AI Doesn’t Always Get It Right

Posted on Thursday, 23 October 2025

AI is powerful, but it’s not perfect. Even the smartest algorithms can make mistakes, sometimes in ways that seem obvious to humans. Understanding AI’s limitations helps us use it safely and spot when it might be misleading us.

AI systems learn patterns from data. If the data is biased, incomplete, or outdated, the AI can produce incorrect results.

Some common reasons for errors include:

  • Incomplete or biased training data: AI can only “know” what it has been shown. If the training is based on a biased or incorrect data, then the AI tool may provide biased or incomplete information.
  • Misinterpreted context: AI struggles with nuance, sarcasm, or cultural references.
  • Overconfidence: AI can present wrong answers as if they are correct. These types of answers are called hallucinations.
  • Generative errors: Tools that create text, images, or audio might produce impossible or illogical results.
Real-World Examples of AI Getting it Wrong

  • AI chatbots have been caught inventing court cases, offering misinformation about company policies, and creating images with impossible physics or proportions.
  • Translation errors: AI translation tools can sometimes turn simple phrases into confusing, or even alarming messages. For example, Samsung’s AI chatbot once mistranslated the Korean phrase for ‘I love you’ into ‘I will murder you.’
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