PLANMalaysia AI Training CitySage Day 1

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.