Data-based decision-making must account for data manipulation , or gaming, by agents who are aware of how decisions are being made  . We study a framework in which this manipulationmakes data less informative when decisions depend more strongly on data. We formalize why and how a decision-maker should commit to under-utilizing datain order to attenuate information loss .
Data-based decisionmaking must account for the manipulation of data by agents who are aware of how decisions are being made and want to affect their allocations . We study a framework in which , due to such manipulation, data becomes less informative when decisions depend more strongly on data. We formalize why and how a decisionmaker should commit to underutilizing data. Doing so attenuates information loss and thereby improves allocation accuracy .
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decision-making
decisionmaking
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data manipulation , or gaming,
the manipulation of data
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and want to affect their allocations
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this manipulationmakes data
, due to such manipulation, data becomes
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decision-maker
decisionmaker
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under-utilizing datain order to attenuate information loss
underutilizing data. Doing so attenuates information loss and thereby improves allocation accuracy