Equity & Risk Checklist

Accessibility & Equity

Ensuring AI tools are accessible to all students and don't create or reinforce inequities

Have we ensured all students can access this AI tool?

Consider technical requirements, device compatibility, internet access, and cost barriers.

Key Considerations:

Does the tool require specific hardware or software?
Is there a cost associated with the tool?
Are there alternative access methods for students with disabilities?
Does the tool work on mobile devices and older computers?

Does the tool provide equitable support for students from diverse backgrounds?

Evaluate whether the tool works equally well for students with different cultural backgrounds, learning styles, and academic preparation levels.

Key Considerations:

Does the tool support multiple languages or cultural contexts?
Are there built-in accommodations for different learning needs?
Does the tool assume prior knowledge that some students might not have?
Are there clear instructions and support materials?

Have we considered the digital divide and provided alternatives?

Ensure students without reliable internet or devices can still participate in the course.

Key Considerations:

Are there offline alternatives or backup plans?
Can the tool be accessed through campus computer labs?
Have we communicated available resources and support?
Is the tool optional or required for course completion?

🔒 Privacy & Data Protection

Protecting student data and ensuring compliance with privacy regulations

What data does the AI tool collect, and are there adequate privacy protections?

Review the tool's data collection practices, storage policies, and compliance with FERPA, GDPR, and other relevant regulations.

Key Considerations:

What personal information is collected from students?
How long is the data stored and where?
Is the data shared with third parties?
Can students access, modify, or delete their data?
Does the tool comply with institutional data policies?

Have we obtained proper consent from students for data collection?

Ensure students understand what data is being collected and how it will be used.

Key Considerations:

Is the consent process clear and transparent?
Can students opt out without academic penalty?
Have we explained the educational benefits of data collection?
Is consent obtained before any data is collected?

Does the tool have appropriate security measures to protect student data?

Verify that the tool uses encryption, secure authentication, and other security best practices.

Key Considerations:

Is data encrypted in transit and at rest?
Does the tool use secure authentication methods?
Are there regular security audits and updates?
What happens if there's a data breach?

⚖️ Bias & Fairness

Identifying and mitigating potential biases in AI tools

Could the AI tool introduce bias or disadvantage any group of students?

Evaluate whether the tool's algorithms or training data might produce biased results for certain groups.

Key Considerations:

What data was used to train the AI model?
Have bias tests been conducted on the tool?
Are there known issues with the tool's performance on certain groups?
How does the tool handle ambiguous or culturally-specific content?

Have we tested the tool with diverse student populations?

Ensure the tool works fairly for students from different backgrounds, abilities, and learning styles.

Key Considerations:

Have we piloted the tool with a diverse group of students?
Are there different performance outcomes for different groups?
Have we collected feedback from students about fairness?
Are there mechanisms to report and address bias concerns?

Does the tool provide transparent explanations of its decisions?

Students should understand how the AI tool makes decisions that affect their learning.

Key Considerations:

Can students see why the tool made specific recommendations?
Are the explanations clear and understandable?
Can students challenge or appeal AI decisions?
Is there human oversight of AI decisions?

🎓 AI Literacy & Training

Ensuring users have the necessary skills to use AI tools effectively

Do users have the necessary AI literacy to use this tool effectively?

Assess whether students and faculty understand how to use the tool appropriately and critically.

Key Considerations:

What level of technical knowledge is required?
Are there clear instructions and tutorials?
Do users understand the tool's limitations?
Have we provided training on critical evaluation of AI outputs?

Have we provided adequate training and support resources?

Ensure users have access to training materials, help documentation, and support channels.

Key Considerations:

Are there video tutorials or written guides?
Is there technical support available?
Have we created best practice guidelines?
Are there opportunities for hands-on practice?

Do users understand how to critically evaluate AI-generated content?

Students should learn to assess the quality, accuracy, and appropriateness of AI outputs.

Key Considerations:

Have we taught students to fact-check AI outputs?
Do users understand when AI might be wrong or biased?
Are there guidelines for verifying AI-generated information?
Have we discussed the importance of human oversight?

📊 Impact Assessment

Measuring the effectiveness and impact of AI tool integration

How will we measure the impact on student learning and integrity?

Establish metrics to evaluate whether the AI tool improves learning outcomes and maintains academic integrity.

Key Considerations:

What learning outcomes are we trying to improve?
How will we measure student engagement and performance?
What indicators will we use to assess academic integrity?
How will we compare outcomes with and without the tool?

Have we established baseline measurements before implementation?

Collect data on current performance and practices to compare against post-implementation results.

Key Considerations:

What data do we have on current student performance?
How do students currently approach similar tasks?
What are the current academic integrity challenges?
Have we documented current teaching practices?

Do we have a plan for ongoing monitoring and evaluation?

Establish regular review processes to assess the tool's continued effectiveness and identify needed adjustments.

Key Considerations:

How often will we review the tool's impact?
Who will be responsible for ongoing evaluation?
What feedback mechanisms are in place?
How will we make adjustments based on findings?

How to Use This Tool

Review Each Category

Check Off Items

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Assessment Progress

Accessibility & Equity

Have we ensured all students can access this AI tool?

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Does the tool provide equitable support for students from diverse backgrounds?

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Have we considered the digital divide and provided alternatives?

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