Module 5Lesson 12 of 13·20 min

A Closer Look at Diligence

Explore the Diligence competency — the ethical dimension of AI fluency. Learn about Creation Diligence, Transparency Diligence, and Deployment Diligence to ensure your AI collaborations are responsible and trustworthy.

The Ethical Dimension of AI Fluency

Delegation, Description, and Discernment primarily focus on making your AI collaborations effective and efficient. Diligence adds the equally critical ethical and safety dimension. It is about taking responsibility for how you use AI, being honest about AI involvement in your work, and ensuring the outputs you share meet your standards of quality and integrity.

Diligence is not about following a rigid set of rules — contexts differ, and expectations vary across academic, professional, and personal settings. It is about developing the judgment to make thoughtful decisions about responsible AI use in whatever context you operate.

Three Components of Diligence

1

Creation Diligence — Thoughtful Tool Choices

Be intentional about which AI systems you use and how you engage with them. Consider the data privacy implications of what you share. Understand the terms of service and data handling practices. Choose tools appropriate for the sensitivity of your work. Not every AI system is suitable for every task, and sharing sensitive information with the wrong tool can have real consequences.

2

Transparency Diligence — Honest Communication

Be open about AI involvement in your work with everyone who needs to know. Different contexts have different expectations — academic institutions may require detailed disclosure, professional settings may have their own AI use policies, and personal projects may need less formal acknowledgment. The key is understanding what your context requires and meeting or exceeding those expectations.

3

Deployment Diligence — Owning the Output

When you share AI-assisted work with others, you are vouching for its quality and accuracy. This means taking the time to verify key claims, check for errors, ensure the output represents your understanding, and accept responsibility for the final product regardless of how much AI contributed. Your name on the work means your standards should be met.

Creating a Diligence Statement

A diligence statement is a transparent acknowledgment of AI involvement in your work, combined with your commitment to responsibility for the final output. While not always required, creating one is good practice — it forces you to reflect on how AI contributed and what verification steps you took.

Example Diligence Statement

"In creating this report, I collaborated with Claude AI to assist with initial research, data synthesis, and draft structuring. I reviewed and verified all AI-generated content and claims for accuracy. The final output reflects my expertise, judgment, and intended meaning. I maintain full responsibility for the content, its accuracy, and its presentation."

Diligence Across Different Contexts

How Diligence Expectations Vary

Academic Settings

  • •Institutions often have specific AI use policies that must be followed
  • •Detailed disclosure of AI involvement may be required for assignments
  • •Verification standards are typically higher for academic work
  • •Using AI in ways that violate academic integrity policies can have serious consequences

Professional Settings

  • •Many organizations are developing AI use policies — familiarize yourself with yours
  • •Client-facing work may require disclosure of AI assistance
  • •Data privacy and confidentiality obligations apply to what you share with AI
  • •Industry regulations may impose additional requirements

Personal Projects

  • •Disclosure expectations are generally less formal
  • •Focus on personal standards of quality and honesty
  • •Consider how your audience would feel if they knew AI was involved
  • •Use it as practice for developing your Diligence habits

Key Takeaways

  • 01Diligence adds the ethical dimension to your AI fluency — responsibility, transparency, and accountability.
  • 02Creation Diligence: Be thoughtful about which AI tools you use and what data you share.
  • 03Transparency Diligence: Be honest about AI involvement with everyone who needs to know.
  • 04Deployment Diligence: Take ownership of AI-assisted outputs — your name means your standards.
  • 05Different contexts have different expectations — understand and meet them.
  • 06Diligence statements are a practical tool for reflecting on and communicating your AI collaboration process.