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Safe and Responsible Use?

AI is transforming education by enhancing learning through tools like chatbots, personalized platforms, and multimedia generators, moving beyond traditional classrooms. However, while these technologies offer convenience, they also present ethical risks such as copyright infringement, which this section addresses through real-world examples, checklists, and practical guidelines for responsible AI use.

Basic Concepts for Ethical AI Use?

Why is Ethical Use Important? Need for Self-Awareness and Habit Formation

Specific AI Tool Use Cases and Ethical Principles?

AI Generated Text AI Generated Multimedia Recommendation Algorithms

Using Checklists for Habitual Compliance

Quiz?

Check your understanding of applying AI Ethics

AI Safety and Regulation?

AI and Safety: What should We Know? Basic Principles of Data Protection and Privacy

Quiz

Human-Led AI Life cycle

Legal Accountability and Case Studies

Critical Analysis of AI Uses and Capabilities

Responsibilities for using and developing AI

Discussion about Human Responsibility and Human Rights

Will AI Replace Humans?

How AI and Automation Affects Our Minds

Practical Guide for Implementating AI Ethics for Everyone?

Project-Based Learning Continuous Monitoring and Feedback Role-Playing and Simulated Situations
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Activity – AI Incident Simulation Scenarios

AI Incident Simulation Scenarios

Practice makes perfect—especially when preparing for problems that can come up in real AI projects. Below are three simulation ideas to help you learn how to handle AI issues in a safe, hands-on way.

Managing Algorithmic Bias

Scenario: A credit-scoring AI unfairly gives lower scores to people from certain neighborhoods or racial groups.

 

What You’ll Do:

  1. Spot the Bias: Figure out why the AI is making unfair decisions.
  2. Fix the Problem: Use a “correction” algorithm or change the training data so the AI becomes fairer.
  3. Check the Results: Measure how well your changes worked and see if the AI still treats everyone equally.

 

Why This Matters:

  • Ensures everyone gets a fair chance.
  • Builds trust in technology by avoiding discrimination.

Responding to Data Breaches

Scenario: During an AI project, sensitive user information is accidentally shared online.


What You’ll Do:

  1. Sound the Alarm: Quickly tell the right people what happened.
  2. Isolate the Data: Stop more people from seeing or copying it.
  3. Remove the Leak: Securely delete or hide the leaked information, and figure out how the breach occurred.

 

Why This Matters:

  • Protects users’ private information.
  • Teaches you how to react calmly and responsibly during emergencies.

Identifying AI-Generated Fake Content

Scenario: You’re given a set of videos and images. Some are real, and some are altered by AI to look real (deepfakes).


What You’ll Do:

  1. Look for Clues: Check for odd facial movements, mismatched shadows, or strange audio.
  2. Use Detection Tools: Apply filters or AI programs that can spot signs of manipulation.
  3. Decide What’s Fake: Mark which files you think are deepfakes and explain why.

 

Why This Matters:

  • Helps you avoid being tricked by fake news or videos.
  • Builds critical thinking skills to spot misinformation.

Putting It All Together

By practicing these scenarios, you’ll learn how to handle real-life problems that can arise with AI. Whether it’s fixing unfair algorithms, stopping data leaks, or catching deepfakes, these exercises make you better prepared to use AI responsibly and safely.

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