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 adopt 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 our proposal of algorithmic pluralism, we argue for the urgent priority of alleviating severe bottlenecks. 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，旨在实现算法决策系统中的机会均等。算法多元主义描述了一种状态：没有一组算法严重限制获取机会的途径，从而使个人能够自由追求多样化的生活路径。为论证算法多元主义，我们采纳了约瑟夫·菲什金（Joseph Fishkin）的瓶颈理论，该理论聚焦于决定机会如何分配的决策节点结构。该理论认为，每个决策节点或瓶颈都会在一定程度上以不同的严重性和合法性限制机会获取。我们借鉴菲什金的结构性视角，将其用于重新审视算法决策中关于机会均等的现有系统性问题，例如模式性不平等和算法单一文化。在我们提出的算法多元主义中，我们主张缓解严重瓶颈是当务之急。我们认为，必须为众多不同个体提供机会的多元性，才能以系统性的方式促进机会均等。我们进一步通过当前关于算法招聘中机会均等的辩论，展示了该框架对系统设计与监管的若干启示。