XI AI : Unit 1: Introduction- AI for Everyone

Introduction- AI for Everyone

MCQs

1. What is Artificial Intelligence (AI)?
a) A system that performs tasks requiring human intelligence
b) A rule-based system
c) A simple machine that follows commands
d) A type of hardware device
Answer: a) A system that performs tasks requiring human intelligence
2. Which of the following is an example of AI in daily life?
a) Microwave oven
b) Electric fan
c) Self-driving car
d) Basic calculator
Answer: c) Self-driving car
3. Who coined the term “Artificial Intelligence”?
a) Alan Turing
b) John McCarthy
c) Marvin Minsky
d) Herbert Simon
Answer: b) John McCarthy
4. Which AI concept focuses on teaching machines to understand human language?
a) Computer Vision
b) Cognitive Computing
c) Natural Language Processing (NLP)
d) Data Science
Answer: c) Natural Language Processing (NLP)
5. What is the role of Machine Learning in AI?
a) Machines learning from data without being explicitly programmed
b) Pre-programmed instructions for machines
c) Data collection
d) Automation without learning
Answer: a) Machines learning from data without being explicitly programmed
Evolution of AI
6. In which year was the Dartmouth Conference, marking the birth of AI, held?
a) 1950
b) 1956
c) 1965
d) 1972
Answer: b) 1956
7. What did Alan Turing propose in his 1950 paper?
a) The concept of Natural Language Processing
b) The imitation game (Turing test)
c) The idea of neural networks
d) The first AI algorithm
Answer: b) The imitation game (Turing test)
8. Which decade saw the advent of expert systems and symbolic reasoning in AI?
a) 1950s
b) 1960s
c) 1980s
d) 1990s
Answer: b) 1960s
Types of AI
9. Which type of AI is focused on solving specific tasks?
a) Narrow AI
b) General AI
c) Artificial Superintelligence
d) Broad AI
Answer: a) Narrow AI
10. What is the theoretical type of AI that could perform any intellectual task a human can do?
a) Narrow AI
b) General AI
c) Artificial Superintelligence
d) Machine Learning
Answer: b) General AI
11. Which of the following is an example of Narrow AI?
a) A system that can translate languages
b) A robot that can think like a human
c) A self-aware machine
d) A system with abstract thinking abilities
Answer: a) A system that can translate languages
Domains of AI
12. What does Natural Language Processing (NLP) focus on?
a) Visual data interpretation
b) Numerical data processing
c) Understanding human language
d) Predicting stock prices
Answer: c) Understanding human language
13. Which AI domain deals with interpreting visual information from images or videos?
a) NLP
b) Computer Vision
c) Data Science
d) Cognitive Computing
Answer: b) Computer Vision
14. Which domain of AI involves analyzing large datasets for insights?
a) Cognitive Computing
b) Data Science
c) NLP
d) Computer Vision
Answer: b) Data Science
Machine Learning (ML)
15. Which type of learning involves labeled data to make predictions?
a) Supervised Learning
b) Unsupervised Learning
c) Reinforcement Learning
d) Deep Learning
Answer: a) Supervised Learning
16. Which machine learning method is based on trial and error to maximize rewards?
a) Supervised Learning
b) Unsupervised Learning
c) Reinforcement Learning
d) Deep Learning
Answer: c) Reinforcement Learning
17. What is a key feature of Deep Learning?
a) Works on small datasets
b) Divides tasks into sub-tasks
c) Requires large datasets and complex networks
d) Uses simple calculations
Answer: c) Requires large datasets and complex networks
Benefits and Challenges of AI
18. Which of the following is NOT a benefit of AI?
a) Increased productivity
b) Improved decision-making
c) Enhanced job security
d) Innovation in various fields
Answer: c) Enhanced job security
19. What is a major concern related to AI ethics?
a) Speed of computation
b) Explainability of decisions
c) Simplicity of algorithms
d) Power consumption
Answer: b) Explainability of decisions
20. What challenge arises with AI concerning personal data?
a) Data overload
b) Data privacy concerns
c) Data simplicity
d) Data modeling
Answer: b) Data privacy concerns
Cognitive Computing
21. What is the main goal of Cognitive Computing?
a) Mimic human decision-making processes
b) Automate mechanical tasks
c) Follow rule-based instructions
d) Replace human thought
Answer: a) Mimic human decision-making processes
22. Which AI system is an example of Cognitive Computing?
a) IBM Watson
b) Google Translate
c) Quickdraw
d) Siri
Answer: a) IBM Watson
23. What are the main components of Cognitive Computing?
a) Learning, reasoning, interaction
b) Programming, automation, analysis
c) Language, vision, speech
d) Memory, storage, retrieval
Answer: a) Learning, reasoning, interaction
Miscellaneous
24. Which AI function is most relevant for facial recognition?
a) NLP
b) Data Science
c) Computer Vision
d) Cognitive Computing
Answer: c) Computer Vision
25. Which AI-powered game involves guessing user drawings?
a) Quickdraw
b) Semantris
c) I, Robot
d) Turing Test
Answer: a) Quickdraw
26. What is the primary concern with AI’s impact on jobs?
a) Efficiency
b) Job displacement
c) Innovation
d) Productivity
Answer: b) Job displacement
27. Which learning method involves discovering patterns in unlabeled data?
a) Supervised Learning
b) Unsupervised Learning
c) Reinforcement Learning
d) Structured Learning
Answer: b) Unsupervised Learning
AI Applications
28. Which application would best use NLP?
a) Spam email detection
b) Face recognition
c) Stock prediction
d) Object detection
Answer: a) Spam email detection
29. What is an example of AI used in healthcare?
a) Image recognition for tumor diagnosis
b) Voice-based shopping
c) Autonomous drones
d) Language translation
Answer: a) Image recognition for tumor diagnosis
Artificial Intelligence Concepts
30. What is a key difference between traditional rule-based systems and AI systems?
a) AI systems follow explicit rules
b) AI systems learn from data
c) Rule-based systems are faster
d) Rule-based systems perform better at complex tasks
Answer: b) AI systems learn from data
31. Which of the following is NOT considered a part of AI?
a) Cognitive computing
b) Machine learning
c) Simple automation tools
d) Deep learning
Answer: c) Simple automation tools
32. Which concept refers to machines capable of learning and improving from data without direct programming?
a) Automation
b) Data science
c) Machine learning
d) Cognitive computing
Answer: c) Machine learning
33. Which of the following is an example of unstructured data?
a) Stock prices
b) Customer comments
c) Names and addresses
d) Dates
Answer: b) Customer comments
34. Which layer of AI represents the most complex and human-like intelligence?
a) Narrow AI
b) General AI
c) Artificial Superintelligence
d) Broad AI
Answer: c) Artificial Superintelligence
Machine Learning and Deep Learning
35. Which of the following is a characteristic of supervised learning?
a) Finds hidden patterns in unlabeled data
b) Uses labeled data for predictions
c) Focuses on task-specific training
d) Receives rewards for correct actions
Answer: b) Uses labeled data for predictions
36. Which AI technique divides tasks into sub-tasks and solves them individually?
a) Deep learning
b) Machine learning
c) Data science
d) Cognitive computing
Answer: b) Machine learning
37. Which machine learning method often requires large amounts of data to be effective?
a) Supervised learning
b) Unsupervised learning
c) Deep learning
d) Reinforcement learning
Answer: c) Deep learning
38. In reinforcement learning, how does the machine learn?
a) By analyzing patterns in data
b) By being explicitly programmed
c) Through rewards and penalties
d) By trial and error with no feedback
Answer: c) Through rewards and penalties
Ethical Considerations in AI
39. Which of the following is an ethical concern related to AI?
a) High-speed computation
b) Bias in AI algorithms
c) Faster decision-making
d) Improved accuracy of predictions
Answer: b) Bias in AI algorithms
40. Why is AI transparency important?
a) It allows machines to make faster decisions
b) It ensures machines use more data
c) It helps humans understand how AI makes decisions
d) It increases the speed of AI processing
Answer: c) It helps humans understand how AI makes decisions
41. What is a potential drawback of AI in decision-making?
a) Enhanced productivity
b) Lack of transparency in complex models
c) Reducing human intervention
d) Ability to work with large datasets
Answer: b) Lack of transparency in complex models
Data in AI
42. Which of the following is a key characteristic of structured data?
a) It is easy to analyze due to organized format
b) It lacks specific organization
c) It is harder to manipulate
d) It includes images and videos
Answer: a) It is easy to analyze due to organized format
43. Which data type involves a blend of organized and unstructured content?
a) Structured data
b) Unstructured data
c) Semi-structured data
d) Non-interactive data
Answer: c) Semi-structured data
AI Domains and Applications
44. Which AI domain focuses on interpreting and analyzing numerical and alphanumeric data?
a) Computer Vision
b) Natural Language Processing
c) Data Science
d) Cognitive Computing
Answer: c) Data Science
45. Which application belongs to the domain of Computer Vision?
a) Spam email detection
b) Object detection in self-driving cars
c) Language translation
d) Fraud detection
Answer: b) Object detection in self-driving cars
46. Which of the following is an example of Natural Language Processing?
a) Text summarization
b) Facial recognition
c) Gesture recognition
d) Stock prediction
Answer: a) Text summarization
47. Which AI application helps optimize performance in sports analytics?
a) Computer Vision
b) Data Science
c) Natural Language Processing
d) Reinforcement Learning
Answer: b) Data Science
48. What is the key function of AI in self-driving cars?
a) Recognizing spoken language
b) Identifying objects and making decisions
c) Performing tasks based on rules
d) Recommending actions to drivers
Answer: b) Identifying objects and making decisions
Cognitive Computing and Reasoning
49. What is the purpose of Cognitive Computing in AI?
a) To automate physical tasks
b) To improve human decision-making
c) To generate text from raw data
d) To store vast amounts of data
Answer: b) To improve human decision-making
50. Which AI technology attempts to mimic the human brain’s ability to process information?
a) Natural Language Processing
b) Cognitive Computing
c) Machine Learning
d) Computer Vision
Answer: b) Cognitive Computing