AI did not end the data literacy crisis. It changed it. As machines move from providing information to interpreting it and recommending what to do, the scarce skill is becoming judgment: knowing what to trust, what to question, and what decisions are still ours to make.
Evidence does not make decisions. People interpret it, weigh it, challenge it, and make judgments. A courtroom reveals what leaders can learn about evidence, expertise, confidence, and data-informed decision-making.
Feeling sure doesn't mean you're right. Learn five simple ways to question what feels true, spot what might be influencing you, and make better decisions about what to believe.
What a historic Red Sox winning streak reveals about the Two Clocks of decision-making. Every important decision is made between the deadline to act and the time required for evidence to mature. That's where judgment matters most.
The evidence arrives after the decision is due. That's why judgment exists.
The debate about the Red Sox turnaround is a debate about causes, and it cannot be settled. Manager, culture, luck, and schedule all moved at once, which means no explanation can be isolated. The common read treats a streak as information about what a team is. The more useful read treats it as a deadline problem. Evidence takes months to mature. The decision arrives in weeks.
You have approved a budget increase on six weeks of data. You have scaled a pilot on early returns, or credited a turnaround to the executive who happened to arrive before it. The cost is not that these calls are wrong. It is that they are made inside a window too short to reveal anything, and then the decision itself removes the chance to find out. The alternative is not more analysis or more patience, since the deadline will not move. It is a way of deciding that stays explicit about what remains unknown, and that builds in the review before the outcome arrives to write its own story.
Anyone who allocates resources against incomplete evidence and cannot wait for it to fill in. Leaders judging a new hire at ninety days. Executives weighing whether a strong quarter justifies a structural bet. Anyone who has watched a confident explanation harden into accepted fact inside their organization without a single person asking what would disprove it.
A way to separate the explanations worth testing from the ones built so they can never fail. A method for pricing both errors instead of predicting one outcome. And a sharper eye for the moment when evidence and a deadline arrive out of step, which is most of the moments that matter.
On June 18, after the Toronto Blue Jays finished sweeping his team, Red Sox pitcher Sonny Gray stood at his locker and said "We're just not a good team right now. That's a fact."
The data backed him up. The Boston Red Sox were one of the worst teams in baseball. They were 14 games under .500 in late June, about halfway through the season. The offense ranked 27th out of 30 teams in scoring. The front office was fielding trade calls on its veterans, Gray included. Boston sports radio had moved on to start covering the NFL training camps.
Five weeks later, that same roster made history. Fifteen consecutive wins, tying the franchise record set by the 1946 team that had Ted Williams in the lineup and six All-Stars around him. Four-game sweeps of the New York Yankees and Tampa Rays. The run ended on July 22, one win short of the record, when the Baltimore Orioles won the second game of a doubleheader hours after Boston had won the first to reach fifteen.
Now the streak is over, and the question it left behind is the one every business leader should recognize. What changed?
A story that cannot be tested is a story that can never be wrong.
Ask ten people and you will get five confident explanations. These are the ones you hear most.
The manager changed. Chad Tracy took over on an interim basis, and the turnaround has come on his watch. Sports Illustrated compared it to 1988, when the Sox won 12 straight after an interim manager took the reins.
The distraction left. In early July, the team sent injured star Roman Anthony to Florida to rehab a rare finger injury that has kept him out since early May. The streak began days later. For anyone hunting a cause, that coincidence writes its own story: the drama left the building, and the winning began.
Or maybe nothing changed at all, and we are watching variance do what variance does.
Every one of these is plausible. Several are probably partly true. And that is what makes a streak so dangerous to learn from. When many things move at once, the honest answer to "what changed" is "we cannot fully know." That answer feels terrible, so we do not give it. We pick a story instead. Then, before the season has told us whether the story is right, we make decisions we cannot take back.
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Evidence does not make decisions. People interpret it, weigh it, challenge it, and make judgments. A courtroom reveals what leaders can learn about evidence, expertise, confidence, and data-informed decision-making.
Feeling sure doesn't mean you're right. Learn five simple ways to question what feels true, spot what might be influencing you, and make better decisions about what to believe.
We teach data literacy as a ladder: data at the bottom, wisdom at the top, climb step by step. But the rungs are not where the work happens. The judgment lives in the gaps between them, and that is exactly where AI now carries us straight past.
Every organization keeps one scoreboard for mistakes and none for missed opportunities. So people optimize the one they can see, and the largest losses never appear as losses at all. They appear as things no one tried.
