  We consider the problem of a Bayesian agent receiving signals over time and
then taking an action. The agent chooses when to stop and take an action based
on her current beliefs, and prefers (all else equal) to act sooner rather than
later. The signals received by the agent are determined by a principal, whose
objective is to maximize engagement (the total attention paid by the agent to
the signals). We show that engagement maximization by the principal minimizes
the agent's welfare; the agent does no better than if she gathered no
information. Relative to a benchmark in which the agent chooses the signals,
engagement maximization induces excessive information acquisition and extreme
beliefs. An optimal strategy for the principal involves "suspensive signals"
that lead the agent's belief to become "less certain than the prior" and
"decisive signals" that lead the agent's belief to jump to the stopping region.
