  Fairness-aware recommender systems that have a provider-side fairness concern
seek to ensure that protected group(s) of providers have a fair opportunity to
promote their items or products. There is a ``cost of fairness'' borne by the
consumer side of the interaction when such a solution is implemented. This
consumer-side cost raises its own questions of fairness, particularly when
personalization is used to control the impact of the fairness constraint. In
adopting a personalized approach to the fairness objective, researchers may be
opening their systems up to strategic behavior on the part of users. This type
of incentive has been studied in the computational social choice literature
under the terminology of ``bossiness''. The concern is that a bossy user may be
able to shift the cost of fairness to others, improving their own outcomes and
worsening those for others. This position paper introduces the concept of
bossiness, shows its application in fairness-aware recommendation and discusses
strategies for reducing this strategic incentive.
