Mitigating Biases

Addressing biases in AI systems requires action by both technology developers and end-users. This is crucial to ensure equitable learning experiences for all students.
Question mark icon for Mitigating Biases
What measures is the vendor/provider taking to recognize and address biases within their AI systems? How can human users intervene to check and adjust the system’s output?

No technology is perfect but by asking the right questions about a technology and carefully considering our capacity to effectively leverage it, we can maximize impact.



Bias Mitigation:

What approaches have you taken in developing your AI to identify and mitigate biases, particularly in training datasets?


Can you provide transparency reports or documentation on the measures taken to address biases in your AI systems?

Continuous Monitoring:

What processes do you have in place for ongoing monitoring and mitigation of biases as your AI tool evolves?




How will you ensure that AI-generated content or assessments are inclusive and representative of your diverse student population?

AI Literacy:

What steps will you take to educate yourself and your students about the potential biases in AI systems and their impact?

Mitigation Strategies:

How do you plan to implement strategies or tools to identify and mitigate biases within AI-generated content and assessments?


A workplace training department for a large, nationwide corporation in the food processing industry with a highly diverse workforce creates training videos that use AI-driven avatars. These avatars are designed to be linguistically, culturally, and racially diverse, matching the diverse demographics of the company’s employees. Learning and development coordinators collaborate with frontline workers to select avatars, script content, and review videos translated to their home language. They ensure that the avatars not only represent a variety of employee backgrounds but also adhere to cultural sensitivities and language preferences. The training videos feature AI avatars that speak multiple languages and exhibit culturally relevant non-verbal cues, making the content more relatable and engaging for employees from different backgrounds. The introduction of AI avatars in their training videos opens up opportunities to engage employees in co-creation. This results in upskilling for both the frontline workers and learning and development coordinators, enhancing both groups’ AI literacy and cultural awareness. Employee engagement with training materials increases. Feedback surveys indicate that employees feel more represented and understood, which enhances learning outcomes and compliance rates across the corporation.
2 workers looking at a tablet device.

The AI Integration Framework was adapted, with permission, from the "Top 6 Questions for GenAI EdTech Providers" resource developed by AI for Education.

This is one dimension of the AI Integration Framework.

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