Not all the time.
Outputs of AI models used today are predictions, rules or actions based on existing datasets and instructions, on which the AI was trained. AI models offer probabilities and therefore carry inherent uncertainty. Generative AI can create content, including text, images, audio or video, when prompted by a user, but it is not cognitive and lacks human judgment.
Accuracy in AI (and, more generally, in statistical modelling) refers to how often an AI system guesses the correct answer. No AI system can be 100% accurate—there will always be the possibility of false negatives and false positives.
Generative AI systems require a user to submit prompts that guide the generation of new content. However, many iterations may be required to produce the intended result because generative AI is sensitive to the wording of prompts.
AI produces predictions based on recognizing patterns from their training data.
No AI system can be 100% accurate—false negatives and false positives are possible.
Generative AI can create new content when prompted to do so by a user, but multiple attempts may be needed to achieve the desired outcome.
IEEE Spectrum: Seven Revealing Ways AIs Fail
White House Office of Science and Technology Policy: National Artificial Intelligence Initiative Office