The 4D Framework

The 4D Framework for AI Fluency

In this course, we're trying to build lasting AI fluency. We want to give you the tools to use AI effectively, efficiently, ethically, and safely, no matter what challenges you might face. In this video, we'll take a quick look at the 4D framework: four interconnected skills that, when combined, transform how you work with AI.

To help you apply this framework, we'll consider two modes of interaction with AI:

1. The first is at a higher level: deciding when to use AI at all. We call this the Delegation-Diligence loop.
2. The second is deciding how to engage with AI effectively on a day-to-day basis. We call this the Description-Discernment loop.

Delegation and Diligence

First is Delegation: deciding what work should be done by humans, what should be done by AI, and how to distribute tasks between them. It has three parts:

• Problem awareness: This means clearly understanding your goals and the nature of the work before involving AI. Before writing a donor thank-you letter, ask: Is this just acknowledging the gift where boilerplate language is more acceptable, or are you trying to nurture a donor relationship where the human touch is essential?
• Platform awareness: This means understanding the capabilities and limitations of different AI systems. For example, if you're working with sensitive donor data, you'd want to consider the privacy protections of your tool.
• Task delegation: This is how you thoughtfully distribute work between humans and AI to leverage the strengths of each.

We couple this with Diligence: taking responsibility for how you use AI.

• Creation diligence: This means being thoughtful about which AI systems you use and how you interact with them. For example, maybe you use AI tools to write a report, but you were intentional about which parts of that report it's working on.
• Transparency diligence: This means being honest about AI's role in your work with everyone who needs to know. Your board, funders, and beneficiaries deserve to know when AI has been involved and how.
• Deployment diligence: This means taking responsibility for verifying and vouching for the outputs you use or share. You verify every statement and confirm that any final document or artifact genuinely represents your mission. 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 be matched by ongoing responsibility for how you use it. Your diligent practices inform smarter delegation decisions over time.

Description and Discernment

When you opt to use AI, how can you ensure you're maintaining agency? That's where the Description-Discernment loop comes in. This guides the day-to-day interactions with AI.

Description is how we refer to communicating effectively with AI systems. This goes beyond writing good prompts to building cognitive environments in which you work with AI:

• Product description: Defining what you want in terms of outputs, format, audience, and style. Instead of "write a social media post about our food pantry," product description teaches us to try something more specific.
• Process description: Defining how the AI approaches your request. Think of it like giving instructions to a junior colleague or sharing the correct order of operations for a given task.
• Performance description: Defining the AI's behavior during your collaboration. Do you need critical feedback, a "hype man," or a skeptical audience? Just ask for it.

Discernment, the final component of our framework, asks you to thoughtfully and critically evaluate the product, process, and performance of your AI collaborator:

• Product discernment: Evaluating the quality of what AI produces. Are these statistics accurate? Does this language reflect how our beneficiaries describe their experiences?
• Process discernment: Evaluating how the AI arrived at its output. Did it consider all relevant factors? Did it make assumptions about your community that don't hold true?
• Performance discernment: Evaluating how the AI behaves during your interaction. Is the AI giving you useful suggestions or just generating content?

Importantly, discernment doesn't just mean accepting or rejecting AI outputs. It involves iteration to get where you want to go. 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. It's sort of like working with a human collaborator; you build understanding through conversation.

Putting the 4Ds into Practice

The four Ds come alive when you use them together. For example, when creating an impact report:

• Use Delegation to decide what AI handles versus what you provide.
• Use strong Description to guide the AI's work.
• Apply Discernment to evaluate the results.
• Practice Diligence throughout by choosing appropriate tools and taking responsibility for accuracy.

This framework isn't about making AI do your work for you. It's about making you more effective at the work that matters—work that requires human judgment, creativity, and a deep understanding of your community's needs.

Throughout this course, you'll apply these competencies to a few nonprofit-specific challenges: writing grants, analyzing data, automating tasks, and integrating AI sustainably into your organization. The skills you'll take away will serve you as you work with AI into the future.