• 
• 7 min
• TED
• 2017

Predictive policing software such as PredPol may claim to be objective through mathematical, “colorblind” analyses of geographical crime areas, yet this supposed objectivity is not free of human bias and is in fact used as a justification for the further targeting of oppressed groups, such as poor communities or racial and ethnic minorities. Further, the balance between fairness and efficacy in the justice system must be considered, since algorithms tend more toward the latter than the former.

• Predictive Policing
• Algorithmic Bias
• Machine Learning

• 
• 7 min
• Vice
• 2019

Snapchat stores some user data for legitimate purposes but is vague about doing so, and abuses (such as spying) of this data have occurred within the company.

• Data Privacy
• Tech Monopolies
• Social Networks
• Smartphones

• 
• 5 min
• Science Alert
• 2019

A newly revealed patent application filed by Amazon raises privacy concerns over an upgrade to the virtual assistant Alexa, in which the system records everything a users says in 10-30 second bits to look out for a command.

• Data Privacy
• Assistive Technologies
• Data Mining
• Internet of Things

• 
• 5 min
• The Guardian
• 2019

Biometrics technology will be implemented as a means of gaining access to a residential building in Brooklyn, causing pushback among the tenants who prefer to keep their data private, especially considering the lack of legal regulation surrounding the technology. Specifically, there is growing fear that the facial recognition database could be sold to or abused by law enforcement.

• Data Privacy
• Civil Surveillance
• Biometrics

• 
• 7 min
• The New York Times
• 2019

ICE, along with other law enforcement agencies, mined state driver’s license databases using facial recognition tech to track down undocumented immigrants and prosecute more cases.

• Data Privacy
• Civil Surveillance
• Computer Vision
• Object Recognition
• Data Mining

• 
• 7 min
• The New York Times
• 2019

The article discusses how to protect and delete DNA data from sites like 23andme. It mentions that many privacy policies for such companies are very brief and do not explain what data is stored and what happens to that data. Specifically, once genetic data is shared digitally with third party companies, it is nearly impossible to definitively erase, and there is an imminent possibility that this data could even be de-anonymized.

• Data Privacy
• Computational Genomics