WorksheetsGeneral AI Concepts - Multiple Choice Questions
Total questions: 56
Worksheet time: 28mins
Which of the following best defines Artificial Intelligence (AI)?
Automation of all manual tasks
Study of computations enabling perception, reasoning, and action
Use of robots in factories
Cloud-based automation only
Which term describes AI that performs one task extremely well but lacks general reasoning?
General AI
Strong AI
Narrow AI
Cognitive AI
In the Turing Test, an AI is considered intelligent when:
It passes 100% accuracy
Humans cannot distinguish it from another human
It beats humans in chess
It answers questions faster
Which UAE initiative focuses on open government data to support AI?
Vision 2040
Smart Abu Dhabi
Dubai Pulse
AI Lab Sharjah
What underpins AI models’ accuracy the most?
Hardware cost
Data quality
Marketing budget
Cloud subscription
Which company produces Trainium & Inferentia chips for AI training?
NVIDIA
Apple
Amazon Web Services
The UAE’s Minister of AI, Omar Sultan Al Olama, was appointed under which strategy?
UAE AI Strategy 2031
Vision 2020
Digital 2030
Emirates AI Act
Which AI branch converts structured data into natural language reports?
Speech Recognition
Natural Language Generation
Machine Vision
Predictive Analytics
Which AI type is used in Tesla Autopilot?
Reinforcement Learning
Symbolic AI
Rule-based Inference
Chatbot Reasoning
The EU AI Act classifies “emotion-scanning AI” as:
Minimal risk
High risk
Unacceptable risk
Limited risk
In the “AI Maturity Ladder,” which level ties AI to organizational strategy?
Level 1 – Shiny Object
Level 2 – Confused
Level 4 – Strategic
Level 5 – Smart
Which is not a common challenge of AI implementation?
Messy data
Lack of training
Overnight ROI
Ethical audits
Which AI example aids language preservation?
Seeing AI
Masakhane NLP
Watson Health
Sora 2
“Black-box AI” refers to:
Open-source algorithms
Systems whose decisions can’t be explained
Hardware containers
Cybersecurity tools
UAE’s PDPL (2024 update) focuses on:
AI marketing campaigns
Data privacy and ethics
Financial forecasting
Blockchain only
The human side of AI implementation highlights:
Compute power
Team skills and mindset
Hardware failure
Network latency
“Fairness, Transparency, Accountability” are principles of:
AI Innovation
AI Ethics
Marketing AI
Cognitive Bias
In analytics terminology, “Predictive Analytics” corresponds to:
What happened?
What will happen?
Why it happened?
How to visualize it?
Scenario 1 – Recruitment Bias: A company’s AI screening tool rejects qualified women due to biased training data. Which principle is violated?
Transparency
Fairness
Privacy
Efficiency
The Amazon recruiter tool that favored men illustrates which issue most clearly?
Explainability
Data bias
Human oversight
Data augmentation
“Smart grids and load forecasting” represent AI use in which sector?
Education
Energy
Retail
Healthcare
Scenario 2 – Emotion Recognition in Classrooms: The AI mislabels students as “disengaged.” The main ethical risk is:
Data bias
Open data access
Cloud pricing
Energy usage
Scenario 3 – Predictive Policing: Continuous patrolling in certain areas amplifies bias. Which remedy is most appropriate?
Use bigger datasets
Audit historical data for bias
Collect citizen biometrics
Deploy more cameras
Scenario 4 – AI Medical Chatbot: The hospital’s bot gives dangerous advice. Which is the most ethical solution?
Remove human oversight
Disclose AI limitations and require doctor review
Ignore edge cases
Market as 100% accurate
Scenario 5 – Deepfake Ads: An agency uses AI-generated faces without consent. What is the primary ethical issue?
Bias
Intellectual property and consent
Data storage
Explainability
Scenario 6 – Smart Campus AI: A university adds AI attendance tracking. Students object. Which law applies in the UAE?
EU GDPR
UAE PDPL
COPPA
HIPAA
Scenario 7 – Startup AI Forecasting: A company uses ChatGPT for sales predictions but feeds wrong data. The outcome exemplifies:
Bias reduction
Garbage in → garbage out
Explainable AI
Data ethics
Scenario 8 – HR Analytics: A turnover-prediction tool reveals personal data to managers. The main violation is:
Accountability
Privacy
Transparency
Bias
Scenario 9 – AI in Energy: An industrial AI predicts equipment failures but is fed messy sensor data. The most likely consequence is:
Higher accuracy
Faulty predictions
Lower bias
Reduced cost
Scenario 10 – Education AI App: A teacher uses ChatGPT to grade essays without review. The main risk is:
Improved efficiency
Lack of human oversight
Lower grading time
Better student feedback
Which AI image-generation tool lets users create realistic visuals from text prompts and was featured in the “AI Tools Gone Wild” slide?
Jasper
Midjourney v7
Copilot
Canva Magic Studio
Which OpenAI tool converts text descriptions into full videos, raising ethical debates about realism?
Sora 2
DALL·E 2
Runway Gen-2
Synthesia
Google’s free AI app-building platform highlighted in Week 4 is called:
AppSheet
PartyRock
Vertex AI
Firebase AI
Which AI platform from AWS provides Trainium and Inferentia chips for machine-learning workloads?
Oracle Cloud
Amazon Web Services
Microsoft Azure
G42 Stargate
The Teachable Machine project in the slides was used to demonstrate:
Speech synthesis
Image classification
Chatbot training
Sentiment analysis
Which UAE company was cited for using AI to forecast energy demand and predict equipment failures?
ADNOC
DEWA
Etisalat
G42
The tool used to check plagiarism and smart grading in education examples is powered by:
Jasper
AI Learning Apps
Canva AI
Gemini
Which open-source chatbot was listed among “Popular AI Agent Chatbots” in Week 2?
HuggingChat
Llama 2 Chat
Claude Instant
Bard
Which AI ethics toolkit was mentioned for the UAE context and is available at digitaldubai.ae?
OECD AI Toolkit
Digital Dubai AI Ethics Self-Assessment
IBM WatsonX Governance
McKinsey Ethics Guide
The image-to-video and face-cloning tools HeyGen and Dubverse were used to illustrate which concern?
AI security risk management
AI creativity vs deepfake concerns
Cloud cost optimization
Predictive maintenance
A UAE hospital introduces Doctor Bot to assist in triage. Nurses report faster intake times, but some patients misinterpret its recommendations as final diagnoses. What leadership action best reflects the “Strategic Stage” of AI maturity?
Ignore patient confusion and scale system quickly
Replace nurses fully with Doctor Bot
Integrate training plus clear disclaimers before full rollout
Suspend AI usage entirely
A Dubai clinic notes that Doctor Bot saves physicians time but occasionally misclassifies rare symptoms. Which statement best summarizes this trade-off?
AI always increases accuracy once deployed
Efficiency may rise while clinical risk also increases without oversight
Errors prove AI is unfit for healthcare
Time savings negate any safety concerns
A CEO buys an AI chatbot after seeing it succeed abroad but fails to brief staff or check data quality. What maturity level does this illustrate?
Strategic Stage
Smart Stage
Shiny Object Stage
Organized Stage
Table insight shows most Doctor Bot test users are university graduates. When expanding to rural UAE, what should managers prioritize?
Use the same dataset since it performed well before
Exclude non-graduates to avoid noise
Collect more diverse patient data to reduce bias
Translate interface only into Arabic
A health-tech startup decides to embed Doctor Bot inside its HR wellness app for employee symptom checks. Which Build vs Buy strategy is most appropriate?
Build entirely from open-source models
Some Build, Some Buy — customize existing chatbot frameworks
Mostly Buy — use vendor without customization
Mostly Build — develop new language model from scratch
A clinic’s Doctor Bot provides a wrong triage suggestion leading to delayed care. Under UAE AI Charter guidelines, who holds ethical accountability?
The software vendor alone
The organization and supervising physicians using the AI
The patient for misuse
No one — AI is autonomous
Patients fear that Doctor Bot “hides how it thinks.” Which modern AI technique best addresses this concern?
Reinforcement Learning
Explainable AI (XAI)
Random data augmentation
Unsupervised pre-training
If Doctor Bot were allowed to give final diagnoses without physician review, what ethical risk is most critical?
Copyright infringement
Patient safety and clinical liability
Marketing bias
Server downtime
During testing, Doctor Bot records voice samples to improve accuracy without informing patients. Which ethical principle is violated?
Fairness
Accuracy
Consent and Transparency
Efficiency
A hospital notices Doctor Bot performs poorly for elderly patients. Which intervention best fits ethical mitigation steps?
Ignore outliers
Collect more young user data
Retrain model with age-balanced datasets and bias auditing
Disable AI for older patients
A healthcare network cleans its data and trains staff before launching AI. Which maturity stage is this?
Confused Stage
Shiny Object Stage
Organized Stage
Smart Stage
An energy company wants AI for predictive maintenance but skips small-scale pilots to impress investors. Which trap does this mirror?
Lack of ROI tracking
No clear strategy or pilot testing before rollout
Too many ethics audits
Overtraining the model
An HR team is asked to use AI analytics for turnover prediction but cannot interpret graphs or data sources. Which foundation step is missing?
Bias testing
Hardware upgrade
Data fluency and analytical literacy training
Regulatory approval
An organization has excellent data scientists but lacks domain experts. What risk does this create?
Over-automation
Model duplication
Insights that lack real-world context or business relevance
Faster deployment
After a successful pilot, a hospital forms a cross-functional AI ethics committee to monitor risk and patient feedback. What does this step represent in AI maturity?
Confused Stage
Organized Stage
Smart Stage — human plus AI workflow harmony
Shiny Object Stage
Which example best reflects deepfake risk management linked to tools like HeyGen and Dubverse?
Allow auto-generated patient videos without consent
Require provenance checks and watermarks for synthetic media
Ban all multimedia communications
Prioritize cloud cost cuts over verification
