The most common question about our AI leadership coverage is whether we're evaluating executive decisions on their actual merits or simply on whether they turned out well in hindsight, which isn't always the same thing.
Why this distinction matters
A well-reasoned decision can fail due to factors outside anyone's control, and a poorly-reasoned decision can succeed by luck, and coverage that judges leadership purely on outcomes risks rewarding poor process that happened to work and punishing sound process that didn't.
Our actual approach
We try to evaluate leadership decisions based on what was reasonably knowable at the time they were made, distinct from how they eventually turned out, though we acknowledge this is a harder and more subjective standard to apply consistently than simple outcome-based judgment.
Why we don't always succeed at this distinction
Hindsight bias is a genuinely difficult thing to fully correct for, and we don't claim to always separate process quality from outcome quality as cleanly as we'd like.
Why we think this distinction is worth attempting anyway
We think readers are better served by coverage that at least attempts to evaluate leadership decisions on their reasoning, not just their eventual results, even when that attempt is imperfect.