Would AI have drafted Michael Jordan?
AI is a powerful tool but it often misses the mark when evaluating human potential.
Consider some of history’s greatest athletes:
Muggsy Bogues, at 5’3”, led the NBA in steals and defied every expectation of what a point guard “should” be. No algorithm would draft him—too short.
Cal Ripken Jr. redefined baseball as a 6'4" shortstop. Machines would have rejected him as "too tall" for the role.
Michael Jordan didn’t fit any mold. He wasn’t the best scorer, playmaker, or defender—but he fused all three with an unquantifiable competitive fire.
These legends had intangible qualities like creativity, adaptability, and grit.
Traits no spreadsheet can capture.
AI excels at optimizing within predefined parameters of what “good” looks like.
Yet, transformative potential often lies beyond these boundaries.
Jordan didn’t just play the game—he rewrote it.
Similarly, in lending, traditional underwriting models focus on conventional credit scores and employment histories, overlooking important signals like cash flow stability, bill payment consistency, and other indicators of financial responsibility.
At FairPlay, we help companies build AI systems that see beyond the obvious metrics to recognize the full spectrum of human potential.
If even the greatest athletes would’ve been overlooked by AI, how might it fail other unseen innovators, entrepreneurs, and borrowers?
The question isn't whether AI can quantify intangibles.
It's whether we're brave enough to use tools that try.