  Scholars have recently drawn attention to a range of controversial issues
posed by the use of computer vision for automatically generating descriptions
of people in images. Despite these concerns, automated image description has
become an important tool to ensure equitable access to information for blind
and low vision people. In this paper, we investigate the ethical dilemmas faced
by companies that have adopted the use of computer vision for producing alt
text: textual descriptions of images for blind and low vision people, We use
Facebook's automatic alt text tool as our primary case study. First, we analyze
the policies that Facebook has adopted with respect to identity categories,
such as race, gender, age, etc., and the company's decisions about whether to
present these terms in alt text. We then describe an alternative -- and manual
-- approach practiced in the museum community, focusing on how museums
determine what to include in alt text descriptions of cultural artifacts. We
compare these policies, using notable points of contrast to develop an analytic
framework that characterizes the particular apprehensions behind these policy
choices. We conclude by considering two strategies that seem to sidestep some
of these concerns, finding that there are no easy ways to avoid the normative
dilemmas posed by the use of computer vision to automate alt text.
