Introduction to Artificial Intelligence

AIE · 40 questions

• A city clerk compares a human caseworker deciding hardship fee waivers with an AI assistant that only applies written policy rules. What difference should the clerk highlight?
• 311 supervisors decide which ticket-triaging steps stay with humans and which an AI can draft for review. Which collaboration pattern fits best?
• Public-health nurses use AI to summarize call notes but keep clinical follow-up decisions themselves. How should leadership frame the AI’s role?
• Permitting staff notice that AI cannot invent a new variance rationale the way an experienced planner can. What limitation of current AI does this illustrate?
• Transit ops contrasts a human dispatcher adapting to a sudden flood detour with an AI ETA model trained only on normal days. What does this contrast emphasize?
• Library staff debate whether recommending books with AI is “intelligence” or pattern matching over catalog metadata. At an essentials level, what should they conclude?
• Courts IT trains clerks to treat AI docket summaries as drafts needing human verification before filing. Which mindset for human–AI collaboration does this reinforce?
• Water utility managers map tasks that need on-site sensory common sense versus tasks AI can optimize from sensor logs. What principle are they applying?
• Parks department explains to volunteers that AI chat answers are not the same as a ranger’s lived trail knowledge. What distinction is being taught?
• Housing authority caseworkers keep final eligibility calls while AI pre-fills forms from prior applications. Which collaboration pattern does this describe?
• A city open-data team explains that a pothole predictor needs data, an algorithm, and a trained model—not just a dashboard. What foundations of an AI system are they naming?
• A county assessor notes garbage-in garbage-out when parcel photos are mislabeled before model training. What foundation problem is being illustrated?
• Emergency management separates the flood-alert algorithm from the model weights learned from historical incidents. What distinction are they making?
• 311 product owners learn that without resident ticket text as data, no algorithm can triage language requests. Why is data a prerequisite foundation?
• Transit planners treat bus GPS traces as the data layer feeding a delay-prediction model. What relationship does this highlight?
• Public works maps the pipeline from raw work-order logs to cleaned features to a ranking model for crew dispatch. Which foundation story does this end-to-end view tell?
• A clerk’s office realizes a form-filling tool that only uses if-then macros is automation, not a learned model. What distinction should staff take away?
• An adult-education center teaching civic staff shows that changing the algorithm can change how the same enrollment data is scored. What role of algorithms does this demonstrate?
• A utilities CIO briefs council that models are specific artifacts that expire when city consumption patterns shift. What should council understand about models?
• A city attorney asks which foundation—data, algorithm, or model—failed when a grant-matcher recommended ineligible programs. What diagnostic habit does this encourage?
• A municipal IT timeline workshop places early expert systems for tax codes before modern LLM resident chatbots. What evolution milestone idea does this convey?
• A library archives exhibit contrasts rule-based catalog helpers of the past with today’s generative catalog assistants. What shift is the exhibit highlighting?
• County training covers AI winters so staff do not expect uninterrupted hype cycles for budget asks. What lesson should managers take?
• A transit museum talk links early pathfinding and routing research to today’s bus trip-planning apps. What connection should listeners take away?
• Public-health historians note when machine learning entered outbreak surveillance versus older statistical dashboards. What milestone contrast are they drawing?
• A city innovation office maps the rise of deep learning to when camera-based parking occupancy pilots became feasible. What milestone link should staff emphasize?
• A courts modernization brief places transformer-based language models as the recent milestone behind clerk drafting tools. What should clerks understand from that placement?
• A water utility contrasts SCADA threshold alarms with later anomaly-learning models on meter streams. What evolution is being illustrated?
• Parks GIS staff recount when computer vision matured enough to count park visitors from camera feeds under ethical review. What milestone readiness are they describing?
• 311 leadership places chatbot eras as FAQ keyword bots, then intent classifiers, then generative assistants grounded on policy PDFs. What lesson do those generational milestones teach?
• A city strategy office explores multimodal AI that reads permit drawings and text instructions together. What future direction does this represent?
• Emergency management pilots interest in agentic assistants that propose multi-step shelter opening checklists with human approval. What advancement pattern should leaders stress?
• A transit authority evaluates smaller on-device models for offline station kiosks versus cloud LLMs. What future direction is under review?
• An open-data team watches explainable AI research so residents can see why a grant-scoring model ranked applications. What future direction are they prioritizing?
• A housing authority tracks retrieval-augmented generation so lease FAQs cite the correct policy sections. What advancement does RAG represent for civic Q&A?
• A clerk’s office monitors deepfake risk as a future challenge for verifying public meeting video authenticity. What direction of concern is this?
• Public works forecasts digital twins of storm drains that combine sensors and predictive models. What advanced direction is that concept describing at a literacy level?
• A library consortium explores AI that translates service brochures into multiple community languages with human review. What future application direction is this?
• A city CISO tracks AI-assisted defensive monitoring as a near-term direction for municipal SOC awareness. What literacy point should staff take away?
• A council briefing asks how human-in-the-loop will remain required even as municipal AI autonomy increases. What future collaboration norm should the briefing affirm?