Practice Ethical Considerations of Using Generative AI - 17 | 17. Ethical Considerations of Using Generative AI | CBSE Class 9 AI (Artificial Intelligence)
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is generative AI?

💡 Hint: Think about content creation.

Question 2

Easy

What does 'bias' mean in the context of AI?

💡 Hint: Consider examples from job hiring.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the main ethical concern regarding misinformation from generative AI?

  • It can create realistic but misleading content.
  • It increases job opportunities.
  • It guarantees information accuracy.

💡 Hint: Remember examples of fake news.

Question 2

True or False: Generative AI can reduce job opportunities for creative workers.

  • True
  • False

💡 Hint: Consider the role of automation in various industries.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You're a tech company proposing a new generative AI tool. Assess the potential ethical concerns and outline a plan to address them.

💡 Hint: Consider both legal and moral implications in your plan.

Question 2

Discuss the impact of generative AI on journalism. What are the ethical considerations that come into play, and how should journalists adapt?

💡 Hint: Think about the traditional values of journalism versus AI capabilities.

Challenge and get performance evaluation