This unit explores practical UX design patterns for AI-powered interactions, including autocomplete, next-step suggestions, chat-focused information architecture, and plugin-enabled continuous learning. Students will examine data roles, mitigation of AI hallucinations, and produce promptbooks and quick prototype ‘spikes’ that prepare them for integration and evaluation in the final unit.
Learning Objectives
- analyze UX implications, error modes, and acceptance criteria for AI-driven autocomplete and next-step suggestion features and document mitigation strategies
- apply plugin and data-integration principles to design a continuous-learning plan for a specified system, including data flows, feedback loops, and update cadence
- evaluate risks of AI hallucination and other failure modes (‘AI bullshit’) and propose concrete data governance, monitoring, and prompt-engineering controls to reduce harmful outputs
- demonstrate creation of a promptbook and a scoped chat-focused IA spike with test cases and measurable success criteria
Curriculum
- 1 Section
- 13 Lessons
- 30 hours
Expand all sectionsCollapse all sections
- Unit 3 — AI Interaction and Continuous Learning13
- 1.1AI-Driven Autocomplete20 mins
- 1.2Plug-Ins: Integrated Continuous Learning About Your Specific System20 mins
- 1.3Design Idea #420 mins
- 1.4What the Heck Is a Spike?20 mins
- 1.5AI Bullshit20 mins
- 1.6Next-Steps Suggestions20 mins
- 1.7The IA of the AI Is Straightforward, Focused on Chat20 mins
- 1.8Design Idea #520 mins
- 1.9What Is the Role of Data?20 mins
- 1.10Final Words20 mins
- 1.11Final Words20 mins
- 1.12Promptbooks: No Need to Twist into Pretzels to Write Prompts20 mins
- 1.13But Wait, Did You Catch That?20 mins
Instructor
Free
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