AI Ethics & Responsible Use of Generative AI

Name: AI Ethics & Responsible Use of Generative AI
Rating: 4.4 (9 reviews)

Learn AI ethics, bias, privacy, hallucinations, synthetic media, safety, and responsible generative AI use

Created bySATCOM & Technology School

Last updated 8/2026

English

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What you'll learn

Understand the core ethical principles and risks involved in the responsible use of generative AI
Identify and reduce risks related to AI bias, misinformation, privacy, sensitive data, and synthetic media.
Apply responsible practices for using generative AI in education, creative work, and the workplace.
Evaluate AI-generated outputs using verification, human oversight, accountability, and risk-based safeguards.
Recognize how bias can enter generative AI systems and lead to unfair or unequal outcomes
erify AI-generated claims and recognize the risks of hallucinations, misleading content, and synthetic media
Protect privacy and sensitive information when interacting with generative AI tools
Understand authorship, attribution, plagiarism, and ownership issues in AI-assisted creative work
Determine when human oversight is necessary based on the potential consequences of an AI-assisted decision
Use a practical framework to assess AI use before, during, and after interacting with a generative AI system

Course content

5 sections • 13 lectures • 1h 39m total length

Introduction5:33
This introduction explores what responsible use of generative AI means and why human judgment remains essential. You will learn why fluent AI outputs are not necessarily accurate or appropriate, and discover the key ethical questions surrounding accuracy, fairness, privacy, ownership, and accountability.
Introduction

What Generative AI Creates6:20
Learn what generative AI can create, from text and images to code, audio, and video. This lesson explains how generated content differs from simple information retrieval and introduces the key limitations, risks, and responsibilities associated with each type of AI-generated output.
What Generative AI Creates
How Generative AI Produces Output7:15
Discover how generative AI turns prompts into new content using training data, learned patterns, tokens, and probabilistic generation. This lesson explains the basic mechanics behind AI outputs and why understanding them is essential for recognizing limitations, errors, and potential bias.
How Generative AI Produces Output
Fluency Is Not Understanding6:58
Learn why fluent and confident AI responses should not be mistaken for genuine understanding or verified knowledge. This lesson explores the differences between fluency, factual accuracy, intention, judgment, and responsibility, and explains why human oversight remains essential.
Fluency Is Not Understanding
Ethics Beyond the Model7:05
Explore AI ethics beyond the technology itself. This lesson examines how design choices, training data, deployment, incentives, product interfaces, and human decisions shape the impact of generative AI, while highlighting the importance of context, accountability, and considering everyone affected.
Ethics Beyond the Model

Sources of AI Bias7:43
Learn where bias in generative AI can come from and why it is rarely caused by a single factor. This lesson explores how social patterns, training data, human labeling, model design, proxy variables, deployment choices, and feedback loops can contribute to unfair or unequal outcomes.
Sources of AI Bias
How Bias Appears in Outputs8:21
Explore how bias can appear in AI-generated text, images, translations, recommendations, and automated assistance. This lesson shows how stereotypes, assumptions, and omissions can influence outputs and introduces practical ways to identify and reduce unfair patterns.
How Bias Appears in Outputs
Unequal Effects on People8:01
Learn why the same AI system can affect people differently depending on their needs, resources, language, accessibility, and circumstances. This lesson explores the difference between equal treatment and fair access, with practical examples from hiring, education, public services, and everyday AI use.
Unequal Effects on People
Reducing Bias in Practice7:44
Learn practical ways to identify and reduce bias in generative AI systems. This lesson explores diverse testing, training-data curation, human review, user feedback, ongoing monitoring, and documentation while highlighting the limitations and trade-offs of each approach.
Reducing Bias in Practice

Why AI Hallucinates8:11
Learn why generative AI can produce confident and convincing information that is false or unsupported. This lesson explains how hallucinations arise, when they are more likely to occur, and how verification, reliable sources, and proportionate human review can reduce the risks.
Why AI Hallucinates
Verifying AI-Generated Claims7:51
Learn how to verify AI-generated claims before relying on or sharing them. This lesson introduces proportional verification and practical methods for checking facts, summaries, quotations, calculations, and references using appropriate and reliable sources.
Verifying AI-Generated Claims
Understanding Synthetic Media7:49
Learn what synthetic media is and why realistic content is not necessarily authentic. This lesson explores AI-generated images, voice cloning, and video, while examining key issues such as provenance, consent, impersonation, reputation, and responsible verification.
Understanding Synthetic Media

Requirements

No prior knowledge of artificial intelligence or AI ethics is required
No technical or programming experience is needed
An interest in using generative AI responsibly in everyday, academic, or professional contexts is helpful

Description

This course contains the use of artificial intelligence.

Generative AI is changing how we work, learn, create, communicate, and make decisions. But using these systems responsibly requires more than knowing how to write a good prompt.

This course provides a practical introduction to AI ethics and the responsible use of generative AI. You will learn how to recognize important risks, evaluate AI-generated content critically, and make better decisions about when and how these tools should be used.

The course explores bias and fairness, including how unequal patterns can appear in generated text, images, recommendations, translations, and automated assistance. You will examine AI hallucinations and reliability, learning why confident AI-generated answers are not necessarily accurate and how important claims should be verified.

You will also explore synthetic media, AI-generated images and audio, privacy and meaningful consent, intellectual property and attribution, and the responsible use of AI in education and the workplace.

Rather than treating AI ethics as a collection of abstract principles, the course focuses on practical situations and decisions. You will learn how to identify potential harms, consider who may be affected, determine when human oversight is necessary, and apply appropriate safeguards.

By the end of the course, you will be able to:

Recognize common ethical risks associated with generative AI.
Identify bias and potentially unfair AI-generated outputs.
Evaluate AI-generated claims and verify important information.
Understand the risks associated with hallucinations and synthetic media.
Consider privacy, consent, ownership, and attribution.
Apply human oversight according to the potential consequences of an AI-assisted decision.
Use a practical framework for more responsible AI use.

No technical background in artificial intelligence or machine learning is required. The course is designed for professionals, students, educators, managers, and anyone who uses generative AI tools and wants to use them more responsibly.

Who this course is for:

Professionals who use or plan to use generative AI tools in the workplace
Students and educators interested in the ethical and responsible use of generative AI
Managers and team leaders who need to understand AI risks, accountability, and human oversight
Content creators and other professionals using AI to assist with writing, images, research, or creative work
Anyone interested in understanding how to use generative AI safely, ethically, and responsibly

AI Ethics & Responsible Use of Generative AI

What you'll learn

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Course content

Introduction1 lecture • 6min

Understanding Generative AI and Its Limitations4 lectures • 28min

Understanding Bias, Fairness, and Unequal Impact4 lectures • 32min

Truth, Reliability, and Synthetic Media3 lectures • 24min

Conclusion1 lecture • 10min

Requirements

Description

Who this course is for: