  Synthetic media detection technologies label media as either synthetic or
non-synthetic and are increasingly used by journalists, web platforms, and the
general public to identify misinformation and other forms of problematic
content. As both well-resourced organizations and the non-technical general
public generate more sophisticated synthetic media, the capacity for purveyors
of problematic content to adapt induces a \newterm{detection dilemma}: as
detection practices become more accessible, they become more easily
circumvented. This paper describes how a multistakeholder cohort from academia,
technology platforms, media entities, and civil society organizations active in
synthetic media detection and its socio-technical implications evaluates the
detection dilemma. Specifically, we offer an assessment of detection contexts
and adversary capacities sourced from the broader, global AI and media
integrity community concerned with mitigating the spread of harmful synthetic
media. A collection of personas illustrates the intersection between
unsophisticated and highly-resourced sponsors of misinformation in the context
of their technical capacities. This work concludes that there is no "best"
approach to navigating the detector dilemma, but derives a set of implications
from multistakeholder input to better inform detection process decisions and
policies, in practice.
