Introduction
Leaders increasingly face judgment calls around AI use that don't have an established precedent to fall back on — questions where the "right" answer isn't yet a matter of settled convention, and where reasonable, well-intentioned leaders might draw the line in different places. Navigating this well requires a different kind of leadership than following an existing rulebook: it requires explicit, communicable ethical reasoning.
The Kinds of Questions Without Precedent
- Disclosure — how much should AI-generated content be labeled as such, in what contexts, and to whom?
- Delegation of authority — how much decision-making should be handed to an automated system, and where should the line for mandatory human review sit?
- Uncomfortable findings — how should a leader handle situations where AI tools reveal patterns — bias in a hiring process, inefficiency in a long-standing workflow — that are uncomfortable but important to address?
- Fairness in AI-informed evaluation — how should leaders ensure that AI tools used in performance or hiring decisions don't introduce or reinforce unfair bias, even unintentionally?
Why a Rulebook Isn't Enough
Because these questions are genuinely new for many organizations, a comprehensive rulebook covering every situation doesn't yet exist — and waiting for one before acting leaves leaders paralyzed on questions that need answers now. What matters more than a complete set of rules is a leader's ability to reason through a novel situation transparently, in a way the team can understand and, ideally, anticipate.
What Explicit Ethical Reasoning Looks Like
Rather than making a judgment call silently and only revealing the conclusion, leaders build more durable trust by making the reasoning visible:
- Stating the competing considerations at play, not just the final decision
- Being honest about genuine uncertainty, rather than presenting a judgment call as if it were obviously correct
- Being consistent — applying similar reasoning to similar situations over time, so the team can predict roughly how future ambiguous cases will be handled
- Being willing to revisit a previous decision if new information or a new situation reveals the original reasoning was incomplete
A Simple Framework for Novel Ethical Questions
- Identify who could be affected by this decision, directly and indirectly
- Consider what precedent this decision sets for similar future situations
- Ask whether the reasoning would hold up if explained openly to the people affected by it
- Make the decision, and document the reasoning — not just the outcome
Why This Builds Trust Even When People Disagree
Teams generally don't expect every leadership decision to be one they'd have made themselves. What they do expect is that the decision was made thoughtfully, for reasons that can be explained and defended. A leader who visibly reasons through a hard ethical question — even imperfectly — tends to retain more trust than one who avoids the question or hands down a conclusion without explanation, even if the eventual decisions are similar.