Title: 1 Bias And Fairness
Course: LLM_Prompt_Engineering_For_Developers > Section: Module 1: 1 Bias And Fairness

1. Bias and Fairness

Explanation:

LLMs learn from vast datasets that may contain biases present in society. As a result, prompts fed into these models can inadvertently elicit biased responses. It’s crucial to recognize that the language models may replicate or amplify existing societal biases.

Example:

If a developer creates a prompt that elicits gender stereotypes, such as asking for “the qualities of a good nurse,” the model may respond with traditionally feminine traits, reinforcing gender norms.

Mitigation:

Developers should strive to create inclusive prompts that encourage diverse perspectives and avoid framing that could lead to biased outputs.

2. Misuse of AI