AI and ML ethics and safety
Summary
Guidance on ethical considerations for ML projects, covering fairness, privacy, transparency, and safety per Google's AI principles.
Key quotes
ML models should benefit society and avoid causing harm, bias, or misuse of personal data.
Fairness in models requires addressing potential biases in training data and ensuring equitable outcomes for all user groups.
Privacy considerations involve adhering to relevant regulations, protecting personal data, and ensuring secure data handling practices.
Transparency and safety involve making model functionality understandable, documenting model details, and designing models to operate securely and reliably.
This Google Developers page outlines ethical guidelines for machine learning projects, referencing Google’s Responsible AI principles. It provides practical advice for ensuring fairness, privacy, transparency, and safety in model development.