  A rapidly growing number of voices argue that AI research, and computer
vision in particular, is powering mass surveillance. Yet the direct path from
computer vision research to surveillance has remained obscured and difficult to
assess. Here, we reveal the Surveillance AI pipeline by analyzing three decades
of computer vision research papers and downstream patents, more than 40,000
documents. We find the large majority of annotated computer vision papers and
patents self-report their technology enables extracting data about humans.
Moreover, the majority of these technologies specifically enable extracting
data about human bodies and body parts. We present both quantitative and rich
qualitative analysis illuminating these practices of human data extraction.
Studying the roots of this pipeline, we find that institutions that
prolifically produce computer vision research, namely elite universities and
"big tech" corporations, are subsequently cited in thousands of surveillance
patents. Further, we find consistent evidence against the narrative that only
these few rogue entities are contributing to surveillance. Rather, we expose
the fieldwide norm that when an institution, nation, or subfield authors
computer vision papers with downstream patents, the majority of these papers
are used in surveillance patents. In total, we find the number of papers with
downstream surveillance patents increased more than five-fold between the 1990s
and the 2010s, with computer vision research now having been used in more than
11,000 surveillance patents. Finally, in addition to the high levels of
surveillance we find documented in computer vision papers and patents, we
unearth pervasive patterns of documents using language that obfuscates the
extent of surveillance. Our analysis reveals the pipeline by which computer
vision research has powered the ongoing expansion of surveillance.
