---
id: "concept-praiseworthy-exploratory-testing"
type: "concept"
source_timestamps: ["§ When Experimentation Looks Like Rule-Breaking"]
tags: ["innovation", "culture", "psychological-safety"]
related: ["concept-blameworthy-deviance", "action-legitimize-experimentation", "entity-amy-edmondson"]
definition: "Experimenting at the edge of known processes to produce failures that generate valuable learning, often misidentified by organizations as rule-breaking."
sources: ["execution"]
sourceVaultSlug: "hbr-seg-execution"
originDay: 8
articleStem: "hbr-cl-76-employees-not-transparent-ai-usage"
sourceUrl: "https://hbr.org/2026/06/why-employees-arent-transparent-about-their-ai-usage"
sourceTitle: "Why Employees Aren’t Transparent About Their AI Usage"
---
# Praiseworthy Exploratory Testing

A concept championed by Harvard Business School professor [[entity-amy-edmondson|Amy Edmondson]], representing experimentation *at the edge of what is known*. In the context of AI, this looks like employees iterating on prompts, testing novel tasks, and building idiosyncratic workflows — precisely the behavior that surfaces valuable AI use cases.

The danger is miscategorization: organizations frequently mistake this behavior for [[concept-blameworthy-deviance]] (harmful rule-breaking) and punish the exact exploratory behavior they need to encourage. That confusion drives AI experimentation underground and is the failure mode named in [[claim-governance-targets-wrong-problem]].

The prescriptive fix is to give the behavior a sanctioned name and home — see [[action-legitimize-experimentation]] and [[concept-side-quests]]. Understanding *why* it must be protected requires the concept of [[prereq-psychological-safety-basics|psychological safety]].