  We focus on explaining image classifiers, taking the work of Mothilal et al.
[2021] (MMTS) as our point of departure. We observe that, although MMTS claim
to be using the definition of explanation proposed by Halpern [2016], they do
not quite do so. Roughly speaking, Halpern's definition has a necessity clause
and a sufficiency clause. MMTS replace the necessity clause by a requirement
that, as we show, implies it. Halpern's definition also allows agents to
restrict the set of options considered. While these difference may seem minor,
as we show, they can have a nontrivial impact on explanations. We also show
that, essentially without change, Halpern's definition can handle two issues
that have proved difficult for other approaches: explanations of absence (when,
for example, an image classifier for tumors outputs "no tumor") and
explanations of rare events (such as tumors).
