Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Ethical Testing in the Real World: Evaluating Physical Testing of
  Adversarial Machine Learning   This paper critically assesses the adequacy and representativeness of
physical domain testing for various adversarial machine learning (ML) attacks
against computer vision systems involving human subjects. Many papers that
deploy such attacks characterize themselves as "real world." Despite this
framing, however, we found the physical or real-world testing conducted was
minimal, provided few details about testing subjects and was often conducted as
an afterthought or demonstration. Adversarial ML research without
representative trials or testing is an ethical, scientific, and health/safety
issue that can cause real harms. We introduce the problem and our methodology,
and then critique the physical domain testing methodologies employed by papers
in the field. We then explore various barriers to more inclusive physical
testing in adversarial ML and offer recommendations to improve such testing
notwithstanding these challenges.

10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
27
The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph