Design & Present Responsible AI Solutions

This course is part of multiple programs.

Instructors: Starweaver

Access provided by EDGE Group

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Evaluate AI use cases by applying key Responsible AI principles such as fairness, transparency, and accountability.
Identify and document potential risks and biases across data, models, and user interactions using structured ethical design tools.
Develop and communicate stakeholder-ready presentations and documentation that clearly articulate Responsible AI design decisions.

Skills you'll gain

Design
Accountability
Governance
Responsible AI
Ethical Standards And Conduct
Project Documentation
Artificial Intelligence
Stakeholder Analysis
Data Storytelling
Case Studies
Risk Mitigation
Presentations
Risk Management
Stakeholder Communications
Technical Communication
Data Ethics
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Assessments

1 assignment

Taught in English

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There are 3 modules in this course

In an era where artificial intelligence influences hiring, healthcare, finance, and everyday decision-making, the demand for Responsible AI design has never been greater. This course empowers professionals, researchers, and innovators to design, evaluate, and communicate AI solutions that are transparent, fair, and trustworthy. Through practical frameworks and guided demos, learners will explore how to apply core Responsible AI principles-fairness, transparency, accountability, privacy, and safety-across the AI lifecycle. You’ll practice identifying bias and ethical risks, documenting safeguards using structured templates, and transforming complex technical work into clear, stakeholder-ready presentations. Real-world examples and corporate case studies demonstrate how leading organizations operationalize Responsible AI.

This course is for AI, data, ethics, and tech professionals who want to design and present transparent, fair, and responsible AI solutions. Ideal for developers, policymakers, and business leaders, it helps you apply Responsible AI principles and communicate them clearly to diverse stakeholders. Learners should have a basic understanding of AI/ML concepts, familiarity with data ethics, and the ability to present ideas clearly to non-technical audiences. By the end of this course, you’ll confidently design ethically sound AI solutions and present them persuasively to both technical and non-technical audiences.

This module introduces learners to the foundational concepts of Responsible AI - exploring why ethical design, transparency, and accountability matter in modern AI systems. Learners will examine the core principles of Responsible AI, understand how bias and harm can emerge throughout the AI lifecycle, and discover how to embed ethical considerations into every stage of AI solution design. Through real-world case examples and structured reflection, this module establishes the mindset and vocabulary needed to design AI systems that are both innovative and trustworthy.

What's included

4 videos2 readings1 peer review

4 videos Total 23 minutes

Welcome to Responsible AI Design 4 minutes
Why Responsible AI Matters 5 minutes
The Core Principles of Responsible AI 7 minutes
From Principles to Practice: Designing with Ethics in Mind 6 minutes

2 readings Total 10 minutes

Welcome to the Course: Course Overview 5 minutes
Responsible AI: Why It Matters and How We’re Infusing It at Microsoft 5 minutes

1 peer review Total 20 minutes

Hands-On-Learning: Responsible AI Risk Reflection 20 minutes

This module guides learners through the practical process of integrating Responsible AI principles into real-world system design. Learners will explore how to identify and mitigate ethical risks, detect and document bias, and evaluate model performance beyond accuracy metrics. They will learn to apply tools such as Responsible AI canvases, risk logs, and model cards to ensure transparency and accountability across the AI development lifecycle. By the end of the module, learners will be able to design AI systems that align with organizational values, regulatory standards, and human-centered goals.

What's included

3 videos1 reading1 peer review

3 videos Total 22 minutes

Embedding Ethics into the AI Lifecycle 7 minutes
Using Responsible AI Canvases and Checklists 7 minutes
Reducing Bias and Communicating Uncertainty 8 minutes

1 reading Total 5 minutes

Building Trustworthy AI: How Google Designs for Transparency and Fairness (2024) 5 minutes

1 peer review Total 20 minutes

Hands-On-Learning: Responsible AI Design Challenge 20 minutes

This module focuses on transforming Responsible AI design work into clear, stakeholder-ready communication. Learners will discover how to structure and deliver presentations that effectively convey technical rigor, ethical awareness, and societal impact. The module covers techniques for visual storytelling, ethical reporting, and audience-tailored messaging to build trust and understanding among diverse stakeholders-executives, regulators, and the public alike. By the end of the module, learners will be able to craft compelling presentations and documentation that demonstrate both AI innovation and accountability.