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WorksheetsPLANMalaysia AI Training CitySage Day 1
Total questions: 10
Worksheet time: 5mins
In the DIKW hierarchy, what distinguishes Knowledge from Information?
Knowledge requires ethical reflection.
Knowledge adds context, experience, and interpretation to information.
Information is always subjective, while knowledge is always objective.
Knowledge is only relevant when stored in databases.
Which best describes the transition from a Smart City to a Wise City?
From data-driven decision-making to experience-driven intuition.
From optimizing efficiency to integrating ethical, cultural, and human values
From using AI models to replacing humans with automation.
From improving infrastructure to digitizing all government services.
Which of the following is the greatest risk when deploying AI in urban planning?
High computational costs
Biased datasets leading to inequitable decisions
Lack of WiFi in rural areas
Too much public participation slowing projects
According to the Personal Data Protection Act (PDPA), urban AI systems must…
Prioritize algorithmic accuracy above all.
Ensure consent, transparency, and limited data retention.
Only use publicly available data.
Encrypt all data but exclude humans from review.
The equation for Urban Wisdom can be simplified as:
Wisdom = Knowledge + Experience + Curiosity.
What does Curiosity represent in this formula?
The computational speed of AI models.
The human drive to ask new questions and test assumptions.
The automation of workflows.
The ability to reduce uncertainty through big data.
Which AI method is most relevant for combining GIS data with real-time policy simulation?
Retrieval-Augmented Generation (RAG)
Reinforcement Learning
Neural Style Transfer
Generative Adversarial Networks (GANs)
In Responsible AI, the principle of human-in-the-loop is primarily intended to…
Speed up model training.
Provide oversight, accountability, and ethical judgment.
Reduce the need for regulations.
Lower costs of automation
Which is the strongest enabler for AI adoption in urban governance?
High-performing hardware (GPUs)
Clear national policy and ethical guidelines
Large volumes of unstructured data
Private sector branding initiatives
What is the main conceptual weakness of Smart City projects without ethical grounding?
They lack IoT sensors
They risk becoming technologically efficient but socially unjust.
They cannot integrate with cloud services.
They do not comply with ISO 9001 standards.
In AI roadmap planning, what does a quick win usually look like?
A fully autonomous AI planning system.
A low-cost pilot project showing measurable impact in <6 months.
A complete smart grid transformation.
A long-term research collaboration with multiple universities.
