How can we enhance AI training data for better performance?

How can we enhance AI training data for better performance?

Improving AI training data involves increasing its quality, diversity, and relevance. What specific areas are you interested in?

I'm particularly concerned about bias in the training data.

Addressing bias can be done by ensuring diverse representation in the data and regularly auditing datasets for fairness.

What techniques can we use to identify and reduce bias?

Techniques include using fairness metrics, conducting bias audits, and employing data augmentation strategies to balance the dataset.

Can you suggest some tools for auditing training data?

Sure! Tools like Fairness Flow, AI Fairness 360, and What-If Tool can help in auditing and analyzing training data for bias.