Video and data surveillance by public and private entities.
Civil Surveillance (26)
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- 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.
Discussion Prompts:
What are the consequences of employing biased technologies to survey citizens? Who loses agency, and who gains agency?
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- 15 min
- Kinolab
- 2017
Detective Shazia Akhand is assigned to investigate the case of a man who was hit by a pizza truck in the street to help him build a case. She uses a brain-computer interface to read the memories of both the man hit by the truck and other witnesses, where the vague, abstract images are projected onto a screen. One of these witnesses includes Mia, a serial killer whose former crimes are revealed during her interview. In order to erase any footage or evidence of her murders, Mia continues her killing spree by wiping out Shazia and her family. However, Mia is eventually caught through the memories of an unlikely source.
- Kinolab
- 2017
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- 15 min
- Kinolab
- 2017
Digital Memory Projection and Walking Surveillance Cameras
Detective Shazia Akhand is assigned to investigate the case of a man who was hit by a pizza truck in the street to help him build a case. She uses a brain-computer interface to read the memories of both the man hit by the truck and other witnesses, where the vague, abstract images are projected onto a screen. One of these witnesses includes Mia, a serial killer whose former crimes are revealed during her interview. In order to erase any footage or evidence of her murders, Mia continues her killing spree by wiping out Shazia and her family. However, Mia is eventually caught through the memories of an unlikely source.
Discussion Prompts:
Should police or detectives be able to view memories for interrogation reasons? Where should the line be drawn in these cases? What are the issues with tasking precise digital technologies with extracting and showing abstract memories? How could this technology be manipulated to make subjective memories seem objective? How might this sort of technology makes witnesses to crimes more targeted? How is this concept similar and different to the idea that anyone could accidentally or intentionally be capturing anything on a phone camera? Should technology be created that essentially allows anyone to be a walking surveillance camera?
Black Mirror: Shazia Interviews the Crash Victim-
- 12 min
- Wired
- 2018
This video offers a basic introduction to the use of machine learning in predictive policing, and how this disproportionately affects low income communities and communities of color.
- Wired
- 2018
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- 12 min
- Wired
- 2018
How Cops Are Using Algorithms to Predict Crimes
This video offers a basic introduction to the use of machine learning in predictive policing, and how this disproportionately affects low income communities and communities of color.
Discussion Prompts:
Should algorithms ever be used in a context where human bias is already rampant, such as in police departments? Why is it that the use of digital technologies to accomplish tasks in this age makes a process seem more “efficient” or “objective”? What are the problems with police using algorithms of which they do not fully understand the inner workings? Is the use of predictive policing algorithms ever justifiable?
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- 5 min
- Gizmodo
- 2020
This article describes the new Amazon Sidewalk feature and subsequently explains why users should not buy into this service. Essentially, this feature uses the internet of things created by Amazon devices such as the Echo or Ring camera to create a secondary network connecting nearby homes which also contain these devices, which is sustained by each home “donating” a small amount of broadband. It is explained that this is a dangerous concept because this smaller network may be susceptible to hackers, putting a large number of users at risk.
- Gizmodo
- 2020
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- 5 min
- Gizmodo
- 2020
You Need to Opt Out of Amazon Sidewalk
This article describes the new Amazon Sidewalk feature and subsequently explains why users should not buy into this service. Essentially, this feature uses the internet of things created by Amazon devices such as the Echo or Ring camera to create a secondary network connecting nearby homes which also contain these devices, which is sustained by each home “donating” a small amount of broadband. It is explained that this is a dangerous concept because this smaller network may be susceptible to hackers, putting a large number of users at risk.
Discussion Prompts:
Why are “secondary networks” like the one described here a bad idea in terms of both surveillance and data privacy? Is it possible for the world to be too networked? How can tech developers make sure the general public has a healthy skepticism toward new devices? Or is it ultimately Amazon’s job to think about the ethical implications of this secondary network before introducing it for profits?
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- 7 min
- Wired
- 2020
As different levels of the U.S government have introduced and passed bills regulating or banning the use of facial recognition technologies, tech monopolies such as Amazon and IBM have become important lobbying agents in these conversations. It seems that most larger groups are on different pages in terms of how exactly face recognition algorithms should be limited or used, especially given their negative impacts on privacy when used for surveillance.
- Wired
- 2020
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- 7 min
- Wired
- 2020
Congress Is Eyeing Face Recognition, and Companies Want a Say
As different levels of the U.S government have introduced and passed bills regulating or banning the use of facial recognition technologies, tech monopolies such as Amazon and IBM have become important lobbying agents in these conversations. It seems that most larger groups are on different pages in terms of how exactly face recognition algorithms should be limited or used, especially given their negative impacts on privacy when used for surveillance.
Discussion Prompts:
Can and should the private sector be regulated in its use of facial recognition technologies? How is it that tech monopolies might hold so much sway with government officials, and how can this be addressed? Do the benefits of facial recognition, such as convenience at the airport, listed at the end of the article make enough of a case against a complete ban of the technology, or do the bad applications ultimately outweigh the good ones? What would the ideal bill look like in terms of limiting or banning facial recognition?
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- 7 min
- Wired
- 2020
After student members of the University of Miami Employee Student Alliance held a protest on campus, the University of Miami Police Department likely used facial recognition technology in conjunction with video surveillance cameras to track down nine students from the protest and summon them to a meeting with the dean. This incident provided a gateway into the discussion of fairness of facial recognition programs, and how students believe that they should not be deployed on college campuses.
- Wired
- 2020
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- 7 min
- Wired
- 2020
Facial Recognition Applications on College Campuses
After student members of the University of Miami Employee Student Alliance held a protest on campus, the University of Miami Police Department likely used facial recognition technology in conjunction with video surveillance cameras to track down nine students from the protest and summon them to a meeting with the dean. This incident provided a gateway into the discussion of fairness of facial recognition programs, and how students believe that they should not be deployed on college campuses.
Discussion Prompts:
How can facial recognition algorithms interfere with the right of people to protest? When it comes to facial recognition databases, are larger photo repositories better or worse? Does facial recognition and video surveillance have a place on college campuses? How does facial recognition and video surveillance embolden people in power in general?