FIT3206 Conversation for artificial intelligence

When you finish this unit, you should be able to:

1. 1

   Diagnose and resolve complex failure modes in conversational AI (e.g., hallucinations, retrieval errors, brittleness under distribution shift, and unsafe outputs) by applying systematic error analysis and selecting justified mitigations aligned to domain risk and constraints;

2. 2

   Select, apply and justify methods and tools for building, evaluating and improving conversational AI systems, including embeddings, retrieval workflows, prompting strategies, adapters and guardrails to produce robust, auditable and context‑appropriate solutions;

3. 3

   Design and implement a domain-grounded conversational AI system by specifying user goals, domain constraints, interaction flows, and system components (e.g., retrieval augmentation, tools, and transparency mechanisms) that support reliable use in context;

4. 4

   Construct and execute evaluation workflows for conversational and generative systems using task-appropriate measures (e.g., quality, robustness, latency/cost, and auditability) and produce reproducible evidence to inform iteration and release decisions;

5. 5

   Assess and address responsible deployment requirements for conversational AI, including bias, safety, privacy-aware handling of sensitive content, and stakeholder-appropriate disclosure and monitoring practices that support accountability and trust.