Topic archive

Fairness

2 published stories filed under Fairness.

A balance scale tipping toward a solid object of gears and tools over a flat paper certificate

ai June 24, 2026 5 min read

Hiring for Capability: Applied AI and the Skills-First Bet

Skills-first hiring promises to judge people on what they can do, not the credentials they happen to hold. Doing that at scale means making fast judgments about capability — and that is exactly where applied AI helps, and exactly where it can do the most damage.

Skills-first hiring asks software to judge capability, not credentials. That is a judgment problem, not a filtering one — and the bias and explainability burden is the whole game. Where applied AI fits, and where a human still decides.

Eli Wood

CEO, Black Flag Design

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Three distinct data streams flowing into a single balanced scale that outputs one numbered score, with a human hand resting on the scale's beam

applied ai June 24, 2026 4 min read

Scoring people fairly: the explainability burden of rating humans with AI

Composite scores that rank people — blending grades, social signals, and demonstrated skill — are some of the highest-stakes models you can ship. The hard part isn't the math; it's earning the right to be trusted with a number that changes someone's life.

When AI assigns a single score to a person, explainability and bias aren't features — they're the whole product. Here's how to build composite rating systems that hold up.

Keith Pattison

Founder, Black Flag Design

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