Font size
Worksheets1. Basic Concept and Early History of AI
Total questions: 80
Worksheet time: 40mins
Which statement best defines Artificial Intelligence in computer science?
Systems that store and retrieve static data
Programs that only execute numeric calculations
Machines that think, learn, reason, and decide
Hardware that accelerates graphics rendering
Which capability is commonly associated with AI systems?
Compressing files with fewer errors
Solving problems and learning from experience
Increasing screen brightness automatically
Rendering three-dimensional graphics faster
Which is a real-world example of AI mentioned in introductory contexts?
Bluetooth device pairing protocols
Voice assistants like Siri and Alexa
Spreadsheet macros for accounting
File system hierarchical folders
In the conceptual roots of AI, which sequence captures the flow from foundations to AI?
Linguistics → Semantics → Pragmatics → AI
Economics → Game theory → Markets → AI
Philosophy → Mathematics → Computation → AI
Biology → Chemistry → Neuroscience → AI
What key insight from mathematics contributed to AI’s foundations?
Reasoning depends on emotional states
Learning only occurs through physical practice
Logic can be represented as 0 and 1
Perception requires color vision
Who is identified as a key contributor connecting computation to the birth of AI?
Marvin Minsky
Claude Shannon
Ada Lovelace
Alan Turing
What was the purpose of the Turing Test proposed in 1950?
Measure machine speed on arithmetic tasks
Classify algorithms by computational complexity
Assess mechanical reliability under stress
Evaluate if machines can mimic human conversation
Which event in 1956 is widely regarded as marking AI as an academic discipline?
UNESCO conference on cybernetics
Royal Society symposium on logic
Dartmouth Conference on Artificial Intelligence
Bell Labs automation summit
Which early AI system is correctly matched with its description?
Logic Theorist — produced mathematical proofs
ELIZA — early rule-based chatbot
Shakey — neural network for image captioning
Perceptron — symbolic theorem prover
Which factors contributed to the AI Winters?
Breakthroughs in deep learning and GPUs
Poor real-world results leading to funding cuts
High expectations with limited computing power
Abundant data and cheap hardware expansion
During which periods did the first and second AI Winters occur?
1990–1995 and 2000–2005
1980–1984 and 1994–1998
1974–1980 and 1987–1993
1960–1967 and 1970–1972
In the expert system architecture diagram, what component transforms a knowledge base of IF–THEN rules into a decision or advice?
User interface layer
Data pipeline
Inference engine
Neural encoder
Which real-world system is cited as an example application of expert systems in the 1980s?
Watson for quiz competitions
AlphaFold for protein folding
MYCIN for medical diagnosis
PageRank for web search
According to the comparison diagram, how do traditional AI and machine learning primarily differ in creating behavior?
Traditional AI learns features from data automatically
Machine learning encodes logic as IF–THEN rules
Both rely on symbolic reasoning with no data
Traditional AI uses human-written rules; ML learns from data
Which event marked a milestone in the 1990s shift toward machine intelligence?
ImageNet dataset was released
Deep Blue defeated world chess champion
Watson won Jeopardy
AlphaGo beat a Go champion
In the deep learning revolution flowchart, what sequence best completes the pipeline from resources to impact?
GPUs → Rule bases → Symbolic reasoning → Lab demos
Big Data + GPUs → Deep Neural Networks → High Accuracy Models → Real-World AI Applications
Data lakes → Support vectors → Medium accuracy → Toy problems
Cloud storage → Decision trees → Expert advice → White-box audits
Which breakthrough is repeatedly highlighted for the 2010–present era?
Self-driving car public trials
AlphaGo defeating a human Go champion
GPT-2 text generation demo
SIRI voice assistant debut
In the modern AI ecosystem diagram, what element directly precedes Generative AI in the pipeline?
Expert rules
Large Language Models
Feature engineering
Reinforcement agents
Which set lists applications aligned with the modern AI and generative AI section?
Chatbots
Healthcare diagnosis
Education
Autonomous vehicles
Cryptocurrency mining
Which statement best captures the key mathematical contribution of George Boole to AI foundations?
Graph theory for optimal search paths
Differential equations for neural dynamics
Boolean logic using true and false values
Probability calculus for uncertain inference
Alan Turing’s 1950 proposal assessed machine intelligence by evaluating whether a machine could do what?
Build programs without human input
Pass a human performance benchmark in chess
Solve unsolved mathematical conjectures
Imitate human conversation convincingly
Which event is widely considered the official birth of AI as a research field?
Release of ELIZA in 1966
Launch of Shakey in 1969
Dartmouth Conference in 1956
Publication of Perceptrons in 1969
Which pair correctly matches artifact and capability from early AI achievements?
ELIZA — early rule-based chatbot
Shakey — stationary reasoning automaton
Logic Theorist — natural language translation
ELIZA — general theorem proving system
Which best describes the central idea behind early symbolic AI?
Storing big data for pattern discovery
Emergent behavior from random interactions
Representing thinking with symbols and rules
Learning by adjusting continuous weights
Which names were organizers of the 1956 Dartmouth Conference?
Herbert Simon
Nathan Rochester
Claude Shannon
Marvin Minsky
John McCarthy
Which expectations during 1956–1974 most contributed to later disappointment?
Belief that robotics required no reasoning ability
Belief that human-level intelligence would arrive within twenty years
Belief that human-level intelligence was decades away
Belief that AI would automate arithmetic only
Which combination lists common approaches explored during early optimism (1956–1974)?
Search algorithms
Rule-based systems
Evolutionary hardware design
Symbolic AI
Probabilistic deep learning
Which is NOT cited as a reason for the first AI winter (1974–1980)?
Limited computing power of the time
High expectations with weak results
Difficulty with real-world uncertainty
Abundant funding and industry enthusiasm
What was a typical impact of the first AI winter?
Many projects gained larger budgets
Government funding increased dramatically
Numerous AI projects were discontinued
Private labs expanded AI hiring
Expert systems of 1980–1987 primarily attempted to do what?
Imitate decision-making of human experts
Simulate human emotion and empathy
Self-improve without explicit rules
Control mobile robots with vision
Which mechanism best characterizes how expert systems encoded knowledge?
Genetic algorithms evolving rules
Gradient descent adjusting weights
Bayesian networks updating beliefs
If-then rules triggering conclusions
Which factor best explains the shift from rule-based AI to data-driven learning in the 1990s–2000s?
Invention of quantum processors early
Abandonment of statistics entirely
Availability of labeled data at scale
Desire for symbolic reasoning dominance
Which set lists key 1990s–2000s machine learning developments?
Heuristic stacks, logic solvers, Prolog tools
Neural networks, SVM, Bayesian models
Genetic coding, fuzzy trees, expert shells
Quantum nets, rule compilers, Lisp engines
What made Deep Learning succeed in the 2010s? Choose all that apply.
Massive datasets became available
Improved algorithms emerged
Decreased need for data quality
Powerful GPUs accelerated training
Which breakthrough tasks surged in the Big Data and Deep Learning era?
Symbolic theorem proving dominated
NLP capabilities expanded significantly
Speech recognition advanced rapidly
Image recognition accuracy improved
Which system is correctly matched to its achievement and year?
Deep Blue beat a grandmaster in 2007
AlphaGo defeated a Go master in 2016
Watson won chess titles in 2011
ELIZA won Turing Award in 1966
During the Second AI Winter (1987–1993), expert systems struggled primarily because they were
Scalable and cheap to maintain
Expensive and hard to update
Data-driven and self-learning
GPU-optimized and parallel
Which trend best characterizes modern AI today? Choose all that apply.
Focus on ethical and responsible AI
Generative AI producing text and images
Large Language Models at scale
Exclusive reliance on rule-based logic
Explainable AI (XAI) aims primarily to
Increase dataset size indefinitely
Make model reasoning interpretable
Hide model decisions from users
Replace neural nets with rules
Which application domains are highlighted for modern AI?
Healthcare and education
Finance and robotics
Mining and agriculture
Research and creativity
The rise of personal computers in the late 1980s contributed to AI winter by making which technology obsolete?
Cloud platforms for training
GPU clusters for deep nets
Lisp machines used for AI
Mobile chips for inference
Which statement best captures why current AI systems are considered non-conscious?
They lack subjective experience and self-awareness
They cannot play games or translate languages
They are biological systems with neural tissues
They never follow algorithms or use data
Consciousness is most accurately described as
Awareness of self, feelings, and surroundings
Producing outputs that mimic human language
High-speed processing of large datasets
The ability to execute predefined algorithms
Which pair correctly contrasts simulated and real emotions?
Chatbot showing empathy vs person feeling sadness
Neural network learning chess vs human solving puzzles
Sensor logging temperature vs server cooling fans
Algorithm updating weights vs program compiling code
Select all features that belong to consciousness, not just intelligence-like behavior.
Subjective experience or what it feels like
Real feelings and emotions with awareness
Executing tasks via predefined rules
Processing data without understanding
AI systems operate primarily through which elements?
Instincts, drives, and qualia
Ethics, laws, and social norms
Neurons, hormones, and neurotransmitters
Data, algorithms, and predefined rules
Which example highlights the key difference between pain in humans and damage detection in computers?
Human knows pain; computer detects without feeling
Both feel pain identically through sensors
Computer feels pain when hardware overheats
Human detects damage but does not feel pain
According to the table contrasting AI and consciousness, which pairing is correct?
AI: subjective experience; Consciousness: processes data
AI: real feelings; Consciousness: simulated
AI: self-aware; Consciousness: no self-awareness
AI: man-made; Consciousness: biological
Which tasks were listed as examples of AI abilities?
Experiencing what it feels like to win
Playing strategy games like chess or Go
Translating languages across contexts
Recognizing images and speech
Which claim aligns with the view that AI can never be conscious?
It imitates intelligence without understanding
It might develop awareness in the future
The brain is also a kind of machine
Machines could produce consciousness someday
Which claim aligns with the view that AI could become conscious?
Understanding is impossible for any machine
AI only follows algorithms with no meaning
If brains yield consciousness, machines might too
Subjective experience is exclusive to biology
What is the most defensible reason that intelligent behavior in AI does not imply consciousness?
Consciousness requires speech and language fully
Algorithms cannot ever produce any behavior
Only slow systems can be conscious at all
Behavior can be simulated without inner experience
Which aspect is NOT included in the definition of consciousness provided?
Awareness of oneself and surroundings
Faster computation than humans
Subjective experience of what it feels like
Feelings and emotions with intentions
Which timeline item correctly matches year to event?
1950: Turing Test proposal by Alan Turing
2016: ELIZA chatbot released to public
1936: Dartmouth Conference establishes AI
1997: Expert systems became popularized
In the AI vs Consciousness table, which row correctly matches experience?
AI processes data; consciousness has subjective experience
AI has qualia; consciousness computes datasets
AI is biological; consciousness is man-made
AI feels pain; consciousness simulates pain
Which statement about Weak (Narrow) AI is accurate?
It possesses general self-awareness
It experiences emotions during tasks
It is designed for a specific task
It replaces biological consciousness entirely
What does the Turing Test primarily assess in a machine?
Ability to imitate human conversation
Level of integrated information
Conscious awareness and experiences
Capacity for moral decision making
In the Chinese Room argument, what is the main claim about the person manipulating symbols?
They learn Chinese grammar
They translate Chinese accurately
They simulate understanding Chinese
They truly understand Chinese
According to Integrated Information Theory (IIT), consciousness depends on which factor?
Speed of neural processing
Amount of data stored
Degree of information integration
Number of sensory inputs
Which statement best contrasts Weak AI and Strong AI?
Weak AI thinks like humans
Strong AI cannot be conscious
Weak AI simulates intelligence
Strong AI exists in products now
Which feature is NOT attributed to current AI systems in the material?
Processing inputs programmatically
Following mathematical models
Producing outputs from inputs
Having emotions or feelings
Select all claims that align with IIT and the slides.
Human brains show high integration
Most AI has low integration
Consciousness tracks integrated information
Consciousness requires symbol rules
Which ethical question arises if AI becomes conscious?
How to reduce algorithmic bias
Whether it should have rights
How to speed up training
Whether to encrypt its data
Why does the Chinese Room challenge Strong AI claims about understanding?
It shows machines cannot store data
It shows rule following lacks understanding
It proves translation is impossible
It proves humans cannot learn Chinese
Which pair correctly matches thinker with idea?
Turing — Chinese Room
Searle — Turing Test
Tononi — IIT
Tononi — Symbolism thesis
Which statement best distinguishes Narrow AI from General AI?
Narrow AI performs specific tasks without real understanding
Narrow AI performs any intellectual task with understanding
General AI performs specific tasks without real understanding
General AI exists widely in commercial applications
Which example most appropriately illustrates Narrow AI in current use?
A machine with ethical self-awareness and emotions
A conscious system understanding any human goal
A chatbot answering customer questions reliably
A theory describing universal intelligence generally
Which claim about Strong AI (AGI) is accurate today?
It can already match human creativity consistently
It is task-specific and lacks understanding
It powers most face recognition systems today
It remains theoretical and does not yet exist
In the Weak vs Strong AI comparison, which pairing is correct?
Weak AI—task-specific; Strong AI—general intelligence
Weak AI—general intelligence; Strong AI—task-specific
Weak AI—conscious; Strong AI—no consciousness
Weak AI—future only; Strong AI—exists today
Which set lists typical strengths of computers over humans?
High accuracy on routine computations
Moral and ethical judgment
Very fast calculations
Continuous operation without fatigue
Large data storage capacity
Which ability is more characteristic of human strengths than computer strengths?
Creativity and moral judgment in decisions
Executing billions of operations per second
Storing petabytes of structured records
Running continuously without any rest
What is the key difference summarized between computers and humans?
Computers are fast and accurate; humans are creative and emotional
Computers are creative and emotional; humans are fast and accurate
Both are equally fast and equally creative generally
Neither computers nor humans differ significantly overall
Which domain is listed as a common AI application area?
Transportation for self-driving
Finance for fraud detection
Education for personalized learning
Mythology for analyzing ancient deities
Healthcare for medical imaging
Which example captures how an everyday service uses AI?
A mechanical clock measuring time via gears only
A paper calendar reminding dates using printed notes
A textbook explaining algebra without personalization
A maps app suggesting shortest routes based on traffic
In AI, what does logic primarily enable systems to do?
Make decisions with rules and reasoning
Render graphics with high frame rates
Compress images with minimal loss generally
Generate electricity from chemical reactions
How do Propositional and Predicate logic differ?
Neither concerns truth or relationships respectively
Predicate handles truth values only; Propositional handles objects
Both focus only on objects and relationships
Propositional uses true/false statements; Predicate handles objects and relationships
Which listed benefit is linked to using logic in AI?
Solve problems effectively
Draw justified conclusions
Increase screen brightness
Perform reasoning tasks
Reduce physical device weight
Which is NOT one of the five main components of AI listed?
Problem solving step-by-step
Reasoning with logical rules
Learning from data using models
Motor control for robotic actuation
Which pairing correctly matches a component with its example?
Perception—image and speech recognition
Problem solving—game-playing AI
Language understanding—3D printing equipment
Learning—machine learning models
Reasoning—expert systems
Which summary statement aligns with the material’s quick revision points?
Logic is optional for reasoning within AI systems
Current AI lacks consciousness and Strong AI is theoretical
Current AI has consciousness and AGI is commercial
Computers surpass humans in creativity and emotions
