AI Tools and Accessibility, Data Protection, and Privacy

Updated on Dec 16, 2024

AI Tool Accessibility Checklist

Evaluation Criteria	Description	What to Look For
WCAG Compliance	Ensure AI tool meets Web Content Accessibility Guidelines (WCAG)Links to an external site. standards.	Check for compliance with WCAG 2.1 (or higher) criteria, including perceivable, operable, understandable, and robust principles.
Keyboard Accessibility	Ensure that the AI tool is fully navigable via keyboard.	Confirm that all functionalities (input, navigation, actions) can be performed using only the keyboard without requiring a mouse.
Screen Reader Compatibility	Check if the AI tool works well with screen readers (e.g., JAWS, NVDA, VoiceOver).	Ensure that screen readers can accurately interpret and communicate all information (text, images, buttons, menus) to users.
Text Alternatives for Non-Text Content	Ensure that images, icons, and buttons have descriptive alt text or labels.	Verify that all non-text elements (images, icons, multimedia) have meaningful text alternatives for users with visual impairments.
Color Contrast	Ensure sufficient contrast between text and background colors.	Check that the color contrast ratio meets WCAG guidelines (minimum 4.5:1 for normal text, 3:1 for large text).
Adjustable Text Size	Provide users with options to adjust text size or zoom without breaking layout.	Confirm that users can resize text without losing content or functionality, and that it scales appropriately across the interface.
Error Identification & Recovery	Ensure clear and accessible error messages and recovery options.	Check that error messages are easy to understand, clearly indicated, and provide guidance on how to recover from errors.
Time Limits & Adjustable Settings	Provide flexibility with time-sensitive interactions.	Ensure that users can adjust or extend time limits if applicable, or that there are no arbitrary time constraints that hinder interaction.
Cognitive Load & Simplicity	Ensure that the tool is easy to understand and use for people with cognitive disabilities.	Evaluate the complexity of the interface, instructions, and language. Look for simple, clear, and concise text and an intuitive interface.
Mobile & Responsive Design	Ensure accessibility on mobile devices.	Check that the AI tool is fully responsive and accessible on mobile devices, using appropriate touch targets and gestures for users with disabilities.
Speech-to-Text & Text-to-Speech	Provide speech recognition or read-aloud functionality where needed.	Confirm that the tool offers or integrates with voice input (speech-to-text) and/or text-to-speech options for users with limited mobility or visual impairments.
Customizable Settings	Offer users the ability to customize accessibility settings.	Look for options to personalize font sizes, contrast modes (dark mode, high contrast), and navigation methods to suit individual needs.
Training & Documentation	Provide accessible training materials and documentation for the AI tool.	Ensure that all help resources, tutorials, and documentation are accessible, including being screen-reader friendly and available in multiple formats.
User Feedback Mechanisms	Enable users to provide feedback on accessibility issues.	Check if there are clear pathways for reporting accessibility issues or providing feedback, and ensure quick responses to resolve such issues.

Data Use and Privacy

When considering whether or not to use AI tools in your course, also think about how the tool has addressed, or not addressed, various privacy and data storage concerns. Keep in mind a fundamental tradeoff: if a tool is “free,” the company behind it is likely profiting from your data in some way. Before asking your students to use an AI tool, make sure you’ve considered the following questions:

Data Collection and Use:
- What types of data does the AI tool collect (e.g., personal information, audio/video recordings, student work samples)?
- How is the collected data used, processed, and stored?
- Is the data collection and use compliant with relevant data protection laws and regulations (e.g., FERPA)?
Data Privacy and Security:
- What measures are in place to protect the privacy and security of the collected data?
- Is the data encrypted during transmission and storage?
- Are there robust access controls and authentication mechanisms to prevent unauthorized access?
Data Retention and Deletion:
- How long is the collected data retained, and what is the data retention policy?
- Can the data be easily deleted or removed upon request or when no longer needed?
Transparency and Consent:
- Are learners informed about the data collection practices and the use of AI tools?
- Is explicit consent obtained from learners before using the AI tool?
- Are there clear and accessible privacy policies and terms of service?
Bias and Fairness:
- Has the AI tool been evaluated for potential biases or unfair treatment of different groups based on factors such as race, gender, or socioeconomic status?
- What measures have been taken to mitigate or eliminate algorithmic biases?
Accountability and Oversight:
- Is there a clear process for addressing concerns, complaints, or incidents related to the AI tool's use?
- Are there mechanisms for independent audits or external oversight to ensure responsible and ethical use?
Third-Party Involvement:
- If the AI tool involves third-party services or data sharing, what safeguards are in place to protect learner data and privacy?
- Have the third-party providers' data practices and security measures been thoroughly reviewed?

Should you decide to incorporate an AI-tool into your classroom practice, periodically review the AI tool's data and privacy practices to ensure it continues to conform to data and privacy requirements.