What Kinds of Mistakes Do AI Models Make?
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LESSON 4 - ARTIFICIAL INTELLIGENCE FOUNDATIONS FOR BROADENING CULTURAL HORIZONS
What Kinds of Mistakes Do AI Models Make?
In this lesson, we analyze two types of errors language models can make: classification errors and hallucinations. We also anticipate another source of error: social biases, also known as stereotypes. A classification error occurs when the model assigns an incorrect category to a text or image. Hallucinations, on the other hand, involve presenting false or generated information as if it were true, even citing non-existent sources that seem plausible at first glance. These situations can reinforce automation bias, as we tend to trust responses that sound technical or well-founded. We review complex examples, such as incorrect medical interpretations of X-rays or errors in dosage calculations, even when the model uses official sources via Retrieval-Augmented Generation (RAG) systems.As a case study on classification errors, we analyze the difficulty of distinguishing human-written text from AI-generated text, and how even detection tools can fail. Through concrete examples, we examine how models can mix up information, commit inaccuracies, or make mathematical miscalculations. This lesson invites us to present a critical mindset by recognizing the ways AI makes mistakes and why those errors are often difficult to detect.
At the end of the lesson, you will be asked to answer a few questions.
👩🏫 Instructor: Luciana Benotti-
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