179 research outputs found
A Short-term Intervention for Long-term Fairness in the Labor Market
The persistence of racial inequality in the U.S. labor market against a
general backdrop of formal equality of opportunity is a troubling phenomenon
that has significant ramifications on the design of hiring policies. In this
paper, we show that current group disparate outcomes may be immovable even when
hiring decisions are bound by an input-output notion of "individual fairness."
Instead, we construct a dynamic reputational model of the labor market that
illustrates the reinforcing nature of asymmetric outcomes resulting from
groups' divergent accesses to resources and as a result, investment choices. To
address these disparities, we adopt a dual labor market composed of a Temporary
Labor Market (TLM), in which firms' hiring strategies are constrained to ensure
statistical parity of workers granted entry into the pipeline, and a Permanent
Labor Market (PLM), in which firms hire top performers as desired. Individual
worker reputations produce externalities for their group; the corresponding
feedback loop raises the collective reputation of the initially disadvantaged
group via a TLM fairness intervention that need not be permanent. We show that
such a restriction on hiring practices induces an equilibrium that, under
particular market conditions, Pareto-dominates those arising from strategies
that statistically discriminate or employ a "group-blind" criterion. The
enduring nature of equilibria that are both inequitable and Pareto suboptimal
suggests that fairness interventions beyond procedural checks of hiring
decisions will be of critical importance in a world where machines play a
greater role in the employment process.Comment: 10 page
Traffic-Aware Transmission Mode Selection in D2D-enabled Cellular Networks with Token System
We consider a D2D-enabled cellular network where user equipments (UEs) owned
by rational users are incentivized to form D2D pairs using tokens. They
exchange tokens electronically to "buy" and "sell" D2D services. Meanwhile the
devices have the ability to choose the transmission mode, i.e. receiving data
via cellular links or D2D links. Thus taking the different benefits brought by
diverse traffic types as a prior, the UEs can utilize their tokens more
efficiently via transmission mode selection. In this paper, the optimal
transmission mode selection strategy as well as token collection policy are
investigated to maximize the long-term utility in the dynamic network
environment. The optimal policy is proved to be a threshold strategy, and the
thresholds have a monotonicity property. Numerical simulations verify our
observations and the gain from transmission mode selection is observed.Comment: 7 pages, 6 figures. A shorter version is submitted to EUSIPC
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