Distrust on teams isn't a single event but a progression. It begins with Defensiveness (an early warning), moves to Disengagement (withdrawal), and ends in Disenchantment (actively turning others against leadership). Leaders must intervene in the defensiveness phase before the damage becomes irreversible.
Platforms designed for frictionless speed prevent users from taking a "trust pause"—a moment to critically assess if a person, product, or piece of information is worthy of trust. By removing this reflective step in the name of efficiency, technology accelerates poor decision-making and makes users more vulnerable to misinformation.
Unlike prior generations that valued source authority (e.g., a trusted publication), Gen Z's trust in information is primarily driven by their immediate emotional reaction. Content that validates how they feel in the moment is more likely to be trusted, regardless of its factual accuracy or the credibility of who is delivering it.
Historically, we trusted technology for its capability—its competence and reliability to *do* a task. Generative AI forces a shift, as we now trust it to *decide* and *create*. This requires us to evaluate its character, including human-like qualities such as integrity, empathy, and humility, fundamentally changing how we design and interact with tech.
Historically, trust was local (proximity-based) then institutional (in brands, contracts). Technology has enabled a new "distributed trust" era, where we trust strangers through platforms like Airbnb and Uber. This fundamentally alters how reputation is built and where authority lies, moving it from top-down hierarchies to sideways networks.
The primary problem for AI creators isn't convincing people to trust their product, but stopping them from trusting it too much in areas where it's not yet reliable. This "low trustworthiness, high trust" scenario is a danger zone that can lead to catastrophic failures. The strategic challenge is managing and containing trust, not just building it.