Quality and Ethics

The Question Behind the Question

When instructional designers ask "Can I use AI?" what they're really asking is: "Can I use AI without compromising my professional standards or ethics?"

The answer is yes—but only if you approach AI with the same professional responsibility you bring to any other tool in your workflow.

Quality Standards Don't Change

Whether content is created by you typing every word or by you directing AI and refining the output, the quality bar remains the same:

• Pedagogically sound — Learning objectives aligned with assessments, appropriate scaffolding, evidence-based strategies
• Accurate — Facts verified, examples authentic, procedures correct
• Accessible — WCAG compliant, inclusive language, multiple modalities
• Engaging — Relevant to learners, appropriately challenging, maintains interest
• Aligned with brand/culture — Matches organizational voice, values, and standards

Your Ethical Responsibilities

1. Accuracy and Fact-Checking

AI confidently generates plausible-sounding content that can be completely wrong. You are responsible for verifying:

• Statistics and research citations
• Technical procedures and processes
• Legal or compliance information
• Historical facts and timelines
• Current events or recent developments

Never publish AI-generated content about critical topics (safety, compliance, health, legal) without expert review.

2. Bias and Inclusivity

AI inherits biases from its training data. You must review for:

• Stereotypical examples or scenarios
• Exclusionary language or assumptions
• Cultural insensitivity
• Accessibility barriers
• Representation gaps (who's visible? who's missing?)

3. Attribution and Transparency

Ethical practices around disclosure:

• To learners: Generally not required to disclose AI use (like you don't disclose using spell-check). Exception: if your organization has a specific policy.
• To clients/stakeholders: Be transparent if asked. Many IDs include "AI-assisted content development" in project documentation.
• For images: Some contexts require disclosure of AI-generated images (particularly in academic or research settings).
• For voices: Disclose when using AI-generated narration, especially if mimicking a real person's voice.

4. Copyright and Intellectual Property

Current best practices:

• AI-generated text: Generally considered your intellectual property if you created the prompts and made substantive edits
• AI-generated images: Copyright status varies by tool and jurisdiction. Adobe Firefly offers clearest commercial use rights.
• Training data concerns: Avoid using AI to replicate copyrighted styles or specific creators' work
• Client projects: Clarify ownership and AI usage rights in contracts

Data Privacy and Security

When using AI tools, be mindful of what you're sharing:

• Never input: Confidential business information, personal data (names, emails, health info), proprietary processes, or trade secrets
• Be cautious with: Client names, specific organizational details, sensitive content
• Use generic examples: "A healthcare organization" instead of "Kaiser Permanente," "an employee" instead of real names

Check your organization's AI usage policy. Many companies have guidelines about what can and cannot be shared with AI tools.

Quality Assurance Checklist

Before publishing AI-assisted content, verify:

1. Accuracy — Have I fact-checked critical information?
2. Alignment — Do objectives, content, and assessments align?
3. Appropriateness — Is this suitable for my specific audience?
4. Inclusivity — Have I checked for bias and exclusionary language?
5. Accessibility — Does this meet WCAG standards?
6. Brand/Voice — Does this sound like our organization?
7. Engagement — Would learners find this relevant and interesting?
8. Completeness — Are there gaps or logical leaps?

This is the same checklist you'd use for manually created content. AI doesn't change the standards—just the creation process.

When to Avoid AI Entirely

Some situations call for purely human-created content:

• Highly sensitive topics — Trauma, grief, discrimination, serious health conditions
• Culturally specific content — When authenticity requires lived experience
• Legal/compliance courses — Where errors could have serious consequences (though AI can assist with drafts under expert review)
• Personal stories/testimonials — These should come from real people
• When policy prohibits it — Some organizations or clients explicitly ban AI use

The Bigger Picture

The instructional design profession has absorbed new tools before—authoring tools, LMS platforms, video editing software. AI is another tool in the toolkit, more powerful than most, but still just a tool.

Your value as an instructional designer doesn't come from typing every word yourself. It comes from:

• Understanding how people learn
• Designing effective learning experiences
• Making strategic instructional decisions
• Ensuring quality and appropriateness
• Navigating organizational dynamics
• Maintaining ethical and professional standards

AI can help with execution. It can't replace your expertise in these areas.

Module 1 Complete

You now understand:

• How AI is changing instructional design work
• What AI can and can't do realistically
• Which tools to use for different tasks
• How to maintain quality and ethics with AI assistance

In Module 2, we'll get practical. You'll learn exactly how to use AI for content development: generating learning objectives, creating scenarios, drafting explanations, and building assessments. Time to move from theory to practice.