CBSE Textbook: Introduction to Generative AI | Artificial Intelligence (AI) for Class 9 PDF Download

 Page 1


122 
 
Unit 4 - Generative Artificial Intelligence 
 
Lesson Title: Introduction to Generative AI 
Approach: Interactive Session + Activity 
Summary: 
The lesson covers four main topics, including an introduction to Generative AI, how it works, 
how to use it, and the ethical considerations that come with its use. By the end of the lesson, 
students will have a basic understanding of Generative AI, how it can be used, and the 
potential ethical implications to consider. 
Learning Objectives 
? To understand Generative AI and its types. 
? To know examples and benefits of using Generative AI. 
? To identify popular Generative AI tools and their applications. 
? To sensitize the students about the ethical considerations of using Generative AI. 
? To explain students about the potential negative impact of Generative AI on society. 
Learning Outcomes: 
? Students will be able to define Generative AI & classify different kinds. 
? Students will be able to explain how Generative AI works and recognize how it learns. 
? Students will be able to apply Generative AI tools to create content. 
? Students will understand the ethical considerations of using Generative AI. 
Pre-requisites: 
? Knowledge of AI project cycle. 
Key-concepts: 
? Generative AI 
Programs/Applications Used: 
? MS PowerPoint 
? MS Word 
? Web browser (any) 
Page 2


122 
 
Unit 4 - Generative Artificial Intelligence 
 
Lesson Title: Introduction to Generative AI 
Approach: Interactive Session + Activity 
Summary: 
The lesson covers four main topics, including an introduction to Generative AI, how it works, 
how to use it, and the ethical considerations that come with its use. By the end of the lesson, 
students will have a basic understanding of Generative AI, how it can be used, and the 
potential ethical implications to consider. 
Learning Objectives 
? To understand Generative AI and its types. 
? To know examples and benefits of using Generative AI. 
? To identify popular Generative AI tools and their applications. 
? To sensitize the students about the ethical considerations of using Generative AI. 
? To explain students about the potential negative impact of Generative AI on society. 
Learning Outcomes: 
? Students will be able to define Generative AI & classify different kinds. 
? Students will be able to explain how Generative AI works and recognize how it learns. 
? Students will be able to apply Generative AI tools to create content. 
? Students will understand the ethical considerations of using Generative AI. 
Pre-requisites: 
? Knowledge of AI project cycle. 
Key-concepts: 
? Generative AI 
Programs/Applications Used: 
? MS PowerPoint 
? MS Word 
? Web browser (any) 
123 
 
Purpose: 
To understand the difference between real and AI-Generated Images. 
Examine the images and determine whether either of the images is a real image or an 
AI-generated image. Also, give reasons for your answer. 
Activity: Guess the Real Image vs. the AI-Generated Image 
 
 
 
 
 
 
Let's look at the concepts behind the generation of these images. 
Page 3


122 
 
Unit 4 - Generative Artificial Intelligence 
 
Lesson Title: Introduction to Generative AI 
Approach: Interactive Session + Activity 
Summary: 
The lesson covers four main topics, including an introduction to Generative AI, how it works, 
how to use it, and the ethical considerations that come with its use. By the end of the lesson, 
students will have a basic understanding of Generative AI, how it can be used, and the 
potential ethical implications to consider. 
Learning Objectives 
? To understand Generative AI and its types. 
? To know examples and benefits of using Generative AI. 
? To identify popular Generative AI tools and their applications. 
? To sensitize the students about the ethical considerations of using Generative AI. 
? To explain students about the potential negative impact of Generative AI on society. 
Learning Outcomes: 
? Students will be able to define Generative AI & classify different kinds. 
? Students will be able to explain how Generative AI works and recognize how it learns. 
? Students will be able to apply Generative AI tools to create content. 
? Students will understand the ethical considerations of using Generative AI. 
Pre-requisites: 
? Knowledge of AI project cycle. 
Key-concepts: 
? Generative AI 
Programs/Applications Used: 
? MS PowerPoint 
? MS Word 
? Web browser (any) 
123 
 
Purpose: 
To understand the difference between real and AI-Generated Images. 
Examine the images and determine whether either of the images is a real image or an 
AI-generated image. Also, give reasons for your answer. 
Activity: Guess the Real Image vs. the AI-Generated Image 
 
 
 
 
 
 
Let's look at the concepts behind the generation of these images. 
124 
 
Supervised Learning and Discriminative Modeling 
 
Image Source: Generative AI, Explained by Humans. (n.d.). https://lingarogroup.com/blog/generative-ai-explained-by-humans 
 
The classification of data elements into categories or labels was initially taught to the machine learning 
models by humans. 
 
Unsupervised Learning and Generative Modeling 
 
Image Source: Generative AI, Explained by Humans. (n.d.). https://lingarogroup.com/blog/generative-ai-explained-by-humans 
 
In unsupervised or self-supervised learning, the machine learning model takes unlabeled datasets and 
figures out patterns and inherent structures within them — without human intervention. 
 
What is Generative AI? 
? Generative artificial intelligence (AI) refers to the algorithms that generate new data that 
resembles human-generated content, such as audio, code, images, text, simulations, and videos. 
? This technology is trained with existing data and content, creating the potential for applications 
such as natural language processing, computer vision, the metaverse, and speech synthesis. 
Page 4


122 
 
Unit 4 - Generative Artificial Intelligence 
 
Lesson Title: Introduction to Generative AI 
Approach: Interactive Session + Activity 
Summary: 
The lesson covers four main topics, including an introduction to Generative AI, how it works, 
how to use it, and the ethical considerations that come with its use. By the end of the lesson, 
students will have a basic understanding of Generative AI, how it can be used, and the 
potential ethical implications to consider. 
Learning Objectives 
? To understand Generative AI and its types. 
? To know examples and benefits of using Generative AI. 
? To identify popular Generative AI tools and their applications. 
? To sensitize the students about the ethical considerations of using Generative AI. 
? To explain students about the potential negative impact of Generative AI on society. 
Learning Outcomes: 
? Students will be able to define Generative AI & classify different kinds. 
? Students will be able to explain how Generative AI works and recognize how it learns. 
? Students will be able to apply Generative AI tools to create content. 
? Students will understand the ethical considerations of using Generative AI. 
Pre-requisites: 
? Knowledge of AI project cycle. 
Key-concepts: 
? Generative AI 
Programs/Applications Used: 
? MS PowerPoint 
? MS Word 
? Web browser (any) 
123 
 
Purpose: 
To understand the difference between real and AI-Generated Images. 
Examine the images and determine whether either of the images is a real image or an 
AI-generated image. Also, give reasons for your answer. 
Activity: Guess the Real Image vs. the AI-Generated Image 
 
 
 
 
 
 
Let's look at the concepts behind the generation of these images. 
124 
 
Supervised Learning and Discriminative Modeling 
 
Image Source: Generative AI, Explained by Humans. (n.d.). https://lingarogroup.com/blog/generative-ai-explained-by-humans 
 
The classification of data elements into categories or labels was initially taught to the machine learning 
models by humans. 
 
Unsupervised Learning and Generative Modeling 
 
Image Source: Generative AI, Explained by Humans. (n.d.). https://lingarogroup.com/blog/generative-ai-explained-by-humans 
 
In unsupervised or self-supervised learning, the machine learning model takes unlabeled datasets and 
figures out patterns and inherent structures within them — without human intervention. 
 
What is Generative AI? 
? Generative artificial intelligence (AI) refers to the algorithms that generate new data that 
resembles human-generated content, such as audio, code, images, text, simulations, and videos. 
? This technology is trained with existing data and content, creating the potential for applications 
such as natural language processing, computer vision, the metaverse, and speech synthesis. 
125 
 
Activity 
Watch the video: https://www.youtube.com/watch?v=26fJ_ADteHo and Share your views 
Let us have a look at timeline of Generative AI 
Source: https://www.desdevpro.com/blog/talk-rise-of-generative-ai 
 
Generative AI has evolved over several years to reach its current form. Over time, advancements in 
neural networks and deep learning techniques have significantly enhanced its capabilities. From early 
experiments in generative models to breakthroughs in natural language processing and image 
generation, the development of generative AI has been a continuous journey of innovation and 
refinement. Today, generative AI encompasses a wide range of applications, including text generation, 
image synthesis, and creative content creation, showcasing the culmination of years of research and 
development efforts. 
 
What do you understand about generative AI? 
 
 
Give a few examples of generative AI. 
 
 
What do you know about Deep Fake? 
 
 
Generative AI vs Conventional AI 
In contrast to other forms of AI, Generative AI is specially made to produce new and unique content 
rather than merely processing or categorizing already-existing data. Here are some significant variations: 
Page 5


122 
 
Unit 4 - Generative Artificial Intelligence 
 
Lesson Title: Introduction to Generative AI 
Approach: Interactive Session + Activity 
Summary: 
The lesson covers four main topics, including an introduction to Generative AI, how it works, 
how to use it, and the ethical considerations that come with its use. By the end of the lesson, 
students will have a basic understanding of Generative AI, how it can be used, and the 
potential ethical implications to consider. 
Learning Objectives 
? To understand Generative AI and its types. 
? To know examples and benefits of using Generative AI. 
? To identify popular Generative AI tools and their applications. 
? To sensitize the students about the ethical considerations of using Generative AI. 
? To explain students about the potential negative impact of Generative AI on society. 
Learning Outcomes: 
? Students will be able to define Generative AI & classify different kinds. 
? Students will be able to explain how Generative AI works and recognize how it learns. 
? Students will be able to apply Generative AI tools to create content. 
? Students will understand the ethical considerations of using Generative AI. 
Pre-requisites: 
? Knowledge of AI project cycle. 
Key-concepts: 
? Generative AI 
Programs/Applications Used: 
? MS PowerPoint 
? MS Word 
? Web browser (any) 
123 
 
Purpose: 
To understand the difference between real and AI-Generated Images. 
Examine the images and determine whether either of the images is a real image or an 
AI-generated image. Also, give reasons for your answer. 
Activity: Guess the Real Image vs. the AI-Generated Image 
 
 
 
 
 
 
Let's look at the concepts behind the generation of these images. 
124 
 
Supervised Learning and Discriminative Modeling 
 
Image Source: Generative AI, Explained by Humans. (n.d.). https://lingarogroup.com/blog/generative-ai-explained-by-humans 
 
The classification of data elements into categories or labels was initially taught to the machine learning 
models by humans. 
 
Unsupervised Learning and Generative Modeling 
 
Image Source: Generative AI, Explained by Humans. (n.d.). https://lingarogroup.com/blog/generative-ai-explained-by-humans 
 
In unsupervised or self-supervised learning, the machine learning model takes unlabeled datasets and 
figures out patterns and inherent structures within them — without human intervention. 
 
What is Generative AI? 
? Generative artificial intelligence (AI) refers to the algorithms that generate new data that 
resembles human-generated content, such as audio, code, images, text, simulations, and videos. 
? This technology is trained with existing data and content, creating the potential for applications 
such as natural language processing, computer vision, the metaverse, and speech synthesis. 
125 
 
Activity 
Watch the video: https://www.youtube.com/watch?v=26fJ_ADteHo and Share your views 
Let us have a look at timeline of Generative AI 
Source: https://www.desdevpro.com/blog/talk-rise-of-generative-ai 
 
Generative AI has evolved over several years to reach its current form. Over time, advancements in 
neural networks and deep learning techniques have significantly enhanced its capabilities. From early 
experiments in generative models to breakthroughs in natural language processing and image 
generation, the development of generative AI has been a continuous journey of innovation and 
refinement. Today, generative AI encompasses a wide range of applications, including text generation, 
image synthesis, and creative content creation, showcasing the culmination of years of research and 
development efforts. 
 
What do you understand about generative AI? 
 
 
Give a few examples of generative AI. 
 
 
What do you know about Deep Fake? 
 
 
Generative AI vs Conventional AI 
In contrast to other forms of AI, Generative AI is specially made to produce new and unique content 
rather than merely processing or categorizing already-existing data. Here are some significant variations: 
126 
 
 
           
 
 
Types of Generative AI 
Generative AI comes in a variety of forms, each with unique advantages and uses. Some of the most 
typical varieties are listed below: 
 
 
 
 
Goal 
  
Generative AI creates new content, whereas 
conventional AI analyzes, processes, and 
classifies data. 
 
Training 
  
Generative AI models use vast libraries of samples 
to train neural networks and other complicated 
structures to produce new content based on those 
patterns. Conventional AI employs fewer complex 
algorithms and training methods. 
  
 
Output 
  
Generative AI output is fresh, innovative, and 
often unexpected. 
Conventional AI produces more predictable 
output based on existing data. 
 
Applications 
  
Generative AI benefits art, music, literature, 
gaming, and design.  
Conventional AI is used in banking, healthcare, 
image recognition, and language processing.