NCA-GENL Question 227
Select 3A company is deploying a generative AI language model to assist with customer service inquiries. During testing, they discover that the model produces biased responses based on the gender and ethnicity of the customer names in the input data. Which of the following actions should the company take to minimize bias in the AI system?
- A
Diversify and balance the training dataset to include a wide range of demographic groups.
- B
Use bias detection tools to identify and address biased patterns in the model's outputs.
- C
Remove all demographic information from the dataset to avoid any possibility of bias.
- D
Apply fine-tuning techniques with domain-specific data that emphasize fairness and inclusivity.
- E
Focus only on increasing the dataset size rather than addressing demographic representation.
Show answer and explanation
Correct answers: A, B, D
Explanation
Minimizing bias in AI systems requires a multifaceted approach that includes improving data diversity, using bias detection tools, and applying fine-tuning techniques that prioritize fairness and inclusivity. Simply removing demographic information or increasing dataset size without addressing representation does not effectively address the root causes of bias.
- A. Correct.
Diversifying and balancing the training dataset helps ensure that the model is exposed to and learns from a representative sample of all demographic groups, reducing bias.
- B. Correct.
Using bias detection tools allows the company to identify biased patterns in the model's outputs, which is an important step in mitigating bias during development.
- C. Incorrect.
Simply removing demographic information from the dataset does not necessarily eliminate bias, as it may still exist in other features or patterns within the data.
- D. Correct.
Fine-tuning with domain-specific data that emphasizes fairness helps the model better align with ethical and inclusive practices, reducing bias in its outputs.
- E. Incorrect.
Increasing the dataset size without addressing demographic representation will not reduce bias and may even exacerbate it if the imbalance in the data persists.