  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.
