Ethics and Bias

Even at this early stage, it's important to note:

• AI reflects the biases in the data it's trained on
• Training data is not always approved for use by its owners
• LLMs may generate harmful, misleading, or biased content
• AI can perpetuate stereotypes — a key concern in classrooms
• Models can over-represent dominant cultures or viewpoints
• Developers try to reduce these risks, but no model is perfect

Your oversight and professional judgement are crucial.

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While AI bias exists, your clear, specific prompts can help guide it in the right direction.

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A future module will explore this further.