Lesson 2B: The 4D Framework | AI Fluency: Framework & Foundations Course

Hi, my name is Rick Dacon from the Ringling College of Art and Design. Now

that we've explored what AI fluency means and the different ways we interact with AI, let's dive into the core competencies that help us navigate AI collaboration effectively, efficiently

ethically, and safely.

No matter how you're working with AI whether through automation augmentation, or agency, there are four essential competencies that make all the

difference. We call them the four Ds:

difference. We call them the four Ds: delegation description discernment and diligence. First is delegation

and diligence. First is delegation which focuses on the big picture. What are you trying to

picture. What are you trying to accomplish? What kinds of work are

accomplish? What kinds of work are involved? What work should you handle

involved? What work should you handle yourself? And where might AI be helpful?

yourself? And where might AI be helpful?

Think about a research project you're working on. You might decide to have

working on. You might decide to have your AI assistant review lengthy documents and data, then engage in a thoughtful discussion about the implications and findings, but reserve the critical analysis and final

conclusions for yourself. To delegate effectively, you

yourself. To delegate effectively, you need to understand your goal and the problem you're solving. Recognize what

AI can and can't do well. And lastly

thoughtfully divide the work between you and the AI. Delegation isn't just about

AI. Delegation isn't just about offloading tasks. It's about having a

offloading tasks. It's about having a clear vision and strategically choosing how AI fits into your process. This

thoughtful approach is essential for both effective and efficient AI collaboration. Next comes description

collaboration. Next comes description which focuses on clear communication with AI. Consider the difference between

with AI. Consider the difference between vaguely stating, "Make me a logo."

versus describing your company's values target audience, preferred colors, style references, and so on. Or if you're using an AI as a tutor, you might take the extra step to specify, "Don't tell

me the answer, just help me work through this problem step by step so I can better understand the concept."

Description goes beyond just writing prompts. It's about having detailed

prompts. It's about having detailed contextrich conversations that establish what you're hoping to achieve in the format of the output, how you want the

AI to approach the task, the context and information that the AI might need to best work with you on this task, and the tone and style of interaction.

Effective description means articulating your needs and vision in a way that sets up both you and the AI for greatest collaborative success. The third D is discernment

success. The third D is discernment which involves thoughtfully evaluating what AI gives you. Let's say you've asked an AI assistant to suggest a

marketing strategy. Your discernment

marketing strategy. Your discernment comes into play as you assess, are the facts accurate? Does the reasoning make

facts accurate? Does the reasoning make sense? Do the recommendations align with

sense? Do the recommendations align with your brand values and audience? And most

importantly, does this output actually help you move forward? Discernment draws

upon your own expertise in a domain and requires developing the judgment and critical insight to separate what's useful from what's not and to recognize when AI outputs need refinement or

should be set aside entirely. Most of

our interactions with AI involve small loops of description and discernment describing what we need, evaluating what we get, refining our request, and so on.

We'll explore this more deeply later in the course. Finally, there's diligence

the course. Finally, there's diligence which focuses on responsible AI interactions.

For example, if you are using AI to help write job descriptions or review applications, how are you ensuring fairness and controlling for potential biases? When making important decisions

biases? When making important decisions with AI assistance, how are you verifying the accuracy of the information presented to you? Are you

protecting sensitive data? Have you

considered how to be transparent about the involvement of AI? Are you willing to be accountable for the AI assisted work you have done?

Diligence means taking ownership of your AI assisted work and being willing to stand behind final products created using AI. Diligence is critical for safe

using AI. Diligence is critical for safe and ethical AI collaboration. To recap, AI fluency

collaboration. To recap, AI fluency means developing practical skills knowledge, insights, and values that help you use AI effectively efficiently, ethically, and safely. AI

fluency includes four key competencies. Delegation to decide when

competencies. Delegation to decide when and how to use AI, description to communicate clearly with AI, discernment to evaluate AI outputs, and diligence to

use AI responsibly. What makes these competencies so valuable is that they aren't tied to specific AI tools or techniques that might become outdated.

Instead, they're fundamental skills that will help you adapt and grow alongside this rapidly evolving technology.