  Every year at NeurIPS, machine learning researchers gather and discuss
exciting applications of machine learning in areas such as public health,
disaster response, climate change, education, and more. However, many of these
same researchers are expressing growing concern about applications of machine
learning for surveillance (Nanayakkara et al., 2021). This paper presents a
brief overview of strategies for resisting these surveillance technologies and
calls for greater collaboration between machine learning and human-computer
interaction researchers to address the threats that these technologies pose.
