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Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
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Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
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Computer-vision research powers surveillance technology.

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Computer vision research significantly fuels mass surveillance systems, with a fivefold increase in related patents since the 1990s. This field increasingly normalizes targeting humans, often using obfuscated language.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Surveillance Studies

Background:

  • Growing concerns link artificial intelligence (AI), particularly computer vision, to the development of mass surveillance technologies.
  • The precise relationship between computer vision research and its application in surveillance remains a subject of debate.

Purpose of the Study:

  • To empirically investigate the nature and extent of the surveillance AI pipeline.
  • To provide evidence of the close ties between computer vision research and surveillance applications.
  • To analyze the normalization of human targeting within the computer vision field.

Main Methods:

  • Analysis of computer vision research papers and their citing patents.
  • Quantitative comparison of research-patent links from the 1990s to the 2010s.
  • Examination of language used in research documents to identify patterns of obfuscation.

Main Results:

  • A significant majority of analyzed computer vision documents facilitate the targeting of human bodies and body parts.
  • A fivefold increase was observed in computer vision papers linked to surveillance-enabling patents between the 1990s and 2010s.
  • The study found pervasive normalization of human targeting within the field, often masked by euphemistic language referring to humans as 'objects'.

Conclusions:

  • Computer vision research is extensively intertwined with the development and deployment of surveillance technologies.
  • The normalization of human targeting, often obscured by specific language, is a widespread issue within the computer vision research community.
  • Findings challenge the idea that surveillance is driven solely by a few actors, highlighting systemic integration within the field.