How can I train AI fairly?

What are the key principles for training AI fairly?

Key principles include transparency, accountability, and inclusivity in data selection.

How can I ensure my training data is unbiased?

You can ensure unbiased training data by diversifying your data sources and regularly auditing your datasets.

What are some common pitfalls in AI training?

Common pitfalls include overfitting, lack of diversity in training data, and ignoring ethical considerations.

Can you recommend resources for learning more about fair AI training?

Sure! Look into the Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) conference papers and guidelines.