A broad current application of algorithms is in formal and quantitative measures of murky concepts -- like merit -- to make decisions. When people strategically respond to these sorts of evaluations in order to gain favorable decision outcomes, their behavior can be subjected to moral judgments. They may be described as 'gaming the system' or 'cheating,' or (in other cases) investing 'honest effort' or 'improving.' Machine learning literature on strategic behavior has tried to describe these dynamics by emphasizing the efforts expended by decision subjects hoping to obtain a more favorable assessment -- some works offer ways to preempt or prevent such manipulations, some differentiate 'gaming' from 'improvement' behavior, while others aim to measure the effort burden or disparate effects of classification systems. We begin from a different starting point: that the design of an evaluation itself can be understood as furthering goals held by the evaluator which may be misaligned with broader societal goals. To develop the idea that evaluation represents a strategic interaction in which both the evaluator and the subject of their evaluation are operating out of self-interest, we put forward a model that represents the process of evaluation using three interacting agents: a decision subject, an evaluator, and society, representing a bundle of values and oversight mechanisms. We highlight our model's applicability to a number of social systems where one or two players strategically undermine the others' interests to advance their own. Treating evaluators as themselves strategic allows us to re-cast the scrutiny directed at decision subjects, towards the incentives that underpin institutional designs of evaluations. The moral standing of strategic behaviors often depend on the moral standing of the evaluations and incentives that provoke such behaviors.

翻译：算法当前广泛用于对模糊概念（例如“功绩”）进行正式且量化的评估，以辅助决策。当人们为获取有利的决策结果而对这些评估做出策略性回应时，其行为可能遭受道德评判。此类行为或被描述为“钻系统空子”或“作弊”，或在其他情况下被视为投入“诚实努力”或“寻求改进”。关于策略行为的机器学习文献试图通过强调决策主体为获得更有利评估所付出的努力来描述这些动态——部分研究提供了预防或阻止此类操纵的方法，部分区分了“钻空子”行为与“改进”行为，另一些则旨在衡量分类系统的努力负担或差异性影响。我们的出发点不同：评估设计本身可被理解为服务于评估者的目标，而这些目标可能与更广泛的社会目标不一致。为阐明评估是一种策略互动（其中评估者与被评估主体均出于自身利益行事），我们提出一个模型，通过三个互动代理——决策主体、评估者以及代表价值观与监督机制的“社会”——来表示评估过程。我们强调该模型在多种社会系统中的适用性，在这些系统中，一方或两方参与者策略性地损害其他参与者的利益以谋取自身利益。将评估者本身视为策略主体，允许我们将原本聚焦于决策主体的审视，转向支撑评估制度设计的激励因素。策略行为的道德立场往往取决于引发此类行为的评估与激励机制的道德正当性。