Introduction to Capstone Project Class 11 Questions and Answers

These Class 11 AI Important Questions Chapter 4 Python Programming Class 11 Important Questions and Answers NCERT Solutions Pdf help in building a strong foundation in artificial intelligence.

Python Programming Class 11 Important Questions

Class 11 Python Programming Important Questions

Important Questions of Python Programming Class 11 – Class 11 Python Programming Important Questions

Python Programming Class 11 Very Short Answer Type Questions

Question 1.
What are the issues and concerns around AI?
Answer:
Artificial intelligence research has led to a number of issues, including job loss, trust issues, safety concerns, and computation issues, among others.

Question 2.
What are the sources of AI bias?
Answer:
There are three sources of AI bias are: Data, Societal Bias and Algorithm.

Question 3.
What is Algorithm bias?
Answer:
Algorithmic bias is the term used to characterise systematic and recurrent mistakes made by computer programmes that lead to “unfair” outcomes, such as “privileging” one category over another in ways that go against the algorithm’s original purpose.

Question 4.
What is AI bias?
Answer:
Machine learning bias, sometimes called algorithm bias or AI bias, is a phenomena that arises when an algorithm produces results that are consistently biassed due to erroneous assumptions established during the machine learning (ML) process.

Question 5.
Give two examples of driverless car-related ethical concerns.
Answer:
Concerns concerning the morality of programming autonomous vehicles to make decisions in potentially hazardous circumstances are also raised. For instance, if a collision is unavoidable, should the vehicle choose to safeguard its occupants or limit property damage?

Question 6.
What skills are developed through an AI capstone project?
Answer:
Teamwork, problem identification, solution brainstorming, AI application selection, ethical data usage, prototype testing, and pitching solutions.

Python Programming Class 11 Short Answer Type Questions

Question 1.
Which occupations are at risk from AI?
Answer:

• Bank clerk
• Retail
• Manufacturing
• Translation using NLP
• Customer care/Telemarketing executive
• Driver
• Food preparation service
• Construction

Question 2.
How can bias in AI be reduced or eliminated?
Answer:
Following are some of the ways through which we can reduce AI bias:

• Create procedures for detecting and reducing bias in AI systems.
• Have fact-based discussions regarding possible biases in human judgement.
• Use an interdisciplinary strategy.
• Invest more in studies on AI bias.

Question 3.
Due to the massive number of patients during the Covid epidemic, robots were used to assist with patient care. Talk about the two benefits of this method.
Answer:

• The frontline staff members were protected by the robots acting as a barrier between the patient and the infection.
• During such an unprecedented time, robots were able to serve at maximum capacity (without rest)

Question 4.
What do you mean by a capstone project.
Answer:
The final project of an academic program, typically integrating all of the learning from the program is called the Capstone Project. A capstone project is a project where students must research a topic, deeply understand the subject matter and integrate all their knowledge to develop a solution to a problem.

Question 5.
Name some the skills which students will acquire by doing capstone project
Answer:
While doing a Capstone project, students will learn many important skills including:

• How to work as a team member
• How to clearly identify an issue and who it is affecting (the user)
• How to brainstorm solutions and select the best one
• How to decide which type of AI may be useful for the proposed solution
• How to ethically gather and use data to train a computer to help solve the issue
• How to test the prototype with users and use their feedback to improve the solution
• How to pitch their solution to people who will be able to help them take action

Question 6.
Give some examples of use case of SDG’s
Answer:
Some use cases of the SDGs are given below

• Renewable energy
• Reporting and communicating
• Combating hunger and poverty
• Protecting resources
• Promoting responsible consumption
• Providing access to education

Question 7.
Students are promoted to develop critical and creative thinking. Why?
Answer:
In order for students to effectively communicate and collaborate, they need to be taught how to think critically and creatively. They could pose important queries in response to issues, compile and evaluate pertinent data, generate concepts, and develop well-thought-out findings and solutions. The ability to think critically and creatively is essential for preparing people to be leaders, innovators, and social change agents.

Question 8.
Define Design Thinking
Answer:
One design methodology that offers a solution-based approach to problem solving is called design thinking. It’s quite helpful for solving complicated, unclear, or ill-defined problems.

Python Programming Class 11 Long Answer Type Questions

Question 1.
What are the issues raise due to AI and explain briefly?
Answer:
With development of artificial intelligence, some problems are arise like Trust related problem, Cyber security, Job loss problem and Computing power:
Trust related problem-As algorithms for artificial intelligence grow more potent, concerns, over whether they can make decisions that are fair and beneficial to humanity also surface.

Cyber Security-A technology’s potential for evil as well as good uses increases as its power increases. Hackers will always try to exploit any holes in the system, whether it be on a private network, cloud server, or social media platform.

Job loss problem-Today, there are a lot of expectations for AI. According to the media, cognitive capabilities of artificial intelligence would displace human workers from their occupations. Therefore, the IT sector must accurately communicate that AI is only a tool that can only be used in conjunction with humans.

Computing Power- Unstructured data is often used in AI. Enterprises find significant value in unstructured data, but many organizations are unable to provide useful information because they lack access to established techniques of analysis. Unstructured data is challenging to process and analyze since it cannot be stored in a relational database management system (RDBMS).

Question 2.
What AI and Bias and explain briefly?
Answer:
Artificial intelligence prejudice is a problem that happens when algorithm results are consistently biased towards a particular gender, language, race, wealth, etc. AI bias produces distorted results. Because algorithms are developed by people with conscious or unconscious preferences, they may have inherent biases that aren’t revealed until the algorithm is deployed in a public setting. There are three mainly sources of AI bias that are: Data, Societal Bias, Algorithm.

Data-Because AI systems are only as good as the data we feed them, biased AI results from the ingestion of biased data. AI systems reflect a wider base and are unable to distinguish between correct and incorrect training data.

Algorithm-Technology is meant to be objective. Unfortunately, this is untrue; parenting and society have a shaping effect on people and cause them to internalize certain preconceptions about the world. AI is identical. These individuals built the algorithms that make up the system, and the system tends to “think” in the manner that was taught to it.

Societal Bias-When an AI behaves in a way that reflects institutional discrimination or social intolerance, this is known as societal AI bias. Although the algorithms and data initially appear to be objective, their conclusions confirm societal biases.

Question 3.
Write down the steps of Problem decomposition
Answer:
Problem decomposition steps
1. Understand the problem and then restate the problem in your own words

Know what the desired inputs and outputs are
Ask questions for clarification (in class these questions might be to your instructor, but most of the time they will be asking either yourself or your collaborators)

2. Break the problem down into a few large pieces.
Write these down, either on paper or as comments in a file.

3. Break complicated pieces down into smaller pieces.

Keep breaking down until all of the pieces are small.

4. Code one small piece at a time.

• Think about how to implement it and write the code/query
• Test it on its own and Fix problems, if any

Question 4.
Explain briefly the different stages of Design thinking
Answer:
There are five stages of Design Thinking. They are: Empathize, Define, Ideate, Prototype, and Test.

i) Empathize: Design thinking begins with empathy. It allows designers to understand, empathize and share the feelings of the users. As a designer of the solution to a challenge, one should always understand the problem from the end-user perspective. This is done by observation, interaction or by imagination. Designers interact with customers / users very frequently to gather detailed facts about the problems and user’s expectations. A detailed analysis of these facts leads to approaching the problem in the best possible way.

ii) Define In the Define stage, information collected during Empathize is used to draw insights and is instrumental in stating the problem that needs to be solved. It’s an opportunity for the design thinker to define the challenge or to write the problem statement in a human cantered manner with a focus on the unmet needs of the users. 5 W 1 H method of asking questions can be implemented here.

iii) Ideate Ideation is the process of generating ideas and solutions through sessions such as sketching, brainstorming etc. At this stage, numerous ideas are generated as a part of the problem-solving exercise. In short, ideation is all about idea generation. Brainstorm, Brain write and Brain dump can be used for ideate stage.

iv) Prototype The prototype stage involves creating a model designed to solve consumers’ problems which is tested in the next stage of the process. Creating a prototype may include a developing simple drawing, poster, group role-playing, homemade “gadget, or a 3 d printed product.” The prototypes must be quick and easy to develop and cheap. Therefore, prototypes are visualized as rudimentary forms of what a final product is expected to look like.

v) Test During testing, the designers receive feedback about the prototype (s), and get another opportunity to interact and empathize with the people they are finding solutions for. Testing focuses on what can be learned about the user and the problem, as well as the potential solution.

Question 5.
Explain the different types of Ideation techniques.
Different ideation techniques are brainstorm, brain dump and brain writing
Answer:
Brainstorm
During a Brainstorming session, students leverage the synergy of the group to generate new innovative ideas by building on others’ ideas. Participants should be able to discuss their ideas freely without fear of criticism. A large number of ideas are collected so that different options are available for solving the challenge.

Brain dump

Brain dump is very similar to Brainstorm; however, it’s done individually. It allows the concerned person to open the mind and let the thoughts be released and captured onto a piece of paper. The participants write down their ideas onto paper or post-it notes and share their ideas later with the larger group.

Brain writing

Brain writing is also very similar to a Brainstorm session and is known as individual brainstorming’. At times only the most confident of team members share their ideas while the introverts keep the ideas to themselves. Brainwriting gives introverted people time to write them down instead of sharing their thoughts out loud with the group.

The participants write down their ideas on paper and, after a few minutes, pass on their own piece of paper to another participant who then elaborates on the first person’s ideas and so forth. In this way all participants pass their papers on to someone else and the process continues. After about 15 minutes, the papers are collected and posted for instant discussion.

Case-Based Questions:

Question 1.
Sita and Mina were discussing about trusting AI machines. According to Sita machines should not be trusted because they may give erroneous output but Mina however is not agreeing with her statement help a way out.
Answer:

• AI systems is so complicated that a user does not how it works. Thus trusting its decision is at stake. So its challenge can be addressed by the following ways.
• Using minimum bias data while training the machine.
• Sharing the algorithm with public or government before putting it into actual application.
• The AI developers should be from diverse backgrounds – gender, religion, skin colour, language and so on.
• On International monitoring body should be there, for monitoring and designing the and AI ethics and algorithm policy.

Question 2.
Mona said ‘Ethics and bias are not the problem of the machine rather it is the humans behind the machine’. Do you agree with her?
Answer:
Absolutely, considering that students involved in the AI system’s development-engineers, scientists, developers, etc.-strive to obtain the best accurate findings possible given the data at hand. without considering the bigger picture. Therefore, rather than blaming the machine, we must attribute the problem to the people who built it.

Question 3.
Rita is confused how these advanced machines are so problematic that it is showing biased results. Help her in understanding the sources of AI biasness.
Answer:
The reason there could be many causes for AI bias, but some of them are pointed below:

• Data-AI system does not have the understanding of whether their training data is correct or incorrect. It also have enough representation from a broader base or not.
• Algorithm-Although algorithm does not incur bias but it can amplify the causes behind the bias data.
• People-AI designers may less focus on the broader context of the usages of the machine.

Question 4.
As you near the completion of your Artificial Intelligence program, you are eager to put your newfound skills to good use. You have always been fascinated by the potential of AI to improve healthcare. Recently, you have learned about the challenges of early detection for certain diseases, leading to poorer prognoses. What do you call the project in which you must research a topic, deeply understand the subject matter, and integrate all their knowledge gathered about a particular subject to develop a solution to a problem?
Answer:
Capstone Project

Question 5.
You live in Darjeeling, a beautiful hill station. Due to heavy rains, landslides have damaged the roads, leaving the town temporarily isolated. Your school is closed, and online learning is the only option available. How do you feel about not being able to attend school in person and facing challenges with remote learning? Draw an empathy map to illustrate your thoughts, feelings, and experiences during this unexpected situation.
Answer:

Question 6.
Mr. Muthu Kumar is facing a serious issue of high electricity bill every month. He is trying a lot to reduce it. Considering his issue is worth solving, draw an empathy map related to Muthu Kumar.
Answer:

Question 7.
A small island nation in the Pacific Ocean, known for its beautiful beaches and colorful coral reefs, is in trouble. The sea level is rising, which is causing the shores to erode and making the land salty where plants used to grow. Most of the buildings and roads are near the coast, so they are at risk from the rising sea and strong storms. Because of these problems, it is harder for people to grow food like they used to, and they might not have enough to eat. Which Sustainable Development Goals (SDGs) can you align the above scenario with?
Answer:

• Zero Hunger (SDG 2)
• Sustainable Cities and Communities (SDG 11)
• Climate Action (SDG 13).

Scenario Base Question Answer:

Scenario: Sarah and James are computer science students preparing for their capstone project in artificial intelligence. They are keen on selecting a project that aligns with their interests and showcases their skills effectively. They have read about different stages and methodologies involved in capstone projects and want to ensure they understand the process thoroughly before proceeding.

Question 1.
What are the key skills Sarah and James will develop through their AI capstone project?
Answer:
Sarah and James will develop several important skills through their AI capstone project:

• Teamwork: They will learn how to collaborate effectively with peers to achieve project goals.
• Problem Identification: They will gain the ability to clearly identify and define complex issues that their AI solution aims to address.
• Solution Brainstorming: They will practice generating multiple solutions and selecting the most feasible one for implementation.
• AI Application: They will understand how to assess which AI techniques are suitable for solving specific problems, such as classification, regression, or clustering.
• Ethical Data Usage: They will learn the ethical considerations involved in gathering and utilizing data to train AI models.
• Prototype Testing: They will develop skills in creating prototypes and testing them with users to gather feedback for iterative improvements.
• Pitching Solutions: They will hone their ability to communicate their AI solution effectively to stakeholders who can support its implementation.

Python Programming Class 11 Notes

Capstone Project:

• A research-based project where students deeply explore a topic, integrate their knowledge, and propose a solution to a real-world problem.
• Opportunity to showcase expertise in Al skills as a final step in learning.

Skills Learned in Capstone Projects:

• Teamwork, problem identification, brainstorming solutions, AI applicability assessment, ethical data usage, prototype testing, and pitching solutions.

Examples of Capstone Projects:

• Stock Prices Predictor, Sentiment Analyzer, Movie Ticket Price Predictor, Students Results Predictor, Human Activity Recognition, and more.

Asking the Right Questions:

Before starting an AI Capstone Project, it’s crucial to determine if the problem exhibits identifiable patterns suitable for AI solutions.

AI Techniques for Problem Solving:

Classification, Regression, Clustering, Anomaly Detection, Recommendation systems are used based on the nature of the problem.

Problem Decomposition:

Breaking down complex problems into manageable parts to analyze and solve effectively.

Critical and Creative Thinking:

• Critical thinking involves analyzing situations based on facts and data.
• Creative thinking involves generating new ideas and solutions.

Design Thinking:

Non-linear, iterative process to understand users, redefine problems, and create innovative solutions through stages like Empathize, Define, Ideate, Prototype, and Test.

Empathy Map:
Tool to understand users’ needs, thoughts, actions, and feelings regarding a problem.

SDGs and Capstone Projects:
Aligning project goals with Sustainable Development Goals (SDGs) to address global challenges sustainably.

Empathy Map-An extremely useful tool for understanding the users’ needs and gaining a deeper insight into the problem at hand is the empathy map. It also helps in deepening that understanding, gaining insight into the user’s behavior.

Ideate -By now the problem is obvious and it is time to brainstorm ways and methods to solve it. At this stage, numerous ideas are generated as a part of the problem-solving exercise. In short, ideation is all about idea generation.

Brainstorm -During a Brainstorming session, students leverage the synergy of the group to generate new innovative ideas by building on others’ ideas. Participants should be able to discuss their ideas freely without fear of criticism. A large number of ideas are collected so that different options are available for solving the challenge.

Brain dump -Brain dump is very similar to Brainstorm; however, it’s done individually. It allows the concerned person to open the mind and let the thoughts be released and captured onto a piece of paper. The participants write down their ideas onto paper or post-it notes and share their ideas later with the larger group.

Brain writing- Brain writing is also very similar to a Brainstorm session and is known as ‘individual brainstorming’. At times only the most confident of team members share their ideas while the introverts keep the ideas to themselves. Brainwriting gives introverted people time to write them down instead of sharing their thoughts out loud with the group.

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