We present a structural approach toward achieving equal opportunity in systems of algorithmic decision-making called algorithmic pluralism. Algorithmic pluralism describes a state of affairs in which no set of algorithms severely limits access to opportunity, allowing individuals the freedom to pursue a diverse range of life paths. To argue for algorithmic pluralism, we adopt Joseph Fishkin's theory of bottlenecks, which focuses on the structure of decision-points that determine how opportunities are allocated. The theory contends that each decision-point or bottleneck limits access to opportunities with some degree of severity and legitimacy. We extend Fishkin's structural viewpoint and use it to reframe existing systemic concerns about equal opportunity in algorithmic decision-making, such as patterned inequality and algorithmic monoculture. In proposing algorithmic pluralism, we argue for the urgent priority of alleviating severe bottlenecks in algorithmic decision-making. We contend that there must be a pluralism of opportunity available to many different individuals in order to promote equal opportunity in a systemic way. We further show how this framework has several implications for system design and regulation through current debates about equal opportunity in algorithmic hiring.

翻译：我们提出一种名为“算法多元主义”的结构性方法，旨在算法决策系统中实现机会均等。算法多元主义描述了一种状态：在此状态下，任何算法集合都不会严重限制个人获取机会，从而赋予个体追求多样化人生道路的自由。为论证算法多元主义，我们借鉴了约瑟夫·菲什金（Joseph Fishkin）的瓶颈理论，该理论聚焦于决定机会分配方式的决策点结构。该理论认为，每个决策点或瓶颈都在一定程度上限制了机会的可及性，且这种限制具有不同程度的严重性与合法性。我们扩展了菲什金的结构性视角，并运用其重新审视算法决策中机会均等面临的系统性担忧，例如模式化不平等与算法单一文化。在提出算法多元主义时，我们强调缓解算法决策中严重瓶颈的紧迫性。我们认为，必须为众多不同个体提供多样化的机会，才能系统性地促进机会均等。我们进一步展示了该框架如何通过当前关于算法招聘中机会均等的辩论，对系统设计与监管产生多重影响。