Class 10 (AI)

Part [A] Ch 1: Communication Skills - II

Part [A] Ch 2: Self-Management Skills – II

Part [A] Ch 3: ICT Skills – II

Part [A] Ch 4. Entrepreneurial Skills – II

Part [A] Ch 5. Green Skills - II

Quick Guess (Pg. 92): Ecological balance

Quiz Time (Pg. 92): c.

Let’s Review (Pg. 93)

Write T for True and F for False.      1. T       2. F        3. T

Let’s Review (Pg. 98): Fill in the blanks.

1. Green skills 2. NREGA 3. social, economic, environmental   4. zero hunger Exercises (Pgs. 100–102)

A. Tick (✓) the correct answers.       1. c. 2. c. 3. Stopping setting up of industries 4. b. 5. b. 6. a. 7. c. 8. b. 9. b. 10. b.

B. Fill in the blanks. 1. greenhouse        2. e-waste         3. social          4. 17          5. ecological balance        6. Conservation        7. Goal 7        8. Sinkhole           9. Upcycle        10. Environmental citizenship

C. Write T for True and F for False.      1. F         2. F          3. T         4. T          5. F      6. T          7. F           8. F         9. T       10. T


Instructions: Refer page number 101 of text book.

D. Short answer type questions:

Ans 1. The primary aim of a green economy is to improve human well-being and social equity, while significantly reducing environmental risks and ecological scarcities.

Ans 2. Environmental sustainability, social sustainability, and economic sustainability are important for achieving true sustainable development.

Ans 3. Sustainable development is a way to achieve economic and social development without negatively impacting our natural resources. The availability of these natural resources is critical to continued development in the future.

Ans 4. Waste segregation is important because it makes it easier to follow the 4 Rs and 1 U of waste management and reduces the amount of waste that goes into landfills.

Ans 5. Upcycling means modifying an old, used material to create a new product. Using the lower half of a used plastic bottle as a flower vase is an example of upcycling.

Ans 6. This is the most important step as it requires a reduction in unnecessary consumption and thus generates less waste.

Ans 7. If we save water through rainwater harvesting there would be no need to pump groundwater. This measure would help conserve both water and energy.

Ans 8. Electronic waste, also known as e-waste, is any electronic product, or product containing electronic components, that has reached the end of its usable life cycle. Electronic items contain toxic substances, so they must be handled with care when no longer wanted or needed. However, it must be disposed by a certified e-waste hauler as it can cause harm to humans, animals, and the environment. If e-waste is not disposed properly in landfills or other non-dumping sites, it poses serious threats to public health and can pollute ecosystems for generations to come.

Ans 9. The relationship between society and the environment is interrelated. The behaviour of human beings has a huge impact on the environment, and the latter impacts people’s lives. If people take care of the environment, they are rewarded with fertile soil, clean air and water, plenty of food products, and good quality of life. If people exploit natural resources, the punishment can be in the form of polluted air and water, droughts, floods, and other major problems.

Ans 10. Biodiversity refers to a wide variety of life found on the Earth, including plants, animals, fungi, and microorganisms, along with the communities that they form and the habitats in which they live. Biodiversity is important because the interrelationships between different lifeforms supports important functions like supply of oxygen, clean air and water; pollination of plants; control of pests; wastewater treatment; etc.


E. Long answer type questions (Write only selected questions.)

Ans 1. Sustainable development can be defined as development that meets the needs of the present without compromising the ability of future generations to meet their needs. It is all about finding ways and means to balance different and often competing needs against environmental awareness, social, and economic constraints that we face as a society. The decisions that we take today as a society will have a far-reaching impact on the future generations. Given below are some important reasons on why we need to focus on sustainable development.

Ans 3. Individual efforts can go a long way in contributing towards advancing the sustainable development goals. Here are some measures that you can take:

Ans 5. It is important to focus on social sustainability to create more inclusive societies, empower the citizens, and foster creation of more resilient and peaceful communities. It helps expand opportunities for all people, and when coupled with economic and environmental sustainability, it is vital for poverty reduction and shared prosperity. It also helps in creating opportunities for people living in the most challenging environments. The aim is to build strong households and communities that can withstand conflict and climate change.

Ans 6. Human activities, such as deforestation, intensive agriculture, overgrazing by cattle, building of large dams, and disposal of industrial waste have degraded the quality of the land. This has resulted in serious issues like soil erosion, loss of habitat for animals, and health problems for human beings. It has also made the land unsuitable for agriculture. Ways to conserve land include afforestation, adoption of sustainable agricultural practices, and minimal disposal of harmful waste in landfills. Waste management is an important aspect of conservation because excessive waste created by human activities is responsible for much of the harm caused to the environment.

Ans 8. Green skills are defined as the technical skills, knowledge, values, and attitude needed in the workforce to develop and support sustainable social, economic, and environmental outcomes in business, industry, and the community.

This means that to make the changes required to move towards sustainable development, experts in different fields are needed, including teachers, engineers, economists, technical workers, policymakers, and many more. Young people like we can help the world move towards a green economy and encourage sustainable development through the inculcation of green skills. 


Part [B] Ch 1: Introduction to Artificial Intelligence

E. Short answer questions.

Ans 1. Artificial intelligence can be defined as the intelligence demonstrated by machines that mirrors the learning, problem-solving, and decision-making capabilities of the human mind. When an electronic machine can gather data; interpret, analyse and understand it; and apply it to make informed decisions, while retaining the information as a knowledge bank for the future, it is said to be artificially intelligent.

Ans 2. Intelligence is classified into nine modalities by Howard Gardener that are as follows:

Ans 3. The evolution of AI technology has been of great interest and importance since the 20th century. The earliest significant work in the field of artificial intelligence was done in the mid-20th century by an English mathematician and computer scientist, Alan Turing. In 1947, Turing gave a public lecture In London mentioning computer intelligence. The two central concepts of artificial intelligence that are used to build smart machines today — learning from experience and altering instructions by self— were introduced by him during this lecture. Subsequently, in 1956, John McCarthy and Marvin Minsky hosted the Dartmouth Summer Research Project on Artificial Intelligence summer workshop. It was in this historic conference that the term 'Artificial Intelligence' was coined.

Ans 4. Super AI is a futuristic notion that just does not mimic human intelligence but supersedes it. For super AI to become a reality, computing programs have to be far more superior to human intelligence in all parameters. Super AI system would boast of an intellect that is higher than the human beings in every field, including scientific creativity, general wisdom, and social skills which proves super AI to be a hypothetical concept.

Ans 5. Artificial Intelligence (Al), Machine Learning (ML), Deep Learning (DL), these words, though commonly used interchangeably, are not the same due to the following differences:

(a) Artificial Intelligence is an umbrella term encompassing various sub-fields, such as general intelligence, machine learning, expert systems, and robotics. It focuses on components of intelligence like learning, reasoning, problem-solving, and understanding language.

(b) Machine learning is a subset of artificial intelligence. It is concerned with the development of machines that can learn, adapt, and process information on their own without being provided with explicit instructions.

(c) Deep learning is a subset of machine learning, which is inspired by the human brain. It attempts to solve problems and draw conclusions like human beings.

Ans 6. Data science deals with the use of various algorithms, scientific methods, and processes to extract valuable insights from vast amounts of structured or unstructured data. It helps to uncover hidden patterns from raw data and extract clean information suitable for the formulation of actionable insights.

Ans 7. Virtual voice assistants, such as Amazon's Alexa and Apple's Siri, recognise the speech pattern of the users, understand the meaning of the perceived words, and provide the end-users with useful responses. They help conduct quick research and find answers in seconds, thus proving to make our daily life easy by simple access to technology.

Ans 8. Travel experience today has become much more convenient and enriching through the use of Al technology. Algorithms are being used to predict travel choices, provide personalised travel solutions tailored to meet customer needs, and improve customer service in the travel industry. Customer support is also an important component of the travel industry. Travelers require assistance both while planning trips (for booking hotels, and selecting preferred destinations) as well as during trips (for currency exchange or identifying modes of transport) at any time of the day or night. In such a scenario, Al-based chatbots serve as a convenient and reliable way to provide live support to travellers and also help to save time and resources.

Ans 9. Computer vision is a domain of artificial intelligence that enables computers to derive and extract meaningful information from visual input, such as images, videos, gifs, and so on. A common application of computer vision is facial detection and recognition system. This technology is used for various purposes, such as unlocking a device including mobile phones and tablets.

Ans 10. Two ethical issues related to the use of AI technology are as follows:

Liability: The ability of Al systems to accumulate experience, learn from it, and make independent decisions based on the learning makes them prone to mistakes like humans. Such mistakes can either be small and trivial or have grievous, far-reaching consequences.

Access: A notable side-effect of an increasingly Al-powered society is Its unequal availability Access to the benefits of Artificial Intelligence technology is guided largely by economics with the rich making the most of it, the rest being left behind. This widens the existing societal gap even further and makes the economic state of a nation worse at the same time giving the impression of a digitally advanced society.

Part [B] Ch 2: AI Project Cycle

AI Review (Pg. 132)

Five applications of artificial intelligence in our daily lives are as follows:

AI Review (Pg. 136)

The selected goal is SDG13 – Climate Action.

AI Review (Pg. 138)

A. In the Problem Scoping stage, the problems that may hinder the execution of an AI project are identified; whereas in the Data Acquisition stage, data is acquired for the AI project.

B. Training data set is the first data set used to build the algorithm. The AI model relies on this data to understand, evaluate, and finally come to a single decision, whereas the testing data set is used for the final assessment of a model. After the model is ready, testing data validates whether the model is making accurate predictions or not.

C. Validation data set, also known as secondary data set, is fed into the model when the model is getting trained. The use of this data set is to see how accurately a model can make predictions when it is fed with the new data, whereas testing data set is used for the final assessment of a model. It is the final data set and provides a real-world check to ensure that the AI model was trained effectively.

AI Review (Pg. 145)

An example of a rule-based system is the domain-specific expert system that uses some rules to make choices. For example, an expert system that help a doctor choose the right and appropriate diagnosis based on a cluster of symptoms. An example of a learning-based system is virtual personal assistants.

AI Review (Pgs. 146–147)

Fill in the blanks.

Exercises (Pgs. 152–154)

A. Tick (✓) the correct answers.

1. b. 2. c. 3. a. 4. c. 5. b. 6. b. 7. c. 8. a. 9. a. 10. c.

B. Fill in the blanks.

1. Problem Statement Template 2. SDGs 3. manual methods and automated tools 4. Testing data

5. Data visualization 6. Supervised learning, unsupervised learning 7. Regression, classification 8. Deep learning

9. F1 Score 10. Deployed

C. Write T for True and F for False.

1. T 2. F 3. T 4. T 5. F 6. F 7. T 8. T 9. T 10. F

D. Match the columns.

1. d. 2. e. 3. a. 4. b. 5. c.

E. Short answer type questions

EXTRA QUESTIONS BASED ON SHORT NOTES:

1) What is Problem Scoping?

Ans: Problem Scoping: This is the first stage of the Al project cycle. Problems arise while trying to execute an Al project, and therefore, the first step is to identify these problems and rectify them. This is done during the problem scoping stage. During this stage, problems that might hinder the execution of the Al project are identified, understood, and possible solutions are suggested.

2) What is Data Acquisition?

Ans: Data Acquisition: After understanding the nature of the problem and setting a goal for the project, the next step of the Al Project Cycle is to acquire data for the project. Data acquisition refers to the collection of data from the appropriate resources. Data can be collected from surveys, sensors, web scraping, research, observations, investigations, cameras, and Application Programming Interface (API).

3) What is Data Exploration?

Ans: Data Exploration: During data acquisition, a large amount of complex and unorganised data is gathered. This data must be explored, analysed, and arranged systematically for a better understanding. The data is trimmed to get rid of unessential parts, while the essential ones are retained. Data exploration is the first step of data analysis. Data is analysed visually in a format that the users understand.

4) What is Data Modelling?

Ans: Data Modelling: This stage aims to make an intelligent machine that can think, organise, and provide accurate results. The model must follow instructions, learn, understand, and take conscious decisions, almost like a human being. Al models are usually mathematical algorithms trained to replicate decisions that an expert in that field would have taken, given the same circumstance.

5) What is Evaluation?

Ans: Evaluation: Evaluation is a process wherein an Al model is evaluated. New data is fed to the model and prediction results are compared with the actual values. The model’s effectiveness is calculated based on the parameters—accuracy, precision, recall, and F1 score.

6) What is Supervised Learning?

Ans: Supervised Learning: In this method, the algorithm is provided with a well-labelled training data, that is, the input data is already matched with the output data before feeding it into the machine. The training data fed into the machine works as a supervisor that ensures the machine learns to predict the outcome correctly. Supervised learning is used to develop models related to image recognition, fraud detection, spam filtering, financial analysis, and so on.

7) What is Unsupervised Learning?

Ans: Unsupervised Learning: In this method, algorithms are trained on the unlabelled data set, that is, random data is fed to the machine during training. The machine then identifies the patterns and relationships in the random data. Here, only input labels are provided. Unsupervised learning algorithms are used when you are unsure about the data classification and want the algorithm to classify the data for you.

8) What is Machine Learning? What are its advantages?

Ans: Machine Learning is a learning-based approach that produces dynamic models. Unlike the rule based approach, the Al model makes predictions based on the data and without being fed with rules or instructions in machine learning. The advantages of machine learning are as follows:

a) Automation
b) Continuous scope for improvement
c) Trends and patterns identification
d) Huge range of applications