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The 4D framework

AI Fluency includes 4 core competences (4D): Delegation, Description, Discernment, Diligence.

These competences aren't tied to specific AI tools or techniques that might become outdated. They're fundamental skills that will help you with this technology.

Delegation​

Decide what you need to accomplish, what work to do with AI, what work to do yourself.

Example. Imagine you work on a research project. AI might review lengthy documents and data. You might discuss with AI implications and findings. Yet reserve the final analysis and conclusion for yourself.

How to delegate effectively:

  • Understand your goal and the problem you need to solve.
  • Know what AI systems can and can't do well.
  • Decide how to divide the work between you and the AI.

Description​

Communicate clearly with AI.

Examples

  • Creating a logo. "Make me a logo" is too vague. Describing your company's values, target audience, preferred colors, style references, and so on is a far better approach.
  • Tutor. Imagine using AI as a tutor. You might make 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"

What needs to be described:

  • What you want the final output to be.
  • How you want the AI to approach the task.
  • The context and the information that the AI might need to best work with you on this task.
  • How you want the AI to behave. Define the tone and style of the interaction.

Discernment​

Evaluate AI outputs and behavior.

Examples:

  • Are the facts accurate?
  • Does the reasoning make sense?
  • Do the recommendations align with your brand values and audience?
  • Does this output actually help you move forward?

What needs to be evaluated:

  • Is the output useful and correct?
  • Is the AI taking the right approach?
  • Is the AI behaving as desired?

Diligence​

Use AI responsibly.

Example. If you're using AI to help write job descriptions or review applications, how do you ensure fairness and controlling for potential biases?

What to keep in mind:

  • Ensure accuracy and take responsibility
  • Honesty and transparency
  • Ethical use and critical awareness