  We present an experimental illustration on the quantum sensitivity of
decision making machinery. In the decision making process, we consider the role
of available information, say hint, whether it influences the optimal choices.
To the end, we consider a machinery method of decision making in a
probabilistic way. Our main result shows that in decision making process our
quantum machine is more highly sensitive than its classical counterpart to the
hints we categorize into "good" and "poor." This quantum feature originates
from the quantum superposition involved in the decision making process. We also
show that the quantum sensitivity persists before the quantum superposition is
completely destroyed.
