• 
• 10 min
• Quartz
• 2019

A comparison of surveillance systems in China and the US which target, and aid in the persecution of, ethnic minorities. Data on targeted people is tracked extensively and compiled into intuitive databases which can be abused by government organizations.

• Data Privacy
• Civil Surveillance
• Machine Learning
• Data Mining

• 
• 7 min
• New York Times
• 2018

Youtube’s algorithm suggests increasingly radical recommendations to its users, maximising the amount of time they spend on the platform. The tendency toward inflammatory recommendations often leads to political misinformation.

• Digital Media Misinformation
• Polarization
• Recommender Systems
• Social Networks

• 
• 10 min
• The Washington Post
• 2019

Law enforcement officials at Federal and state levels, notably the FBI and ICE, use state driver’s license photo databases as a repository for facial recognition software. Such capabilities allow DMVs to help law enforcement in finding those suspected of a crime, undocumented immigrants, or even witnesses. Ultimately, states allow this to happen with certain stipulations, feeding into a concerning system of facial recognition and breach of trust. There is not a solid established system for citizen consent to such monitoring.

• Data Privacy
• Civil Surveillance
• Computer Vision
• Biometrics

• 
• 27 min
• Cornell Tech
• 2019

Podcast about worker quantification in factors such as hiring, productivity and more. Dives into the discussion on why we should attempt a fair making of algorithms. Warns specifically about how algorithms can find “proxy variables” to approximate for cultural fits like race or gender even when the algorithms is supposedly controlled for these factors.

• Algorithmic Bias
• Technology and Race
• Machine Learning

• 
• 5 min
• Time Magazine
• 2017

Chicago police enact an algorithm to calculate a “risk score” for individuals based on factors such as criminal history and age with the aim of assessing and pre-emptively striking against risk. However, these numbers are inherently linked to human bias both in input and outcome, and could lead to unfair targeted of citizens, even as it supposedly introduces objectivity to the system.

• Predictive Policing
• Algorithmic Bias
• Machine Learning

• 
• 5 min
• Wired
• 2019

Axon’s novel use of an ethics committee led to a decision to not use facial recognition programs on the body cameras which they provide to police department, on the basis of latent racial bias and privacy concerns. While this is a beneficial step, companies and government offices at multiple levels debate over when and how facial recognition should be deployed and limited.

• Civil Surveillance
• Algorithmic Bias
• Computer Vision