Privacy (134)
Find narratives by ethical themes or by technologies.
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- 7 min
- Kinolab
- 2002
In the year 2054, the PreCrime police program is about to go national. At PreCrime, three clairvoyant humans known as “PreCogs” are able to forecast future murders by streaming audiovisual data which provides the surrounding details of the crime, including the names of the victims and perpetrators. Joe Anderson, the former head of the PreCrime policing program, is named as a future perpetrator and must flee from his former employer. Due to the widespread nature of retinal scanning biometric technology, he is found quickly, and thus must undergo an eye transplant. While recovering in a run-down apartment, the PreCrime officers deploy spider-shaped drones to scan the retinas of everyone in the building.
- Kinolab
- 2002
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- 7 min
- Kinolab
- 2002
Retinal Scans and Immediate Identification
In the year 2054, the PreCrime police program is about to go national. At PreCrime, three clairvoyant humans known as “PreCogs” are able to forecast future murders by streaming audiovisual data which provides the surrounding details of the crime, including the names of the victims and perpetrators. Joe Anderson, the former head of the PreCrime policing program, is named as a future perpetrator and must flee from his former employer. Due to the widespread nature of retinal scanning biometric technology, he is found quickly, and thus must undergo an eye transplant. While recovering in a run-down apartment, the PreCrime officers deploy spider-shaped drones to scan the retinas of everyone in the building.
Is it possible that people would consent to having their retinas scanned in general public places if it meant a more personalized experience of that space? Should government be able to deceive people into giving up their private data, as social media companies already do? How can people protect themselves from retinal scanning and other biometric identification technologies on small and large scales?
Minority Report: Eyedented-
- 10 min
- New York Times
- 2019
Racial bias in facial recognition software used for Government Civil Surveillance in Detroit. Racially biased technology. Diminishes agency of minority groups and enhances latent human bias.
- New York Times
- 2019
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- 10 min
- New York Times
- 2019
As Cameras Track Detroit’s Residents, a Debate Ensues Over Racial Bias
Racial bias in facial recognition software used for Government Civil Surveillance in Detroit. Racially biased technology. Diminishes agency of minority groups and enhances latent human bias.
What are the consequences of employing biased technologies to survey citizens? Who loses agency, and who gains agency?
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- 7 min
- Vice
- 2019
An academic perspective on an algorithm created by PredPol to “predict crime.” Unless every single crime is reported, and unless and police pursue all types of crimes committed by all people equally, it’s impossible to have a reinforcement learning system that predicts crime itself.Rather, police find crimes in the same places they’ve been told to look for them, feeding the algorithm ineffective data and allowing unjust targeting of communities of color by the police to continue based on trust in the algorithm.
- Vice
- 2019
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- 7 min
- Vice
- 2019
Academics Confirm Major Predictive Policing Algorithm is Fundamentally Flawed
An academic perspective on an algorithm created by PredPol to “predict crime.” Unless every single crime is reported, and unless and police pursue all types of crimes committed by all people equally, it’s impossible to have a reinforcement learning system that predicts crime itself.Rather, police find crimes in the same places they’ve been told to look for them, feeding the algorithm ineffective data and allowing unjust targeting of communities of color by the police to continue based on trust in the algorithm.
Can an algorithm which claims to predict crime ever be fair? Is it ever justified for volatile actors such as police to act based on directions from a machine, where the logic is not always transparent?
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- 3 min
- CNET
- 2019
US Government agencies rely on outdated verification methods, increasing the risk of identify theft.
- CNET
- 2019
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- 3 min
- CNET
- 2019
Thanks to Equifax breach, 4 US agencies don’t properly verify your data, GAO finds
US Government agencies rely on outdated verification methods, increasing the risk of identify theft.
If the government does not ensure our cyber security, then who does? Can any digital method for identity verification be completely safe, especially given how much of our personal data lives in the digital world?
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- 7 min
- The New York Times
- 2019
Biometric facial recognition software, specifically that used with arrest photos in the NYPD, makes extensive use of children’s arrest photos despite a far lower accuracy rate.
- The New York Times
- 2019
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- 7 min
- The New York Times
- 2019
She Was Arrested at 14. Then Her Photo Went to a Biometrics Database
Biometric facial recognition software, specifically that used with arrest photos in the NYPD, makes extensive use of children’s arrest photos despite a far lower accuracy rate.
How can machine learning algorithms cause inequality to compound? Would it be better practice to try to make facial recognition equitable across all populations, or to abandon its use in law enforcement altogether, as some cities like Oakland have done?
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- 5 min
- MIT Technology Review
- 2019
In the case of the New Orleans Police Department, along with other cities, data used to train predictive crime algorithms was inconsistent and “dirty” to begin with, making the results disproportionately targeted toward disadvantaged communities.
- MIT Technology Review
- 2019
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- 5 min
- MIT Technology Review
- 2019
Police across the US are training crime-predicting AIs on falsified data
In the case of the New Orleans Police Department, along with other cities, data used to train predictive crime algorithms was inconsistent and “dirty” to begin with, making the results disproportionately targeted toward disadvantaged communities.
If the data which we train algorithms with is inherently biased, then can we truly ever get a “fair” algorithm? Can AI programs ever solve or remove human bias? What might happen if machines make important criminal justice decisions, such as sentence lengths?