4D Framework for AI Fluency — Step-by-Step Guide & Transcript

[00:10] That means giving you the tools to use AI efficiently, ethically, and safely, face. In this video, we'll walk through the 4D framework, four interconnected competencies that, when combined, transform how you work with AI. To help

[00:26] you apply this framework, we'll look at two modes of interaction with AI. The first mode is likely the one you're familiar with, how to engage with AI effectively on a day-to-day basis. This is the inner loop of description and

[00:40] AI to help you with, and then you discern if it meets your expectations. This is a critically important skill set when learning AI, but it's not everything that happens within your interactions with AI, there's also an

[00:55] outer loop of delegation and diligence. This is everything that happens in your workplace, community, and life around the use of AI. Should you be using AI at all? And if you do, what are your ethical responsibilities to ensure

[01:08] you're proceeding intentionally and responsibly? We'll be doing a brief overview of all of this today, but if you'd like a deeper understanding, check out the AI Fluency Framework and Foundations course on Anthropic Academy.

[01:21] Let's begin with a close look at the inner loop of description and discernment. Again, this happens during your day-to-day interactions with AI. Description just means communicating effectively with AI systems. This goes

[01:36] with defining what you want, your outputs, format, audience, and style. Instead of write a summary of this report, try getting specific. Summarize executive audience, focusing on the three highest impact findings in under

[01:52] 300 words. But you can also define how it like giving instructions to a collaborator, specifying the steps, the order of operations, or the reasoning approach you want the AI to follow. And

[02:06] you can shape the AI's behavior during your collaboration as well. Do you need a critical reviewer who pushes back on weak arguments, a brainstorming partner who builds on every idea, a fact-checker who flags uncertainty? You can ask for

[02:20] In our research, we found that description skills are the ones people pick up most naturally. Things like specifying what you want, giving examples, and refining your requests. Most people are already doing some

[02:33] version of these, and that's a great starting point. As you iterate and get more comfortable and effective at description. Discernment, the companion to description, asks you to thoughtfully

[02:46] and critically evaluate your AI collaborator. Start with the output itself. Are these statistics accurate? Does this language reflect how your audience actually talks about this topic? Then look at how AI got there.

[02:59] Did it consider all relevant factors? Importantly, discernment doesn't just mean accepting or rejecting AI outputs. It involves iteration to get where you And while most people describe what they want fairly naturally, discernment is

[03:15] much rarer. In our research, skills like questioning AI's reasoning, checking facts, and identifying missing context were among the least common behaviors we observed. And that's where there's room to grow. It can be an easy step to miss,

[03:28] but it's critically important. It's what drives true AI collaboration. That's why description and discernment work together in a loop. You describe what you need, evaluate what you get, and then refine your description based on

[03:43] that evaluation. It's like working with a human teammate. You build a shared understanding through conversation. Using AI well in day-to-day interactions is only one piece of the puzzle. It's critical to understand all the ethical

[03:56] and social implications of AI use in your context. This is where the delegation diligence loop comes in. Delegation is deciding what work should be done by humans, what work should be done by AI, and how to distribute tasks

[04:09] between them. Good delegation starts with understanding the work itself. Before drafting an email, ask yourself, is this a routine status update where AI sensitive negotiation where tone and nuance need to come directly from you?

[04:23] You need to understand your tools as well. If you're working with want to consider the privacy and security features of the AI system you're using. When you understand both the work and the tools, you can

[04:36] thoughtfully split tasks to leverage the strengths of each. We pair delegation with diligence, taking responsibility for how you use AI. That means being thoughtful about which AI systems you use and how you interact

[04:51] with them. Maybe you use AI to draft a project proposal, but you're intentional about which sections it works on and which require your own expertise. It means being honest about AI's role in your work with the people who need to

[05:04] Your colleagues and stakeholders deserve to understand when and how AI has been responsibility for verifying and vouching for the outputs you use or share. You check every claim, confirm accuracy, and make sure any final

[05:20] deliverable generally represents your goals and standards. You're always accountable for the final result. Delegation and diligence work together as a loop. The thoughtful choices you make about what to delegate to AI must

[05:33] be matched by ongoing responsibility for how you use it. And your diligent practices inform smarter delegation decisions over time. The four D's come alive when you use them together. Writing a strategic plan?

[05:48] Use delegation to decide what AI handles versus what you bring yourself. Use strong description to guide the AI's work. Apply discernment to evaluate the results, and practice diligence throughout by choosing appropriate

[06:00] tools, being transparent about AI's role, and taking responsibility for accuracy. This framework is about making you more effective at the work that judgment, creativity, and deep understanding of your context.

[06:13] Throughout this course, you'll apply these competencies to real challenges, drafting communications, analyzing complex information, automating routine workflows. The skills you take away will serve you

[06:27] as AI continues to evolve. You can learn Academy, and we'll continue to share our research on this topic on Anthropic's research on this topic on Anthropic's blog.