Responsible Machine Learning
Big risks. Big rewards.
Like many powerful technologies, AI and machine learning offer tangible opportunities—but also significant risks. This free report outlines the best practices that will allow you to mitigate those risks and innovate with machine learning safely and responsibly.
Authors Patrick Hall, Navdeep Gill, and Ben Cox focus on both the technical issues of machine learning (ML) and human-centered issues such as security, fairness, and privacy, exploring vital topics such as:
- Why an organization’s ML culture is an important aspect of responsible practice
- How to change or update your processes to govern ML assets
- Tools that can help you build human trust and understanding into your ML systems
- Core considerations for companies that want to drive value from ML
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