Building Responsible AI Algorithms (e-book) (used book) | bookbook.eu

Description

This book introduces a Responsible AI framework and guides you through processes to apply at every stage of the machine learning (ML) life cycle, from problem definition to deployment, to reduce and mitigate the risks and harms found in artificial intelligence (AI) technologies. AI offers the ability to solve many problems today if implemented correctly and responsibly. This book helps you avoid negative impacts - that in some cases have even cost loss of life - and develop models that are fair, transparent, and free from bias.
The approach in this book raises your awareness of the missteps than can lead to negative outcomes and provides a framework by which to deliver responsible and ethical results in ML. It begins with an examination of the foundational elements of responsibility, principles, and data. Next comes guidance on implementation addressing issues such as fairness, safety, transparency, and privacy, including ethical considerations. The book helps you think responsibly while building AI and ML models and take practical steps aimed at delivering responsible models, datasets, and products for your end users and customers.

• Build AI/ML models using Responsible AI frameworks and processes
• Document information on your datasets and improve data quality
• Measure fairness metrics in ML models
• Identify harms and risks per task and run safety evaluations on ML models
• Create transparent AI/ML models
• Develop Responsible AI principles and organizational guidelines