• 
• 10 min
• The Washington Post
• 2021

The academic Philip Agre, a computer scientist by training, wrote several papers warning about the impacts of unfair AI and data barons after spending several years studying the humanities and realizing that these perspectives were missing from the field of computer science and artificial intelligence. These papers were published in the 1990s, long before the data-industrial complex and the normalization of algorithms in the everyday lives of citizens. Although he was an educated whistleblower, his predictions were ultimately ignored, the field of artificial intelligence remaining closed off from outside criticism.

• Control of Personal Data/Identity
• Limitations of Digital Technologies
• Machine Learning
• Recommender Systems

• 
• 7 min
• The New York Times
• 2021

On October 4th, 2021, Facebook’s servers experienced an outage which left its apps, including the commonly used Facebook, Instagram, and Whatsapp, out of commission for several hours. The problem is said to be caused by a incorrect configuring of Facebook’s servers, which ultimately led to a Domain Name System error in which the numerical IP addresses determined by the computer became inaccessible. The myriad effects of this outage spread across the globe as businesses were effected by the lack of access to these social networks. Additionally, certain other internet services linked to Facebook became inaccessible.

• Global Impact of Technology
• Tech Monopolies
• Social Networks
• Networks

• 
• 7 min
• Chronicle
• 2021

The history of AI contains a pendulum which swings back and forth between two approaches to artificial intelligence; symbolic AI, which tries to replicate human reasoning, and neural networks/deep learning, which try to replicate the human brain.

• Singularity
• Scientific Innovation
• Machine Learning
• Networks

• 
• 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.

• Civil Surveillance
• Predictive Policing
• Computer Vision
• Machine Learning

• 
• 7 min
• MIT Tech Review
• 2020

This article examines several case studies from the year of 2020 to discuss the widespread usage, and potential for limitation, of facial recognition technology. The author argues that its potential for training and identification using social media platforms in conjunction with its use by law enforcement is dangerous for minority groups and protestors alike.

• Civil Surveillance
• Algorithmic Bias
• Machine Learning
• Biometrics

• 
• 5 min
• Venture Beat
• 2021

Relates the story of Google’s inspection of Margaret Mitchell’s account in the wake of Timnit Gebru’s firing from Google’s AI ethics division. With authorities in AI ethics clearly under fire, the Alphabet Worker’s Union aims to ensure that workers who can ensure ethical perspectives of AI development and deployment.

• Tech Monopolies
• Technology and Race
• Machine Learning