Lesson List Browse Q&A

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
Go to Course Home
Critical Analysis of AI Capabilities

Critical Analysis of AI Capabilities

1. Compare Hype with Actual Performance

  • What You May See:
    Advertisements and videos sometimes show AI as super smart and able to do everything perfectly.

 

  • Activity:

    • Find an Ad: Look for an AI commercial or article that promises near-flawless results.
    • Find a Real Example: Then, check out something like a chatbot that gives funny or incorrect answers. For instance, some language translation apps make silly mistakes when they don’t understand local slang.

 

  • Why It’s Important:
    You will see the difference between grand promises and reality. This helps you spot where AI isn’t as perfect as it seems.

 

Resource Limits of AI Models

  • Computers Need Power
    For example, big AI models like those used in advanced image searches need large data centers that consume a lot of electricity.

 

  • Data Can Be Biased
    Some facial recognition tools have trouble detecting people with darker skin tones because the data they were trained on lacked diversity.

 

  • Updates Cost Time and Money
    Self-driving car software gets frequent updates to fix bugs and learn new situations (like unusual traffic rules). These updates can be expensive.

2. Don’t Let AI Make All the Decisions

  • Human Choices Are Key
    AI is a tool that can help with suggestions. But you, your teachers, or your parents still need to make the final call. 
    • Example: A school might use an AI scheduling tool to plan exam times. However, teachers should still review and approve the final schedule, in case the AI overlooks events that were not in the system.

Tolerance for Error

  • AI Can Be Wrong
    Just like people, AI can make mistakes.

    • Example: Some digital assistants have accidentally sent private messages to the wrong person because they misunderstood the speaker’s voice commands.

 

  • Checks and Balances
    We need ways to catch errors. This might mean testing AI predictions or having a backup plan if AI fails.

    • Example: A weather prediction AI can help forecast storms, but meteorologists and local authorities always verify the information before issuing real warnings.
← Previous Next →
Skip to toolbar