Lesson 2A: Why do we need AI Fluency? | AI Fluency: Framework & Foundations Course

Main ideas / lessons

• AI fluency goes beyond having access to AI. People may have powerful AI assistants, but that doesn’t automatically mean they know how to use them effectively or responsibly.

• AI fluency is a mindset and skill set that supports effective, efficient, ethical, and safe interaction with AI—so users can maximize value from AI while protecting privacy and security.

• AI fluency is not about memorizing prompt tricks or being only a technical expert. It’s about building adaptive practical skills, knowledge, insights, and values that evolve as AI changes.

• Three primary modes of engaging with AI explain how people use AI and why fluency requires more than prompt engineering.

• Different engagement modes are suited to different tasks. They are not mutually exclusive; users can combine modes within one project.

• When AI acts like more than a tool (partner/medium/co-creator), users need new competencies, described as a framework (the video signals four key competence areas, though details aren’t included in the subtitles shown).

Concepts: the three ways people engage with AI

1. Automation

• What it is: AI completes a specific task based on user instructions.
• Example tasks: summarizing a document, drafting an email, creating an image, planning a trip itinerary.
• When it works best: when the user has a clear outcome in mind.
• When it can be challenging: when the user doesn’t yet know what they’re looking for.

2. Augmentation

• What it is: user and AI collaborate; the AI acts as a creative thinking and problem-solving partner rather than a task executor.
• Example scenarios:
  • developing a story character by exploring ideas, backstory, dialogue, and refinement through conversation
  • working through a difficult architectural/app problem
  • formulating thoughts on a complex research topic
• When it works best: when solutions aren’t straightforward and the user needs space to explore and experiment.
• Key distinction: AI helps the user do their work better—it doesn’t simply do it for them.

3. Agency

• What it is: AI works independently on the user’s behalf.
• Example tasks: categorizing incoming emails by topic/urgency and starting drafts for the most urgent ones; creating dynamic interactive website experiences; powering interactive game characters.
• Core idea: instead of specifying exact actions, the user sets knowledge and behavior patterns.
• Analogy: less like giving the AI step-by-step commands (script writing) and more like directing a vision (director role).

Framework positioning (what the video sets up)

• The AI fluency framework is presented as the way to build competence beyond prompts.
• Core definition of fluency: interacting with AI in ways that are effective, efficient, ethical, and safe, protecting privacy and security of self and others.
• The video claims four key areas of competence will be explored later, but only the intro line appears in the subtitles excerpt.

Speakers / sources featured

• No individual speakers or specific external sources are mentioned in the provided subtitles excerpt.