The SAFE Benchmarks Framework: FAIRNESS
Updated: Feb 1
"Fairness" applied to AI in edtech means, providing ethical, unbiased and equitable learning opportunities can be achieved as long as developers are intentional about the quality of the data being received from both the procurement of large datasets and the usage of their products, and vigilant regarding potential unconscious biases within their designs.
Below, Eric Nentrup interviews Carnegie Learning's Steve Ritter and The Alliance's own Michael Gamerl as they explain how important the quality of "fairness" is becoming in our technology in serving the most critical needs of both learners and teachers in the modern education landscape. Watch below or listen here.