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7.2. Quick Reference Decision Guides
🎯 Quick Reference: Responsible AI Principles
| Principle | One-Line Tell |
|---|---|
| Fairness | Equitable outcomes across groups (watch for proxy bias) |
| Reliability & Safety | Predictable, safe behavior — including on unexpected inputs |
| Privacy & Security | Protect personal data (privacy) + defend the system (security) |
| Inclusiveness | Works for people of all abilities/backgrounds (access) |
| Transparency | People understand how/when AI is used |
| Accountability | Humans remain answerable for the system |
Remember: Transparency = understandable; Accountability = answerable. Fairness = outcomes; Inclusiveness = access.
🎯 Quick Reference: Match the Workload
| Scenario Cue | Workload |
|---|---|
| "Is this review positive?" | Sentiment analysis |
| "Find the company names" | Entity detection |
| "Give me the gist" | Summarization |
| "Transcribe this audio" | Speech recognition (speech-to-text) |
| "Read this aloud" | Speech synthesis (text-to-speech) |
| "What's in this photo?" | Computer vision / multimodal understanding |
| "Where are the objects?" | Object detection |
| "Create an image of..." | Image generation |
| "Pull the total off this invoice" | Information extraction (Content Understanding) |
| "Check inventory and reorder" | Agentic AI |
Remember: Classify by input → output. Understanding reads media; generation creates it.
🎯 Quick Reference: Model Configuration
| Setting | Effect | For Factual Tasks |
|---|---|---|
| Temperature | Randomness/creativity | Low |
| Top-p | Candidate token pool | Low |
| Max tokens | Length cap (and cost bound) | Set to need |
| System prompt | Persistent rules/role | Where durable rules go |
| Grounding | Supply trusted facts | Main defense vs. hallucination |
Remember: Temperature changes style, not intelligence. Bigger model ≠ better choice.
🎯 Quick Reference: Foundry Build Patterns
| Goal | Key Moves |
|---|---|
| Chat client | AIProjectClient(endpoint, credential) → get_openai_client() → responses.create(...) |
| Agent client | Same + a conversation (memory) + an agent_reference (route through agent) |
| Extraction app | Choose analyzer (prebuilt > custom) → run on content → use structured fields |
| Extract-then-generate | Content Understanding fields → feed to model (grounding) |
Remember: Deploy a model before calling it; code references the deployment name.
Written byAlvin Varughese
Founder•18 professional certifications