unit 1 revisiting ai project cycle ethical frameworks for ai Subjective
OBEJECTIVE
AI Project Cycle & AI Domains – MCQ Answers
1. What is the primary purpose of the Problem Scoping stage?
(a) To train the AI model.(b) To collect data from various sources.
(c) To define the problem and goal of the AI project.
(d) To evaluate the model's performance.
2. How many stages are there in the AI Project Cycle?
(a) 4(b) 5
(c) 6
(d) 7
3. Which stage involves converting collected data into visual representations?
(a) Data Acquisition(b) Data Exploration
(c) Modelling
(d) Evaluation
4. What is the main objective of the Deployment stage?
(a) To test the model on new data.(b) To select the most efficient model.
(c) To integrate the AI solution into real-world environments.
(d) To acquire more data for the project.
5. AI models are categorized into three domains based on:
(a) The size of the development team.(b) The type of data fed into them.
(c) The cost of development.
(d) The amount of time it takes to develop.
6. Which AI domain deals with large datasets?
(a) Computer Vision(b) Natural Language Processing
(c) Statistical Data
(d) Robotics
7. Example of Statistical Data application:
(a) A surveillance camera system.(b) An email spam filter.
(c) A price comparison website.
(d) A self-driving car.
8. CV stands for:
(a) Central Vision(b) Computer View
(c) Coded Video
(d) Computer Vision
9. Input for Computer Vision domain:
(a) Text and documents.(b) Numerical data and tables.
(c) Photographs, videos, and images from sensors.
(d) Audio recordings and speech.
10. Primary objective of NLP:
(a) Teach machines to see images.(b) Enable machines to read, decipher, and understand human language.
(c) Create algorithms for statistical data.
(d) Translate digital data into descriptions.
11. Email spam filter belongs to:
(a) Statistical Data(b) Computer Vision
(c) Natural Language Processing
(d) Robotics
12. Frameworks provide:
(a) Random solutions.(b) Step-by-step guidance.
(c) Legal advice.
(d) Ethical justifications.
13. Main purpose of Ethical Framework for AI:
(a) Ensure profitability.(b) Make sure AI decisions don't cause unintended harm.
(c) Speed up development.
(d) Handle technical bugs.
14. Ethical Frameworks are categorized into:
(a) Legal and illegal frameworks.(b) Sector-based and value-based frameworks.
(c) Historical and contemporary frameworks.
(d) Theoretical and practical frameworks.
15. Bioethics is an example of:
(a) Rights-based framework.(b) Utility-based framework.
(c) Sector-based framework.
(d) Virtue-based framework.
AI Ethics & AI Project Cycle – MCQ Answers (Part 5)
16. Core principle of a Rights-based framework:
(a) Maximizing overall good.(b) Prioritizing human rights and dignity.
(c) Focusing on the character of the decision-maker.
(d) Avoiding harm at all costs.
17. Framework evaluating actions based on greatest benefit and minimizing harm:
(a) Rights-based framework.(b) Utility-based framework.
(c) Virtue-based framework.
(d) Sector-based framework.
18. Virtue-based framework focuses on:
(a) Consequences of actions.(b) Protection of individual rights.
(c) The character and intentions of the individuals involved.
(d) Legal regulations.
19. NOT a principle of bioethics:
(a) Respect for Autonomy.(b) Do not harm.
(c) Give justice.
(d) Maximize profit.
20. Non-maleficence means:
(a) Promoting well-being.(b) Intentionally causing harm.
(c) Avoiding causing harm or negative consequences.
(d) Ensuring fair distribution.
21. Beneficence emphasizes:
(a) Avoiding harm.(b) Promoting and maximizing the well-being of individuals and society.
(c) Fair distribution.
(d) Respecting autonomy.
22. Root cause of AI algorithm problem (case study):
(a) The algorithm was trained on biased data.(b) Not properly deployed.
(c) Problem not scoped.
(d) Model not selected efficiently.
23. Problematic AI was trained on:
(a) Physical illness metrics.(b) Healthcare expense data.
(c) Patient satisfaction scores.
(d) Hospital staffing data.
24. Principle addressing awareness of how AI works:
(a) Do not harm.(b) Maximum benefit.
(c) Respect for autonomy.
(d) Justice.
25. Justice requires distribution:
(a) Based on economic status.(b) Irrespective of a person's background.
(c) Based on location.
(d) Based on illness severity.
26. Pre-requisite for lesson on Ethical Frameworks:
(a) Advanced robotics knowledge.(b) Basic understanding of ethics and ethics in AI.
(c) Software expertise.
(d) Psychology background.
27. Purpose of "My Goodness" activity:
(a) Train AI algorithm.(b) Collect donation data.
(c) Uncover individual's biases and thought processes.
(d) Teach about global charities.
28. AI Project Cycle is cyclical means:
(a) Straight line process.(b) Process can be repeated and refined.
(c) Only specific projects.
(d) No start or end.
29. Computer Vision collects information from:
(a) Words and sentences.(b) Audio waves.
(c) Pixels.
(d) Numerical data.
30. Function of ethical framework:
(a) It provides a common language for communication.(b) Increase profit margins.
(c) Automate data acquisition.
(d) Simplify modelling stage.
AI Ethics & AI Project Cycle – MCQ Answers (Part 6)
31. In AI, "bias" refers to:
(a) A preference for a certain programming language.(b) An unintentional leaning that results in unwanted outcomes.
(c) The speed of an AI algorithm.
(d) A type of computer virus.
32. Why is the deployment stage crucial?
(a) It is the longest stage.(b) It ensures successful integration and operation in real-world environments.
(c) It is where data is collected.
(d) It is where the model is built.
33. Central idea behind Utility-based framework:
(a) Respect individual rights.(b) Align with virtuous principles.
(c) Maximize overall good and minimize harm.
(d) Prioritize human life.
34. Surveillance system detecting suspicious activities belongs to:
(a) Natural Language Processing.(b) Statistical Data.
(c) Computer Vision.
(d) Bioethics.
35. Relationship between ethics and ethical frameworks:
(a) They are the same.(b) Ethics are values, while frameworks guide application of those values.
(c) Frameworks are legal only.
(d) Ethics are a type of framework.
36. If you make a mistake in the analogy of AI Project Cycle:
(a) Continue with mistake.(b) Discard it and remake it.
(c) Ask for help.
(d) Use AI to fix.
37. Lesson summary includes recapitulation of AI Project Cycle and:
(a) History of AI.(b) Different domains of AI.
(c) Future of AI.
(d) Economic impact.
38. Large quantities of data necessitate:
(a) Data deletion.(b) Visual representation.
(c) Manual entry.
(d) More physical storage.
39. Purpose of testing models:
(a) Acquire more data.(b) Prepare for deployment.
(c) Stay on budget.
(d) Select base for project.
40. Example of NLP machine translation:
(a) Google Translate.(b) Siri.
(c) Self-driving car.
(d) Medical diagnosis tool.
41. Beneficence means:
(a) Respect autonomy.(b) Do not harm.
(c) Ensure maximum benefit for all.
(d) Give justice.
42. Purpose of case study:
(a) Provide additional data.(b) Show how to apply ethical frameworks to AI solutions.
(c) Test AI Project Cycle knowledge.
(d) Introduce new domain.
43. Value-based framework mentioned:
(a) Bioethics.(b) Rights-based.
(c) Sector-based.
(d) None of the above.
44. Non-maleficence refers to:
(a) Intentionally causing harm.(b) The principle of doing no harm.
(c) Promoting good.
(d) Fair distribution.
45. Why do we need ethical frameworks for AI?
(a) Restrict AI tasks.(b) Guarantee morally acceptable recommendations.
(c) Prove AI superiority.
(d) Simplify data acquisition.
46. Key characteristic of sector-based framework:
(a) Focus on fundamental principles.(b) Tailored to specific sectors or industries.
(c) Assess moral worth.
(d) Always prioritize rights.
47. Recapitulation means:
(a) New introduction.(b) Brief summary or review.
(c) In-depth analysis.
(d) Complex explanation.
48. Difference between Non-maleficence and Beneficence:
(a) Non-maleficence avoids harm, Beneficence promotes good.(b) Opposite meanings.
(c) Justice vs Autonomy.
(d) Same principle.
49. Framework in problem-solving is:
(a) Single solution.(b) Structured approach to problem-solving.
(c) List of problems.
(d) Software type.
50. AI algorithm in case study was biased against:
(a) Western region patients.(b) Patients from a specific ethnic background.
(c) Less severe condition patients.
(d) Patients spending more on healthcare.
AI Project Cycle – MCQ Answers (Set 1)
1. The AI Project Cycle mainly has __.
(a) 2 Stages(b) 3 Stages
(c) 4 Stages
(d) 5 Stages
2. The _ is the first stage of the AI project cycle.
(a) Problem Scoping(b) Data Acquisition
(c) Data Exploration
(d) Data Modelling
3. The _ is the fifth stage of the AI project cycle.
(a) Problem Scoping(b) Data Evaluation
(c) Data Exploration
(d) Data Modelling
4. _ helps to acquire data for the project.
(a) Problem Scoping(b) Data Acquisition
(c) Data Exploration
(d) Data Evaluation
5. Whenever we want an AI project to be able to predict an output, we need to _ it first using data.
(a) Analyze(b) Train
(c) Explore
(d) All of the above
6. For better efficiency of an AI project, the _ needs to be relevant and authentic.
(a) Testing Data(b) Training Data
(c) Exploring Data
(d) All of the above
7. __ refer to the type of data you want to collect.
(a) Data features(b) Exploring Data
(c) Data Acquisition
(d) All of the above
8. What are the different ways to collect data?
(a) Web Scraping & API(b) Surveys & Sensors
(c) Cameras & Observations
(d) All of the above
9. It becomes necessary to find a __.
(a) Reliable source(b) Random source
(c) Unauthorize source
(d) All of the above
10. What do you mean by problem scoping?
(a) Creating an algorithm to solve a problem(b) Proper solution of a problem
(c) Recognizing a problem and having a plan to address it.
(d) Analyzing trends in collected data
11. Once the __ is complete, you now need to test your model on newly fetched data.
(a) Data Acquisition(b) Modelling
(c) Data Mining
(d) None of the above
12. What is the Problem Statement Template?
(a) Data set compiled to identify components(b) The template summarizes each card in the 4Ws Problem Canvas
(c) Template offers data prediction
(d) None of the above
13. Which is not a reliable source?
(a) System Hacking(b) Surveys
(c) Website
(d) None of the above
14. What are the various parameters that affect the problem?
(a) Acquire data as project base(b) Collect data from reliable sources
(c) Explore patterns to decide model type
(d) All of the above
15. Whenever we want an AI project to predict an output, we need to _ it first using data.
(a) Analyze(b) Train
(c) Explore
(d) All of the above
AI Project Cycle – MCQ Answers (Set 2)
16. This previous data is known as:
(a) Testing Data(b) Training Data
(c) Exploring Data
(d) All of the above
17. Simple file format storing data separated by commas:
(a) jpg(b) doc
(c) csv
(d) png
18. Identify the incorrect statement:
i) AI models can be categorized into four domains.ii) Data sciences is one domain of AI.
iii) Price comparison websites are examples of data science.
iv) Information from data science helps decision making.
(a) Only iv)
(b) iii) and iv)
(c) Only (i)
(d) ii) and (iii)
19. Application of data science:
(a) Text summarization(b) Target Advertisements
(c) Face lock in smartphones
(d) Email filters
20. Expand CBT:
(a) Computer Behaved Training(b) Cognitive Behavioural Therapy
(c) Consolidated Batch of trainers
(d) Combined Basic Training
21. 4Ws Problem Canvas is part of:
(a) Problem Scoping(b) Data Acquisition
(c) Modelling
(d) Evaluation
22. Term for machines performing tasks using neural networks and large data:
Deep Learning23. Assertion & Reason:
(a) Both A and R are correct and R is the correct explanation of A(b) Both A and R are correct but R is NOT the correct explanation
(c) A is correct but R is not correct
(d) A is not correct but R is correct
24. Name any two intelligences:
Logical-Mathematical Intelligence, Linguistic Intelligence25. Helps summarize key points into single outline:
(a) 4W Problem canvas(b) Problem Statement Template
(c) Data Acquisition
(d) Algorithm
26. Ideal problem statement template:
(a) Use different airlines(b) Board before crew enters
(c) Current boarding wastes four minutes; solution is side boarding instead of back-to-front.
(d) Sell the airlines
27. One looks at parameters affecting the problem under:
Problem Scoping28. Machine trained with huge amounts of data:
(a) Machine Learning(b) Artificial Intelligence
(c) NLP
(d) Deep Learning
29. Contributes to AI project efficiency:
(a) High Model Complexity(b) Relevant and Authentic Training Data
(c) Minimal Preprocessing
(d) Limited Hardware Resources
30. Reliable source for authentic data:
(a) Private websites(b) Government websites
(c) Personal websites
(d) None of the above
AI Project Cycle – MCQ Answers (Set 3)
31. It gives us a suitable framework that helps us reach the objective of our AI project.
(a) 4Ws Canvas(b) AI Project Cycle
(c) Project Model
(d) AI Models
32. We examine parameters affecting the problem under the _ stage.
(a) Data Exploration(b) Evaluation
(c) Modelling
(d) Problem Scoping
33. The given steps are used for collecting data from:
(a) Cameras(b) Sensors
(c) Surveys
(d) Web scraping
34. Fraction of positive cases correctly identified:
(a) Precision(b) Accuracy
(c) Recall
(d) F1
35. Assertion & Reason:
(d) Both (a) and (R) are false36. Correct order of AI Project Cycle:
(a) Evaluation -> Problem Scoping -> Data Exploration -> Data Acquisition -> Modelling(b) Problem Scoping -> Data Exploration -> Data Acquisition -> Evaluation -> Modelling
(c) Data Acquisition -> Problem Scoping -> Data Exploration -> Modelling -> Evaluation
(d) Problem Scoping -> Data Acquisition -> Data Exploration -> Modelling -> Evaluation
37. Assertion & Reason:
(a) Both A and R are correct and R is the correct explanation of A38. Divided into multiple layers and nodes:
(a) Neural Networks(b) Convolutional Neural Network (CNN)
(c) Machine learning algorithm
(d) Hidden Layers
39. Concept unifying statistics, data analysis and ML:
(a) Computer Vision(b) Natural Language Processing
(c) Data Science
(d) Computer Science
40. Task used for multiple objects in Computer Vision:
(a) Classification(b) Classification + Localisation
(c) Instance Segmentation
(d) Localisation
41. Correct order of AI Project Cycle:
(a) Data Exploration, Problem Scoping, Modelling, Evaluation, Data Acquisition(b) Problem Scoping, Data Acquisition, Data Exploration, Modelling, Evaluation
(c) Modelling, Data Acquisition, Evaluation, Problem Scoping, Data Exploration
(d) Data Acquisition, Data Exploration, Problem Scoping, Modelling, Evaluation
42. Not part of AI Project Cycle:
(a) Data Exploration(b) Modelling
(c) Testing
(d) Problem Scoping
43. AI modelling where machine learns by itself:
(a) Learning Based(b) Rule Based
(c) Machine Learning
(d) Data Sciences
44. Last stage of AI Project Cycle:
(a) Problem Scoping(b) Evaluation
(c) Modelling
(d) Data Acquisition
45. Two methods of collecting data:
(a) Surveys and Interviews(b) Rumors and Myths
(c) AI models and applications
(d) Imagination and thoughts
AI Project Cycle – MCQ Answers (Set 4)
46. The __________________canvas helps in identifying key elements related to the problem.
(a) Problem scoping(b) 4Ws Problem
(c) Project cycle
(d) Algorithm
47. If Prediction is “Yes” and matches Reality → ?
If Prediction is “Yes” and does not match Reality → ?
(b) True Negative, False Negative
(c) True Negative, False Positive
(d) True Positive, False Positive
48. NOT one of the blocks of the 4Ws Problem Canvas:
(a) When(b) Where
(c) What
(d) Why
49. Machine mimicking human traits is said to have:
(a) Computational Skills(b) Learning Capability
(c) Artificial Intelligence
(d) Cognitive Processing
50. Statement Analysis:
Statement 1: To evaluate a model’s performance, we need either precision or recall.Statement 2: When Precision and Recall are 1, F1 score is 0.
(a) Both correct
(b) Both statement 1 and statement 2 are incorrect.
(c) Statement 1 correct, 2 incorrect
(d) Statement 1 incorrect, 2 correct
51. Recall is:
(a) Defined as the fraction of positive cases that are correctly identified.(b) Percentage of true positive vs predicted positive
(c) Percentage of correct predictions overall
(d) Comparison between prediction and reality
52. The person starting a project should be clear with:
(a) Problem Reasons(b) Problem Statement
(c) Problem Solutions
(d) None of the above
53. Information sharing in problem scoping:
(a) Increases misunderstanding(b) Ensures issue won’t arise again
(c) Adds actual value to the organization
(d) Data flow understood clearly
54. You need to __ which becomes the base of your project.
(a) Acquire Data(b) Database
(c) Data Mining
(d) None of the above
55. _ by collecting data from reliable and authentic sources.
(a) Data Acquisition(b) Database
(c) Data Mining
(d) None of the above
56. Define Machine Learning:
(a) Machine learning is the study of computer algorithms that improve automatically through experience.(b) Technique to mimic human intelligence
(c) Systems performing programmed tasks
(d) Projects allowing machine to work on logic
57. Intrapersonal Intelligence describes:
(a) Understanding others’ emotions(b) Mathematical proficiency
(c) Self-awareness including strengths and weaknesses
(d) Spatial visualization skills
58. The __ Problem Canvas helps identify key elements.
(a) 4Ws(b) 6Ws
(c) 2Ws
(d) 3Ws
59. The __ block analyzes people affected directly or indirectly.
(a) Who(b) What
(c) Where
(d) Why
60. _ helps determine the nature of the problem.
(a) Who(b) What
(c) Where
(d) Why
AI Project Cycle – MCQ Answers (Set 5)
61. “What” block helps gather evidence from:
(a) Media(b) Announcements
(c) Newspaper & Articles
(d) All of the above
62. “Where” block helps look into the situation where:
(a) Problem arises(b) The context of it
(c) The locations
(d) All of the above
63. In “Why” block canvas, base of problem solving:
(a) Who will be benefitted(b) What is to be solved
(c) Where solution deployed
(d) All of the above
64. After filling 4Ws canvas, summarize into one:
(a) Template(b) Situation
(c) Both a. and b.
(d) None of the above
65. We look back at the __ to understand key elements.
(a) Problem Solving Template(b) Problem Statement Template
(c) Problem Arising Template
(d) None of the above
66. To predict output, we need to _ it first using data.
(a) Analyze(b) Train
(c) Explore
(d) All of the above
67. For better efficiency, _ must be relevant and authentic.
(a) Testing Data(b) Training Data
(c) Exploring Data
(d) All of the above
68. AI models can be classified as:
(a) Learning Based(b) Rule Based
(c) Both a. and b.
(d) None of the above
69. Learning Based models include:
(a) Machine Learning(b) Deep Learning
(c) Both a. and b.
(d) None of the above
70. AI modelling where rules are defined by developer:
(a) Rule Based Approach(b) Learning based Approach
(c) Both a. and b.
(d) None of the above
71. _ tells us about conditions for decision making:
(a) Dataset(b) Rule Based
(c) Learning based
(d) None of the above
72. Learning based approaches are divided into:
(a) 2(b) 3
(c) 4
(d) 5
73. Correct for Learning based approach:
(a) Supervised Learning(b) Unsupervised Learning
(c) Reinforcement Learning
(d) All of the above
74. In a _ model, dataset is labeled:
(a) Supervised Learning(b) Unsupervised Learning
(c) Reinforcement Learning
(d) All of the above
75. Types of supervised learning:
(a) Classification(b) Regression
(c) Both a. and b.
(d) None of the above
AI Project Cycle – MCQ Answers (Set 6)
76. Where data is classified according to labels is known as:
(a) Classification(b) Regression
(c) Both a. and b.
(d) None of the above
77. _ models work on continuous data.
(a) Classification(b) Regression
(c) Both a. and b.
(d) None of the above
78. An _ model works on an unlabeled dataset.
(a) Unsupervised learning(b) Supervised learning
(c) Reinforcement Learning
(d) All of the above
79. Models used to identify relationships, patterns and trends:
(a) Unsupervised learning(b) Supervised learning
(c) Reinforcement Learning
(d) All of the above
80. Unsupervised learning models are divided into:
(a) 5(b) 4
(c) 3
(d) 2
81. Categories of Unsupervised learning:
(a) Clustering(b) Dimensionality Reduction
(c) Both a. and b.
(d) None of the above
82. Algorithm that clusters unknown data based on patterns:
(a) Clustering(b) Dimensionality Reduction
(c) Both a. and b.
(d) None of the above
83. To reduce dimensions in Unsupervised learning:
(a) Supervised algorithm(b) Dimensionality reduction algorithm
(c) Clustering algorithm
(d) None of the above
84. _ helps to test data to calculate efficiency and performance.
(a) Accuracy(b) Evaluation
(c) Precision
(d) None of the above
85. First layer of a Neural Network:
(a) Output Layer(b) Input Layer
(c) Hidden Layer
(d) All of the above
86. The job of an __ is to acquire data and feed it to the Neural Network.
(a) Output Layer(b) Input Layer
(c) Neural Layer
(d) All of the above
87. In Neural Network, processing occurs in:
(a) Output Layer(b) Input Layer
(c) Hidden Layer
(d) All of the above
88. Hidden Layers means:
(a) Layers are hidden(b) Not visible to the user
(c) Both a. and b.
(d) None of the above
89. Each node in hidden layer executes its own:
(a) Machine Learning Methods(b) Machine Learning Approach
(c) Machine Learning Algorithm
(d) All of the above
90. Final processed data is passed to the:
(a) Output Layer(b) Input Layer
(c) Hidden Layer
(d) All of the above
AI & Ethical Frameworks – MCQ Answers (Set 7)
91. This example represents:
(a) Data Privacy(b) AI Access
(c) AI Bias
(d) Data Exploration
92. Purpose of defining the problem statement:
(a) To collect data(b) To understand the aim and objective of the project
(c) To train the model
(d) To process data
93. AI models are categorized into:
(a) Two domains(b) Four domains
(c) Three domains
(d) Five domains
94. Primary function in Statistical Data domain:
(a) Generating datasets(b) Analyzing data to extract insights
(c) Converting data into images
(d) Distributing data across networks
95. Main goal of Computer Vision projects:
(a) Translating audio data(b) Converting digital to analogue
(c) Teaching machines textual information
(d) Converting digital visual data into computer-readable language
96. Frameworks provide:
(a) Random solutions(b) Step-by-step guidance
(c) Legal advice
(d) Ethical justifications
97. Ethical Frameworks are categorized into:
(a) Legal and illegal(b) Sector-based and value-based frameworks
(c) Historical and contemporary
(d) Theoretical and practical
98. Central focus of virtue-based frameworks:
(a) Maximizing utility(b) Protecting human rights
(c) Aligning actions with ethical principles and beliefs
(d) Legal compliance
99. Rights-based frameworks:
(a) Prioritizing human rights and dignity(b) Maximizing overall good
(c) Character-centered decisions
(d) Greatest benefit outcomes
100. Primary domain of Bioethics:
(a) Agriculture(b) Healthcare and life sciences
(c) Information technology
(d) Environmental conservation
101. Assertion & Reason:
(a) Both Assertion and Reasoning are true, and Reasoning is the correct explanation of the Assertion.(b) Assertion true, Reason false
(c) Both true but Reason not explanation
(d) Assertion false, Reason true
102. Assertion & Reason:
(a) Both Assertion and Reasoning are true, and Reasoning is the correct explanation of the Assertion.(b) Assertion true, Reason false
(c) Both true but Reason not explanation
(d) Assertion false, Reason true