Textbook Solutions: AI Project Cycle & Ethical Frameworks | Artificial Intelligence for Class 10 PDF Download

Test Yourself

​Q1: What is the purpose of defining the problem statement during the Problem Scoping stage in an AI project cycle?
A) To collect data
B) To understand the aim and objective of the project
C) To train the model
D) To process data
Ans: B) To understand the aim and objective of the project

Explanation: Defining the problem clarifies the goal, scope, success criteria and constraints before data collection or model development begins, ensuring the project addresses the right question.

Q2: In what ways can AI models be categorized based on the type of data fed into them?
A) Two domains
B) Four domains
C) Three domains
D) Five domains
Ans: C) Three domains

Explanation: Common categorization divides AI tasks into three data domains: Textual (NLP), Visual (Computer Vision), and Statistical/Numeric data (data analytics).

Q3: In Statistical Data, what is the primary function of the system in relation to data?
A) Generating large datasets
B) Analyzing data to extract insights
C) Converting data into images
D) Distributing data across networks
Ans: B) Analyzing data to extract insights

Explanation: Statistical systems process numeric/tabular data to find patterns, correlations, trends and produce actionable insights for decision-making.

Q4: What is the main goal of Computer Vision projects?
A) Translating audio data into visual descriptions
B) Converting digital data into analogue signals
C) Teaching machines to understand textual information
D) Converting digital visual data into computer-readable language
Ans: D) Converting digital visual data into computer-readable language

Explanation: Computer Vision aims to make images and videos interpretable by machines (e.g., detecting objects, extracting features, classifying scenes).

Q5: What is the primary focus of NLP?
A) Analyzing computer languages
B) Interacting between computers and humans using artificial language
C) Dealing with the interaction between computers and humans using natural language
D) Enhancing human-to-human communication
Ans: C) Dealing with the interaction between computers and humans using natural language

Explanation: NLP enables computers to understand, interpret, generate and respond in human (natural) languages for tasks like translation, summarization, and conversation.

Q6: What do frameworks provide in the context of problem-solving?
A) Random solutions
B) Step-by-step guidance
C) Legal advice
D) Ethical justifications
Ans: B) Step-by-step guidance

Explanation: Frameworks supply structured approaches and systematic steps to analyze and solve problems consistently and efficiently.

Q7: How are Ethical Frameworks for AI categorized?
A) Into legal and illegal frameworks
B) Into sector-based and value-based frameworks
C) Into historical and contemporary frameworks
D) Into theoretical and practical frameworks
Ans: B) Into sector-based and value-based frameworks

Explanation: Ethical frameworks are often grouped by sector (industry-specific guidelines) or by values/principles (e.g., rights-based, virtue-based, utilitarian).

Q8: What is the central focus of virtue-based value-based frameworks?
A) Maximizing utility
B) Protecting human rights
C) Aligning actions with ethical principles and beliefs
D) Ensuring compliance with legal regulations
Ans: C) Aligning actions with ethical principles and beliefs

Explanation: Virtue-based frameworks emphasize the moral character and virtues of decision-makers and alignment of actions with ethical beliefs.

Q9: Which of the following best describes rights-based value-based frameworks?
A) Prioritizing human rights and dignity, valuing human life over other considerations
B) Evaluating actions based on maximizing overall good and minimizing harm
C) Centering on the character of the decision-maker and the alignment of actions with personal or societal virtues
D) Focusing on achieving outcomes that offer the greatest benefit
Ans: A) Prioritizing human rights and dignity, valuing human life over other considerations

Explanation: Rights-based frameworks place primary importance on protecting individual rights and dignity when evaluating actions.

Q10: What is the primary domain of application for Bioethics?
A) Agriculture
B) Healthcare and life sciences
C) Information technology
D) Environmental conservation
Ans: B) Healthcare and life sciences

Explanation: Bioethics addresses moral issues arising in medicine, biology and life sciences, such as clinical ethics, research ethics and biotechnology.

Q11: Assertion: Ethics provide guidance in distinguishing right from wrong.
Reasoning: Ethics consist of a set of values and morals that aid individuals in making moral judgments and decisions.
A) Both Assertion and Reasoning are true, and Reasoning is the correct explanation of the Assertion.
B) Assertion is true, but Reasoning is false.
C) Both Assertion and Reasoning are true, but Reasoning is not the correct explanation of the Assertion.
D) Assertion is false, but Reasoning is true.
Ans: A) Both Assertion and Reasoning are true, and Reasoning is the correct explanation of the Assertion.

Explanation: Ethics are composed of values and moral principles that guide people in judging actions as right or wrong; the reasoning explains why ethics provide that guidance.

Q12: Assertion: Value-based frameworks in ethics provide guidance by focusing on fundamental ethical principles and values.
Reasoning: These frameworks reflect different moral philosophies guiding ethical reasoning and are concerned with assessing the moral worth of actions.
A) Both Assertion and Reasoning are true, and Reasoning is the correct explanation of the Assertion.
B) Assertion is true, but Reasoning is false.
C) Both Assertion and Reasoning are true, but Reasoning is not the correct explanation of the Assertion.
D) Assertion is false, but Reasoning is true.
Ans: A) Both Assertion and Reasoning are true, and Reasoning is the correct explanation of the Assertion.

Explanation: Value-based frameworks draw on moral philosophies (e.g., utilitarianism, rights-based, virtue ethics) to evaluate and guide ethical decisions; the reasoning supports the assertion.

Reflection Time

Q1: Outline the main steps in the AI Project Cycle briefly.
Ans: The AI Project Cycle is a sequence of stages followed to design, build, and implement an AI solution. The main steps are:

• Problem Scoping – Understanding and defining the objective of the project. This step involves identifying the problem, setting clear goals, and specifying success criteria.
• Data Acquisition – Collecting relevant data required to solve the problem. Data can be obtained from databases, sensors, surveys, or other sources.
• Data Exploration – Cleaning, preprocessing, and analyzing the collected data to understand patterns, trends, and relationships. Visualization tools are often used here.
• Model Building – Designing and training machine learning or AI models using the processed data. Different algorithms are tested to build the best-performing model.
• Evaluation – Testing the model to measure its performance against defined success criteria. Metrics like accuracy, precision, recall, or F1-score are used.
• Deployment – Implementing the final AI model in real-world scenarios so that it can be used practically for decision-making or automation.

Q2: What roles does computer vision play in agricultural monitoring systems?
Ans: Computer vision helps farmers monitor and manage crops more effectively by:

• Detecting crop health: Using drones or satellite imagery, CV can identify stress in crops caused by diseases, pests, or lack of nutrients.
• Identifying pests and weeds: Automatically detects invasive plants or pest attacks that may affect yield.
• Monitoring soil and irrigation: Analyzes soil conditions and moisture levels to ensure proper irrigation.
• Estimating crop yield: Provides estimates of crop growth and productivity to support planning and distribution.
• Supporting precision farming: Enables targeted spraying of pesticides, fertilizers, and water, reducing waste and improving productivity.

Q3: Mention the factors which knowingly or unknowingly influence our decision-making.
Ans: Several factors affect human decision-making, sometimes consciously and other times unconsciously:

• Emotions: Feelings like fear, happiness, or anger strongly influence decisions.
• Personal beliefs and values: Individual moral values or religious beliefs guide choices.
• Cultural and social norms: The society we live in influences what we consider acceptable or right.
• Peer pressure: Friends, family, or colleagues can impact our choices.
• Past experiences: Previous successes or failures shape future decisions.
• Biases (conscious/unconscious): Prejudices or stereotypes affect objective thinking.
• Information availability: Limited or misleading information can distort decisions.

Q4: What is the necessity for Ethical Frameworks in AI development?
Ans: Ethical frameworks in AI are essential for:

• Preventing misuse of AI: Without ethics, AI could be used harmfully, such as spreading misinformation or causing discrimination.
• Ensuring fairness and transparency: AI systems must not favor one group unfairly; transparency ensures decisions are explainable.
• Protecting human rights and privacy: Ethics ensure that AI respects user data, privacy, and dignity.
• Providing accountability: Establishes responsibility when AI systems cause harm or errors.
• Building trust in AI systems: Ethical AI increases public confidence, making people more willing to adopt AI solutions.

Q5: Mention the key characteristics of sector-based frameworks.
Ans: Sector-based frameworks are ethical guidelines designed for specific industries. Their characteristics include:

• Industry-specific focus: They deal with unique issues of a particular sector, such as healthcare, finance, or education.
• Address unique ethical concerns: For example, in healthcare, patient privacy and informed consent are emphasized.
• Ensure legal compliance: They align with laws and regulations of that sector.
• Provide practical guidance: Offer clear steps for ethical AI use in real-world applications.
• Stakeholder involvement: Developed with input from industry experts, policymakers, and sometimes the public.

Q6: What do you mean by Bioethics?
Ans: Bioethics is a branch of applied ethics that deals with moral issues in biology, medicine, and life sciences. It examines questions about what is right or wrong in medical practices, research, and biotechnology. Examples include:

• Genetic engineering and cloning: Whether altering genes or cloning humans/animals is ethical.
• Organ transplantation: How organs should be allocated fairly.
• Euthanasia: The moral debate about assisted death for terminally ill patients.
• Clinical trials: Ensuring experiments respect human dignity and informed consent.
  Bioethics ensures that advancements in biology and medicine benefit humanity while respecting human rights and moral values.

Q7: What is Natural Language Processing? Explain any two real-life applications of NLP.
Ans: Natural Language Processing (NLP) is a branch of AI that enables computers to understand, interpret, and generate human language in a way that is meaningful. It combines linguistics and computer science to process both spoken and written language.

Applications:

• Chatbots and Virtual Assistants: Systems like Siri, Alexa, and ChatGPT use NLP to understand user queries and respond conversationally.
• Language Translation: Services like Google Translate automatically translate text between different languages, making communication across cultures easier.

Q8: How do value-based frameworks contribute to ethical decision-making by emphasizing fundamental principles and values?
Ans: Value-based frameworks focus on principles like fairness, justice, honesty, rights, and dignity. They contribute to ethical decision-making by:

• Prioritizing fundamental human values: Ensuring decisions respect rights and dignity.
• Guiding moral evaluation of actions: Judging whether an action is right or wrong based on principles rather than only outcomes.
• Balancing competing values: Helping decision-makers resolve conflicts between different ethical priorities.
• Encouraging responsible behavior: Promoting honesty, accountability, and fairness in AI development.
  These frameworks ensure that AI is developed and used in ways that align with human ethics and benefit society.