Built for students
Shows AI fairness with simple sliders, plain language, and fictional data.
Third RRF Student Science Tool
Can an AI be smart and still unfair?
The AI Bias & Fairness Lab teaches students how data balance, data quality, thresholds, and human review can change the fairness of a fictional AI system.
Education-only. This simulation uses fictional groups and made-up data. It must not be used for real hiring, school, medical, legal, financial, or personal decisions.
Interactive AI Simulation
Change the data. Watch the fairness gap move.
This lab uses a fictional student-program review model. The “AI” gives a score, then a threshold decides whether the fictional applicant is selected. The goal is to teach AI literacy, not to make real decisions.
Simulation controls
Adjust these settings, then run the simulation. The results show how data conditions can affect two fictional groups.
All scenarios are fictional and education-only.
65%
When one group has many more examples, the model may learn that group better.
25%
Lower-quality records can make the AI less accurate for that group.
60
A higher threshold selects fewer applicants but can change error patterns.
20%
Human review helps catch borderline mistakes. It is not magic; reviewers also need good standards.
Built for schools
Works as a classroom discussion starter for AI literacy, ethics, math, and data science.
Built for sponsors
A company can sponsor AI literacy tools that help students understand technology responsibly.
What Students Learn
AI is not just about code. It is about people, data, and judgment.
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Data Balance
Students see why models can work better for groups that have more examples.
🔎
Data Quality
Students learn that missing, messy, or lower-quality records can affect outcomes.
🎚️
Thresholds
Students test how changing a score cutoff affects selection and error rates.
🤝
Human Review
Students learn why important AI decisions need review, accountability, and clear standards.
Responsible AI Education
Teach students to question the machine.
This tool helps young people understand that AI should be tested, audited, explained, and reviewed — especially when people may be affected by its output.
Build With RRF
Help students understand AI before AI shapes their future.
This tool can support Noble Youth Academy, classroom AI literacy workshops, data science challenges, STEM programs, and sponsor-funded student education.