Ethics and responsible AI

About this course

A course for managers, product owners, and specialists who deploy or oversee AI use cases in an organization and want to understand real sources of harm — bias in data, opaque decisions, personal data leaks — rather than principle statements that don't decide anything on their own and don't protect against actual incidents.

Lessons move from mapping your own AI use cases and where bias in data, labels, and feedback loops comes from, through transparency and explainability — 'What to disclose to whom,' 'Explaining a decision to the person it affects,' 'Labeling generated content' — to data handling and process: risk assessment before launch, human in the loop, monitoring and incident response. Each block ends with a document you can hand to a manager or a team.

The course suits people responsible for one or more AI use cases in an organization — product managers, project leads, data specialists. No legal background is required, but you'll need a real, or at least planned, AI use case from your own work to run the assignments against and assemble a finished set of documents.

What you'll learn

• Tell types of AI harm apart and identify who's affected in a given scenario
• Test a system for bias across different user groups
• Decide what to do about a detected imbalance and where technical fixes stop working
• Build a disclosure matrix for different audiences
• Explain a decision to the person it affects
• Document a system and its data for later review
• Assess a use case's risk before launch
• Set up post-launch monitoring and an incident response process

What you'll end up with

• A fairness review report for one system, written for a manager
• A transparency package: disclosure matrix, decision explanation, content labeling
• A data handling document for a product owner and legal
• An operational responsible-AI package for your team, plus a certificate on paid plans

This course doesn't replace legal advice on AI regulation and doesn't hand you ready-made policies for a specific jurisdiction — it's practice in analyzing risks and process, not a book of rules.