Eleven responsible AI objectives to support AI Governance: data quality, task accuracy, fairness, privacy, reliability, transparency, human oversight, evaluation, wider social and environmental effects, data governance, and accessibility.
Engineering Responsible AI brings together five foundation chapters, eleven practical topic sections and a linked coding companion with eleven downloadable Python code packages, sample data, tests and supporting instructions.
An AI system can sound convincing while selecting the wrong record, missing an important referral, exposing private information or hiding a serious failure behind a favorable average. This guide helps you investigate those problems and turn ethical goals into requirements, controls and evidence that people can review.
Start by defining the intended use, affected people and limits of authority. Then work through the eleven objectives, examining both system behavior and the decisions surrounding it.
Connect evaluation to deployment, monitoring, incident response and eventual retirement.
The coding companion makes the questions concrete. Check data against an explicit contract, compare recorded decisions with independent expectations, inspect group error rates, exercise failure handling and examine declared approval and governance records. Accessibility and wider-impact exercises combine calculations with evidence that still requires human review.
The guide is written for developers, technical leads, enterprise architects, AI consultants and managers responsible for introducing AI. The framework does not require Python expertise. The companion targets Python 3.10 or later, uses the standard library and runs locally without an AI API key. Instructions cover Windows PowerShell, macOS and Linux.
Try before you buy: read Task Accuracy and Human Referral from the coding companion and download its accompanying code ZIP. The exercise uses eight synthetic delivery enquiries to examine correct answers, missed referrals and missing outputs.
US$45 includes the digital guide and all eleven companion code packages. Individual support is available separately. These educational assessments support AI governance and compliance work; they do not certify compliance or establish that a real system is ready for deployment.
