail. To use AI responsibly, you have to question its answers and check them against trusted sources.