1What is the main goal of Artificial Intelligence?
Introduction to AI and its evolution
Easy
A.To store only numerical data
B.To simulate human intelligence
C.To replace all computer networks
D.To design larger batteries
Correct Answer: To simulate human intelligence
Explanation:
Artificial Intelligence aims to create systems that can perform tasks requiring abilities such as learning, reasoning, and decision-making.
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2Which event is commonly associated with the birth of AI as a formal field?
Introduction to AI and its evolution
Easy
A.The launch of GPS
B.The creation of email
C.The invention of the camera
D.The Dartmouth workshop
Correct Answer: The Dartmouth workshop
Explanation:
The 1956 Dartmouth workshop is widely considered the starting point of AI as an organized academic field.
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3What type of AI is designed to perform one specific task?
Types of Artificial Intelligence
Easy
A.Universal AI
B.Narrow AI
C.Super AI
D.General AI
Correct Answer: Narrow AI
Explanation:
Narrow AI is built for a limited task, such as recognizing faces or recommending products.
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4What does Artificial General Intelligence refer to?
Types of Artificial Intelligence
Easy
A.A robot with no learning ability
B.Human-level ability across many tasks
C.A system for one fixed calculation
D.A database containing images
Correct Answer: Human-level ability across many tasks
Explanation:
Artificial General Intelligence describes a theoretical system that could perform a wide range of intellectual tasks like a human.
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5What is Machine Learning?
AI vs ML vs Deep Learning vs Data Science
Easy
A.A programming language for websites
B.A method that learns from data
C.A hardware device for storage
D.A method that avoids all data
Correct Answer: A method that learns from data
Explanation:
Machine Learning enables computer systems to identify patterns and improve their performance using data.
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6Deep Learning mainly uses which type of model?
AI vs ML vs Deep Learning vs Data Science
Easy
A.Physical measuring tools
B.Manual decision lists
C.Artificial neural networks
D.Relational database tables
Correct Answer: Artificial neural networks
Explanation:
Deep Learning uses neural networks with many layers to learn complex patterns from data.
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7Which field combines statistics, programming, and domain knowledge to study data?
AI vs ML vs Deep Learning vs Data Science
Easy
A.Computer graphics
B.Operating systems
C.Network engineering
D.Data Science
Correct Answer: Data Science
Explanation:
Data Science uses statistical and computational methods to collect, analyze, and communicate insights from data.
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8What is the first step in many AI problem-solving processes?
Problem-solving using AI and AI Development Lifecycle
Easy
A.Define the problem
B.Delete the training data
C.Deploy the final model
D.Replace the hardware
Correct Answer: Define the problem
Explanation:
Clearly defining the problem helps determine the required data, method, and success criteria.
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9What is the purpose of training an AI model?
Problem-solving using AI and AI Development Lifecycle
Easy
A.To learn patterns from examples
B.To remove every input feature
C.To convert software into hardware
D.To stop the model from making predictions
Correct Answer: To learn patterns from examples
Explanation:
During training, a model uses examples to learn relationships that can help it make predictions on new data.
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10Which stage checks how well an AI model performs on data?
Problem-solving using AI and AI Development Lifecycle
Easy
A.Initialization
B.Compression
C.Evaluation
D.Formatting
Correct Answer: Evaluation
Explanation:
The evaluation stage measures model performance using selected metrics and test data.
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11What is an intelligent agent?
Intelligent Agents and Agent Environment
Easy
A.A system that senses and acts
B.A cable that connects devices
C.A file that stores passwords
D.A screen that displays text
Correct Answer: A system that senses and acts
Explanation:
An intelligent agent perceives its environment through sensors and takes actions through actuators.
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12In an intelligent agent, what do sensors do?
Intelligent Agents and Agent Environment
Easy
A.Collect information from the environment
B.Move the agent to a new location
C.Translate code into machine language
D.Create backup copies of software
Correct Answer: Collect information from the environment
Explanation:
Sensors allow an agent to perceive or collect information about its surroundings.
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13What do actuators allow an agent to do?
Intelligent Agents and Agent Environment
Easy
A.Store historical datasets
B.Identify the operating system
C.Perform actions in the environment
D.Measure the agent's accuracy
Correct Answer: Perform actions in the environment
Explanation:
Actuators are mechanisms through which an agent acts, such as wheels, robotic arms, or software commands.
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14How can AI support healthcare?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Easy
A.By preventing doctors from using tools
B.By replacing every hospital building
C.By removing all medical records
D.By helping detect diseases
Correct Answer: By helping detect diseases
Explanation:
AI can analyze medical images and patient information to assist professionals in detecting diseases.
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15How is AI commonly used in manufacturing?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Easy
A.For disabling production sensors
B.For hiding equipment failures
C.For predictive maintenance
D.For removing quality checks
Correct Answer: For predictive maintenance
Explanation:
AI can identify patterns in equipment data and help predict failures before they occur.
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16Which is an example of AI in a smart city?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Easy
A.Turning off all street lights
B.Removing public transportation
C.Printing paper maps only
D.Optimizing traffic signals
Correct Answer: Optimizing traffic signals
Explanation:
AI can analyze traffic patterns and adjust signals to improve traffic flow in a smart city.
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17What does fairness in AI aim to reduce?
Ethics in AI and Responsible AI
Easy
A.The size of datasets
B.The number of software updates
C.The speed of computers
D.Unjust bias in decisions
Correct Answer: Unjust bias in decisions
Explanation:
Fairness in AI focuses on reducing unjust or discriminatory outcomes for individuals or groups.
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18Why is transparency important in AI systems?
Ethics in AI and Responsible AI
Easy
A.It helps people understand decisions
B.It guarantees unlimited storage
C.It removes the need for testing
D.It makes every model open source
Correct Answer: It helps people understand decisions
Explanation:
Transparent AI systems provide information about how or why important decisions are made.
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19What can Generative AI create?
Introduction to Generative AI
Easy
A.Only fixed spreadsheet formulas
B.New text, images, or audio
C.Only physical machine parts
D.Only printed circuit boards
Correct Answer: New text, images, or audio
Explanation:
Generative AI produces new content, including text, images, music, audio, and video.
Incorrect! Try again.
20What is a prompt in Generative AI?
Introduction to Generative AI
Easy
A.A file used to cool a computer
B.An instruction given to the model
C.A physical sensor in a robot
D.A password for a database
Correct Answer: An instruction given to the model
Explanation:
A prompt is the text or other input that guides a Generative AI model in producing an output.
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21A bank uses a computer system that examines previous loan decisions and recommends whether a new applicant should be approved. Which development in AI does this example best represent?
Introduction to AI and its evolution
Medium
A.A purely mechanical calculator
B.A rule-based expert system
C.A random decision generator
D.A manual record-keeping process
Correct Answer: A rule-based expert system
Explanation:
The system applies stored knowledge and decision rules to support loan evaluation, which is characteristic of an expert system.
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22Why did early AI systems often perform poorly when faced with situations outside their programmed rules?
Introduction to AI and its evolution
Medium
A.They automatically changed their goals too often
B.They were designed only for image generation
C.They depended mainly on fixed symbolic representations
D.They required no data or domain knowledge
Correct Answer: They depended mainly on fixed symbolic representations
Explanation:
Many early systems relied on explicitly programmed symbols and rules, so they had limited ability to generalize to unfamiliar situations.
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23A customer-service chatbot can answer questions about billing but cannot control a robot or diagnose medical conditions. How should this system be classified?
Types of Artificial Intelligence
Medium
A.Narrow AI
B.General AI
C.Superintelligent AI
D.Self-aware AI
Correct Answer: Narrow AI
Explanation:
Narrow AI is designed to perform specific tasks within a limited domain rather than demonstrate broad human-like intelligence.
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24Which situation would provide the strongest evidence that a system is approaching Artificial General Intelligence?
Types of Artificial Intelligence
Medium
A.It learns and applies knowledge across many unrelated domains
B.It translates text between two selected languages
C.It performs one image-classification task accurately
D.It searches a large database for matching records
Correct Answer: It learns and applies knowledge across many unrelated domains
Explanation:
Artificial General Intelligence refers to broad, flexible intelligence that can transfer knowledge across different types of tasks.
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25A team builds a model that predicts customer churn using customer records, visualizes trends, and recommends retention strategies. Which description best fits the overall work?
AI vs ML vs Deep Learning vs Data Science
Medium
A.Data science involving AI techniques
B.Only database administration
C.Only artificial intelligence
D.Only deep learning
Correct Answer: Data science involving AI techniques
Explanation:
The work combines data analysis, visualization, prediction, and recommendations, so it fits data science while using AI or machine learning methods.
Incorrect! Try again.
26A neural network with many hidden layers learns features directly from thousands of medical images. Which term most specifically describes this approach?
AI vs ML vs Deep Learning vs Data Science
Medium
A.Database indexing
B.Simple automation
C.Deep learning
D.Data science
Correct Answer: Deep learning
Explanation:
Deep learning uses neural networks with multiple layers to learn representations and patterns from large datasets.
Incorrect! Try again.
27Which statement best explains the relationship among AI, machine learning, and deep learning?
AI vs ML vs Deep Learning vs Data Science
Medium
A.AI, ML, and deep learning are identical terms with no distinction
B.Deep learning is broader than AI and includes all data analysis
C.Machine learning is unrelated to AI but depends on databases
D.AI is the broad field, ML is a subset, and deep learning is a subset of ML
Correct Answer: AI is the broad field, ML is a subset, and deep learning is a subset of ML
Explanation:
Artificial intelligence is the broad discipline, machine learning is an approach within AI, and deep learning is a machine learning approach based on multilayer neural networks.
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28An AI team discovers that its training data contains many duplicate records and inconsistent labels. Which lifecycle stage should address this issue first?
Problem-solving using AI and AI Development Lifecycle
Medium
A.User interface design
B.Performance reporting
C.Model deployment
D.Data preparation
Correct Answer: Data preparation
Explanation:
Cleaning duplicates and correcting inconsistent labels are data-preparation activities that should occur before reliable model training.
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29A company wants an AI system to identify defective products. What should the team define before selecting an algorithm?
Problem-solving using AI and AI Development Lifecycle
Medium
A.The number of employees using the system
B.The business problem and success criteria
C.The final dashboard color scheme
D.The preferred programming language only
Correct Answer: The business problem and success criteria
Explanation:
Clearly defining the objective and measurable success criteria guides data collection, model selection, and evaluation.
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30A model achieves high accuracy during training but performs poorly on new customer records. What is the most likely problem?
Problem-solving using AI and AI Development Lifecycle
Medium
A.Data encryption
B.Overfitting
C.Underfitting
D.Feature scaling failure in every case
Correct Answer: Overfitting
Explanation:
Overfitting occurs when a model learns training examples too closely and fails to generalize to unseen data.
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31A navigation system must choose among several routes while considering travel time, traffic, and road closures. Which AI problem-solving activity is most relevant?
Problem-solving using AI and AI Development Lifecycle
Medium
A.Removing the need for evaluation
B.Compressing all input into one value
C.Replacing goals with random actions
D.Searching through possible states
Correct Answer: Searching through possible states
Explanation:
Route planning involves exploring possible states or paths and evaluating them against goals such as minimizing travel time.
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32A vacuum-cleaning agent senses dirt, location, and obstacles, then chooses actions to clean rooms efficiently. What makes it an intelligent agent?
Intelligent Agents and Agent Environment
Medium
A.It observes the environment and acts toward a goal
B.It changes the environment without receiving observations
C.It stores data without taking any action
D.It follows a fixed schedule without sensing conditions
Correct Answer: It observes the environment and acts toward a goal
Explanation:
An intelligent agent perceives its environment through sensors and selects actions intended to achieve specified objectives.
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33For an autonomous delivery drone operating in a city, which environmental property makes decision-making especially challenging?
Intelligent Agents and Agent Environment
Medium
A.The environment provides the correct action directly
B.The environment has no uncertainty or obstacles
C.The environment is dynamic and partially observable
D.The environment is completely static and visible
Correct Answer: The environment is dynamic and partially observable
Explanation:
A city changes while the drone operates, and the drone cannot observe every relevant condition, making the environment dynamic and partially observable.
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34A medical diagnosis agent recommends tests and treatments based on symptoms, patient history, and test results. Which component defines what the agent is trying to achieve?
Intelligent Agents and Agent Environment
Medium
A.The performance measure
B.The environment state
C.The sensor
D.The actuator
Correct Answer: The performance measure
Explanation:
The performance measure specifies how success is evaluated, such as diagnostic accuracy, patient safety, or treatment effectiveness.
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35A factory robot detects a worker nearby and slows its movement to reduce the risk of injury. Which AI application is demonstrated?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Medium
A.Automated text summarization
B.Collaborative robot safety
C.Traffic demand forecasting
D.Medical image segmentation
Correct Answer: Collaborative robot safety
Explanation:
The robot uses sensing and intelligent control to operate safely alongside human workers.
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36An AI healthcare system flags patients who may develop a disease, but a physician makes the final decision. What is the main advantage of this arrangement?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Medium
A.It guarantees that every prediction is correct
B.It combines automated pattern detection with professional judgment
C.It removes the need for patient consent
D.It prevents physicians from reviewing the evidence
Correct Answer: It combines automated pattern detection with professional judgment
Explanation:
AI can identify patterns efficiently, while a qualified professional can interpret context, verify results, and make accountable decisions.
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37A manufacturing system predicts when a machine is likely to fail by analyzing vibration and temperature readings. What type of application is this?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Medium
A.Facial recognition
B.Generative design only
C.Manual quality inspection
D.Predictive maintenance
Correct Answer: Predictive maintenance
Explanation:
Predictive maintenance uses sensor data and models to anticipate equipment failures before they occur.
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38A smart-city platform adjusts traffic signals using live vehicle-flow data. Which outcome is the system primarily designed to improve?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Medium
A.Historical preservation
B.Traffic efficiency
C.Manual data entry
D.Personal entertainment
Correct Answer: Traffic efficiency
Explanation:
Adaptive traffic signals use current conditions to reduce congestion, waiting time, and inefficient traffic movement.
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39A hiring model selects candidates from one demographic group at a much higher rate because its training data reflected past biased decisions. Which responsible AI principle is most directly involved?
Ethics in AI and Responsible AI
Medium
A.Fairness
B.Scalability
C.Compression
D.Latency
Correct Answer: Fairness
Explanation:
The model reproduces a discriminatory pattern, so fairness requires examining bias in the data, model, and resulting decisions.
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40Which practice would best improve the accountability of an AI system used to approve insurance claims?
Ethics in AI and Responsible AI
Medium
A.Use personal data without informing affected customers
B.Deploy the system without monitoring after launch
C.Document decisions and assign clear human oversight
D.Hide the model output from all authorized reviewers
Correct Answer: Document decisions and assign clear human oversight
Explanation:
Documentation and defined oversight make it possible to review decisions, identify errors, and determine responsibility.
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41A system uses symbolic rules to diagnose equipment failures, but its rules are manually authored and never updated from operational data. Which limitation most directly distinguishes it from modern learning-based AI?
Introduction to AI and its evolution
Hard
A.It cannot operate without internet connectivity
B.It cannot represent any domain knowledge
C.It cannot improve automatically from new examples
D.It cannot produce explanations for its decisions
Correct Answer: It cannot improve automatically from new examples
Explanation:
A rule-based system can represent knowledge and often provide explanations, but it does not learn from new data unless its rules are manually revised.
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42Why did expert systems experience a decline in practical adoption despite achieving strong performance in narrow domains?
Introduction to AI and its evolution
Hard
A.They required large labeled image datasets
B.They could not perform arithmetic operations reliably
C.They were difficult to maintain as knowledge changed
D.They depended entirely on neural network hardware
Correct Answer: They were difficult to maintain as knowledge changed
Explanation:
Expert systems suffered from the knowledge-acquisition bottleneck and brittle rule maintenance. Updating rules as domains evolved was expensive and often introduced conflicts.
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43A hospital system can diagnose diseases, schedule staff, and optimize treatment plans, but only within healthcare tasks for which it was designed. How should this system be classified?
Types of Artificial Intelligence
Hard
A.Artificial superintelligence
B.Artificial general intelligence
C.Artificial narrow intelligence
D.Self-aware artificial intelligence
Correct Answer: Artificial narrow intelligence
Explanation:
Artificial narrow intelligence performs specific tasks or operates within a restricted domain. Broad competence across unrelated intellectual tasks would be required for general intelligence.
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44Which observation would provide the strongest evidence that a system is not merely reactive but has a limited model-based capability?
Types of Artificial Intelligence
Hard
A.It maps each current input to a predefined response
B.It predicts hidden states after sensor information is lost
C.It selects actions from a fixed lookup table
D.It repeats an action whenever the same signal appears
Correct Answer: It predicts hidden states after sensor information is lost
Explanation:
A model-based system maintains an internal representation of the environment, allowing it to infer or predict unseen states when observations are incomplete.
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45A team cleans customer data, engineers variables, trains a gradient-boosted model, evaluates fairness, and communicates business recommendations. Which description best captures the overall work?
AI vs ML vs Deep Learning vs Data Science
Hard
A.It is software engineering without artificial intelligence
B.It is exclusively deep learning
C.It is a data science workflow containing machine learning
D.It is exclusively artificial intelligence
Correct Answer: It is a data science workflow containing machine learning
Explanation:
Data science includes data preparation, analysis, modeling, evaluation, and communication. Machine learning is one component, while deep learning is not required.
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46Which statement correctly distinguishes deep learning from machine learning?
D.Deep learning typically uses multilayer neural representations
Correct Answer: Deep learning typically uses multilayer neural representations
Explanation:
Deep learning is a subset of machine learning that generally uses neural networks with multiple representation-learning layers. It still requires data and may be difficult to interpret.
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47A fraud model performs well on historical transactions but fails after criminals change their behavior. Which lifecycle activity is most important for detecting and addressing this issue?
Problem-solving using AI and AI Development Lifecycle
Hard
A.Choosing a larger project title
B.Monitoring model drift and retraining criteria
C.Replacing evaluation with stakeholder interviews
D.Removing all validation data before deployment
Correct Answer: Monitoring model drift and retraining criteria
Explanation:
Changing data distributions and behavior create model drift. Continuous monitoring, drift thresholds, and retraining policies are necessary after deployment.
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48A loan approval model is trained using a feature that encodes decisions made by previous loan officers. The model scores highly in validation. What is the primary concern?
Problem-solving using AI and AI Development Lifecycle
Hard
A.The feature guarantees demographic fairness
B.The model will necessarily have too few parameters
C.The feature may create target leakage and reproduce historical bias
D.Validation accuracy proves the feature is causally valid
Correct Answer: The feature may create target leakage and reproduce historical bias
Explanation:
Historical decisions can leak information about the target while embedding prior discrimination. High validation performance does not establish fairness or causal validity.
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49For an autonomous delivery robot, the requirement is to minimize late deliveries while ensuring that collisions remain below a strict safety threshold. Which formulation is most appropriate?
Problem-solving using AI and AI Development Lifecycle
Hard
A.Optimize safety only and ignore delivery time
B.Choose actions randomly to avoid optimization bias
C.Optimize delivery time subject to a collision constraint
D.Optimize delivery time with no safety constraint
Correct Answer: Optimize delivery time subject to a collision constraint
Explanation:
The problem is constrained optimization: delivery performance is optimized while safety is treated as a non-negotiable constraint rather than merely another preference.
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50A model achieves 98% accuracy when 98% of cases are negative, but it detects only 20% of positive cases. Which evaluation change is most justified?
Problem-solving using AI and AI Development Lifecycle
Hard
A.Use sensitivity, specificity, precision, and a confusion matrix
B.Increase the accuracy target without changing evaluation
C.Report accuracy alone because the classes are imbalanced
D.Remove all negative examples before testing
Correct Answer: Use sensitivity, specificity, precision, and a confusion matrix
Explanation:
Accuracy can conceal poor minority-class detection. Class-sensitive measures reveal whether the model meets the actual cost and risk requirements.
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51A warehouse robot receives noisy camera observations, cannot observe every aisle, and must account for actions that affect future locations. Which environment properties apply?
Intelligent Agents and Agent Environment
Hard
A.Fully observable, deterministic, and episodic
B.Fully observable, static, and episodic
C.Partially observable, static, and independent
D.Partially observable, dynamic, and sequential
Correct Answer: Partially observable, dynamic, and sequential
Explanation:
Limited noisy sensing makes the environment partially observable. Moving workers make it dynamic, and current actions influence future states, making it sequential.
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52Why is a rational agent not necessarily guaranteed to choose the action that produces the best eventual outcome?
Intelligent Agents and Agent Environment
Hard
A.Rationality requires the agent to maximize every short-term reward
B.Rational agents must select actions without uncertainty
C.Rational agents never use performance measures
D.Rationality depends on available information and expected outcomes
Correct Answer: Rationality depends on available information and expected outcomes
Explanation:
A rational agent chooses the action expected to maximize performance given its percept history, knowledge, available actions, and uncertainty. Limited information can still lead to poor outcomes.
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53A thermostat turns heating on whenever the current temperature is below a threshold, without storing previous readings or modeling room heat loss. What type of agent is it closest to?
Intelligent Agents and Agent Environment
Hard
A.Simple reflex agent
B.Goal-based planning agent
C.Model-based reflex agent
D.Utility-based learning agent
Correct Answer: Simple reflex agent
Explanation:
The thermostat maps the current percept directly to an action using a condition-action rule. It does not maintain an internal state, plan, or learn.
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54A surgical-assistance robot detects a rare anatomical configuration that differs from its training data. Which design most appropriately reduces safety risk?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Hard
A.Suppress the observation and continue the planned motion
B.Use uncertainty estimation and require human intervention
C.Allow autonomous action with a lower confidence threshold
D.Replace the sensor input with the nearest training example
Correct Answer: Use uncertainty estimation and require human intervention
Explanation:
Out-of-distribution inputs can produce unreliable predictions. Detecting uncertainty and escalating to a qualified human supports safer operation.
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55A predictive-maintenance system reports fewer machine failures after deployment, but operators also began replacing components more frequently. What must be analyzed before concluding that the model improved reliability?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Hard
A.Only the number of dashboard views
B.Only the model's training loss
C.The counterfactual failure rate under comparable maintenance policies
D.The color scheme used for alert messages
Correct Answer: The counterfactual failure rate under comparable maintenance policies
Explanation:
Observed failures are affected by maintenance actions. Comparing outcomes under equivalent policies helps distinguish model impact from increased preventive replacement.
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56A smart-city traffic model reduces average travel time but increases delays in neighborhoods with limited sensor coverage. Which intervention best addresses the identified deployment risk?
Applications of AI in Robotics, Healthcare, Manufacturing and Smart Cities
Hard
A.Discard all neighborhood-level measurements
B.Increase model complexity without reviewing the data
C.Optimize only the citywide average
D.Audit subgroup performance and improve representative sensing
Correct Answer: Audit subgroup performance and improve representative sensing
Explanation:
Aggregate improvement can hide unequal impacts. Subgroup evaluation and better coverage are needed to identify and reduce systematic service disparities.
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57A hiring model has equal overall accuracy for two demographic groups, but its false-negative rate is substantially higher for one group. What does this demonstrate?
Ethics in AI and Responsible AI
Hard
A.The model is automatically free from proxy discrimination
B.Equal accuracy guarantees equal opportunity
C.The difference is irrelevant because precision is unchanged
D.The model may still create unequal error burdens
Correct Answer: The model may still create unequal error burdens
Explanation:
Overall accuracy can mask disparities in specific error types. A higher false-negative rate means qualified candidates in one group may be rejected more often.
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58Which practice most directly improves auditability for a high-impact AI system after it has been deployed?
Ethics in AI and Responsible AI
Hard
A.Maintaining versioned data, models, decisions, and access logs
B.Publishing only the model's average accuracy
C.Allowing undocumented manual overrides
D.Deleting input records immediately after prediction
Correct Answer: Maintaining versioned data, models, decisions, and access logs
Explanation:
Auditability requires reconstructing how a decision was produced. Versioned artifacts and logs support investigation, accountability, and compliance.
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59An AI provider claims that a model is fair because it does not use race as an input. Why is this claim insufficient?
Ethics in AI and Responsible AI
Hard
A.Fairness requires removing every numerical feature
B.Race cannot be measured in any dataset
C.Other variables may act as correlated proxy attributes
D.Omitting race guarantees identical error rates
Correct Answer: Other variables may act as correlated proxy attributes
Explanation:
Location, education, income, or other features may encode information correlated with race. Fairness must be evaluated through outcomes and error patterns, not input omission alone.
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60A language model produces a confident but unsupported citation. Which explanation is most accurate?
Introduction to Generative AI
Hard
A.The model retrieves truth whenever confidence is high
B.The model cannot produce fluent text without a database
D.The model generates likely sequences without guaranteed factual grounding
Correct Answer: The model generates likely sequences without guaranteed factual grounding
Explanation:
Generative language models optimize prediction of plausible token sequences. Fluency and probability do not guarantee that a citation or claim is factually correct.
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