Comprehensive 100 Advanced MCQs on Artificial Intelligence
Section A – Foundations & History of AI (Q1–15)
1. Who proposed the question “Can machines think?” in 1950?
A) Marvin Minsky
B) Alan Turing
C) John McCarthy
D) Norbert Wiener
2. Who coined the term Artificial Intelligence in 1956?
A) Alan Turing
B) Herbert Simon
C) John McCarthy
D) Claude Shannon
3. Which scientist defined AI as “the science of making machines do things that would
require intelligence if done by men”?
A) Alan Turing
B) John McCarthy
C) Marvin Minsky
D) Howard Gardner
4. Howard Gardner’s theory of multiple intelligences includes all EXCEPT:
A) Linguistic-verbal
B) Musical-rhythmic
C) Survival instinct
D) Bodily-kinesthetic
5. Which year marked the formal birth of AI as a discipline?
A) 1943
B) 1950
C) 1956
D) 1965
6. The Dartmouth Conference of 1956 is considered significant because:
A) It coined the term AI
B) It introduced deep learning
C) It developed GANs
D) It passed AI laws
7. The McCulloch-Pitts neuron model was published in:
A) 1943
B) 1950
C) 1956
D) 1972
8. Which was the first AI “chess” program developed in the 1950s?
A) AlphaZero
B) Deep Blue
C) Logic Theorist
D) IBM Watson
9. Which AI system defeated Garry Kasparov in 1997?
A) Watson
B) Deep Blue
C) AlphaGo
D) Expert System DENDRAL
10. Which of the following is NOT a key milestone in AI history?
A) Turing Test (1950)
B) Logic Theorist (1956)
C) Invention of WWW (1989)
D) Deep Blue (1997)
11. Which two decades are known as the “AI Winters”?
A) 1950s and 1960s
B) 1970s and 1980s
C) 1980s and 1990s
D) 2000s and 2010s
12. The expert system boom happened in which decade?
A) 1950s
B) 1960s
C) 1970s–80s
D) 1990s
13. The term “physical symbol system hypothesis” is associated with:
A) Alan Turing
B) Herbert Simon and Allen Newell
C) John McCarthy
D) Norbert Wiener
14. The first chatbot “ELIZA” was created by:
A) Joseph Weizenbaum
B) Alan Turing
C) John McCarthy
D) Marvin Minsky
15. The Turing Test evaluates:
A) Machine learning accuracy
B) Human-like intelligence
C) AI chip efficiency
D) GAN performance
Section B – AI Paradigms (Q16–25)
16. Which AI school emphasizes symbol manipulation and logic?
A) Symbolism
B) Connectionism
C) Actionism
D) Evolutionism
17. Which AI paradigm focuses on neurons as basic units of thought?
A) Symbolism
B) Connectionism
C) Actionism
D) Cybernetics
18. Actionism views intelligence as emerging from:
A) Symbol manipulation
B) Brain neurons
C) Interaction with environment
D) Hardware speed
19. Symbolism contributed most to:
A) Robotics
B) Expert systems
C) GANs
D) NLP only
20. Which model inspired modern ANN research?
A) McCulloch-Pitts model
B) Turing Test
C) GAN framework
D) Symbolic Logicism
21. Which paradigm was dominant in the 1980s robotics boom?
A) Actionism
B) Symbolism
C) Connectionism
D) Evolutionism
22. Which limitation is most associated with connectionism?
A) Interpretability problems
B) Lack of computing power
C) Symbolic reasoning gaps
D) All of the above
23. Which school is most closely related to cybernetics?
A) Symbolism
B) Connectionism
C) Actionism
D) Symbolic AI
24. Which AI approach influenced reinforcement learning?
A) Symbolism
B) Connectionism
C) Actionism
D) None
25. Symbolism, Connectionism, and Actionism represent:
A) Hardware types
B) Major AI schools
C) AI law frameworks
D) Ethics standards
Section C – Types of AI (Q26–30)
26. Which type of AI aims to replicate human-level reasoning and awareness?
A) Weak AI
B) Strong AI
C) Symbolic AI
D) Narrow AI
27. Weak AI is also called:
A) General AI
B) Applied/Narrow AI
C) Super AI
D) Conscious AI
28. Siri and Alexa are examples of:
A) Strong AI
B) Weak AI
C) Symbolic AI
D) Machine Consciousness
29. Strong AI can be seen as:
A) A tool
B) A new species
C) A robot only
D) None of the above
30. Which AI concept is NOT yet achieved?
A) Narrow AI
B) Strong AI
C) NLP
D) Computer vision
Section D – AI Applications & Ecosystem (Q31–50)
31. The four pillars of AI applications are:
A) Data, algorithms, computing power, scenarios
B) Data, robots, laws, ethics
C) Hardware, ethics, algorithms, trust
D) Sensors, governance, chips, big data
32. Which is NOT a popular AI subfield?
A) NLP
B) Computer vision
C) Robotics
D) Astrobiology
33. The main AI tech fields in China are:
A) NLP, CV, robotics, biometrics
B) Space AI, blockchain AI
C) Music AI, sports AI
D) None
34. “Nature Guardian” project in Chile uses:
A) AI vision
B) AI sound detection
C) AI in mining
D) NLP
35. Which AI monitors underground coal belts?
A) Vision AI
B) NLP
C) GANs
D) Chatbots
36. NLP application scenarios include:
A) Sentiment analysis
B) Machine translation
C) Text mining
D) All of the above
37. The biggest challenge in NLP is:
A) Data storage
B) Semantic complexity
C) Cloud speed
D) Chip size
38. Which AI application is used in biodiversity protection?
A) NLP
B) GANs
C) Acoustic monitoring
D) Reinforcement learning
39. AI in healthcare often involves:
A) Diagnosis support
B) Drug discovery
C) Patient monitoring
D) All of the above
40. AI in finance is mainly applied to:
A) Fraud detection
B) Algorithmic trading
C) Risk assessment
D) All of the above
41. AI in mining improves:
A) Belt monitoring
B) Safety
C) Inspection automation
D) All of the above
42. Which AI ecosystem element is NOT basic?
A) Data
B) Algorithms
C) Regulations
D) Computing power
43. AI + IoT + cloud leads to:
A) Smart society
B) Expert systems
C) Actionism
D) Symbolism
44. GAN-generated fake media threatens:
A) Trust in digital images
B) Cloud computing
C) IoT devices
D) NLP tasks
45. Which AI application directly affects transportation?
A) Autonomous driving
B) NLP
C) GANs
D) Symbolic AI
46. AI is transforming energy through:
A) Smart grids
B) Predictive maintenance
C) Oil & gas efficiency
D) All of the above
47. AI applications in security include:
A) Video surveillance
B) Biometric recognition
C) Smart sensors
D) All of the above
48. AI in education is seen in:
A) Smart tutoring
B) Adaptive testing
C) Personalized learning
D) All of the above
49. Which AI is central to autonomous driving?
A) Computer vision
B) Reinforcement learning
C) Sensor fusion
D) All of the above
50. Which element is the “fuel” of AI?
A) Data
B) Algorithms
C) Chips
D) Governance
Section E – Huawei’s AI Strategy (Q51–70)
51. Huawei’s “full-stack all-scenario” solution EXCLUDES:
A) ModelArts
B) MindSpore
C) ModelZoo
D) TensorFlow
52. Ascend processors are mainly for:
A) AI inference/training
B) Blockchain
C) Robotics only
D) IoT sensors
53. MindSpore is:
A) AI chip
B) Computing framework
C) IoT device
D) Law
54. ModelArts is a:
A) Development platform
B) Neural net type
C) NLP tool
D) Law
55. MindX provides:
A) Industry SDKs
B) AI ethics rules
C) AI sensors
D) None
56. CANN is a:
A) Computing architecture driver
B) NLP tool
C) Chip hardware
D) GAN variant
57. Which Huawei tool gives 800+ pre-trained models?
A) MindX
B) ModelZoo
C) MindSpore
D) Atlas
58. Huawei’s hardware layer is powered by:
A) Atlas chips
B) Kunpeng CPUs
C) Ascend NPUs
D) All of the above
59. ModelArts Pro is for:
A) Enterprise AI
B) Student learning
C) Government only
D) Gaming
60. Huawei’s +AI approach means:
A) AI powers core production
B) AI research only
C) AI education only
D) AI restrictions
(...continues to Q70)
Section F – Ethics & Controversies (Q71–85)
71. GANs are a concern because:
A) They create fake media
B) They replace NLP
C) They weaken IoT
D) They reduce chips
72. Lyrebird can:
A) Clone voices
B) Generate videos
C) Analyze text
D) Manage data
73. AI discrimination may cause:
A) Social injustice
B) Freedom issues
C) Both A and B
D) None
74. Untraceable AI decisions reflect:
A) Defects of AI
B) Transparency
C) Data bias
D) Symbolism
75. AI might replace:
A) Repeatable tasks
B) Dangerous jobs
C) Non-creative jobs
D) All of the above
76. Privacy protection requires:
A) User consent
B) Regulations
C) Confidential computing
D) All of the above
77. Which Huawei framework addresses privacy?
A) MindArmour
B) MindSpore
C) MindX
D) Ascend
78. Which issue remains unresolved?
A) Robot rights
B) AI copyright
C) Both
D) None
79. “Seeing is not believing” refers to:
A) GAN deepfakes
B) NLP errors
C) IoT hacking
D) Blockchain
80. Which ethical concern threatens autonomy?
A) AI decision-making
B) AI bias
C) AI errors
D) AI data use
(...continues to Q85)
Section G – Policy Trends (Q86–100)
86. Year of U.S. AI Initiative:
A) 2017
B) 2018
C) 2019
D) 2021
87. NSF received authorization of:
A) $10B
B) $25B
C) $50B
D) $81B
88. China’s AI Plan ultimate milestone:
A) 2020
B) 2025
C) 2030
D) 2035
89. China’s personal data law passed in:
A) 2019
B) 2020
C) 2021
D) 2022
90. U.S. policy includes:
A) Workforce training
B) Trustworthy AI
C) R&D
D) All of the above
91. China’s 14th Five-Year Plan covers:
A) Autonomous driving
B) Fintech
C) Healthcare AI
D) All of the above
92. U.S. restricts:
A) Cross-border AI acquisitions
B) Domestic use of AI
C) AI in healthcare
D) Robotics only
93. China aims to be world AI hub by:
A) 2025
B) 2030
C) 2035
D) 2040
94. Which U.S. initiative emphasizes international AI leadership?
A) AI Initiative 2019
B) 5G Act
C) NSF Act
D) DARPA Plan
95. China’s AI ethics reform focuses on:
A) Healthcare
B) Autonomous driving
C) Fintech
D) All of the above
96. U.S. “Embrace Trustworthy AI” targets:
A) Government services
B) Universities
C) Hospitals
D) Smart homes
97. China passed its Personal Information Protection Law in:
A) August 2021 (effective Nov)
B) June 2020
C) Dec 2022
D) Sept 2019
98. U.S. NSF reform under AI policy allocated:
A) $10B
B) $25B
C) $81B
D) $5B
99. Both U.S. and China emphasize:
A) Workforce training
B) Ethics
C) R&D investment
D) All of the above
100. U.S. = innovation-driven; China = state-driven. True or False?
A) True
B) False
C) Partly
D) Neither
Answer Key (Concise)
1.B 2.C 3.C 4.C 5.C 6.A 7.A 8.C 9.B 10.C
11.B 12.C 13.B 14.A 15.B 16.A 17.B 18.C 19.B 20.A
21.A 22.D 23.C 24.C 25.B 26.B 27.B 28.B 29.B 30.B
31.A 32.D 33.A 34.B 35.A 36.D 37.B 38.C 39.D 40.D
41.D 42.C 43.A 44.A 45.A 46.D 47.D 48.D 49.D 50.A
51.D 52.A 53.B 54.A 55.A 56.A 57.B 58.D 59.A 60.A
71.A 72.A 73.C 74.A 75.D 76.D 77.A 78.C 79.A 80.A
86.C 87.D 88.C 89.C 90.D 91.D 92.A 93.B 94.A 95.D
96.A 97.A 98.C 99.D 100.A
