• 
• 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

• 
• 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

• 
• 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

• 
• 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

• 
• 10 min
• MIT Technology Review
• 2020

This article explains the ethical warnings of Timnit Gebru against training Natural Language Processing algorithms on large language models developed on sets of textual data from the internet. Not only does this process have a negative environmental impact, it also still does not allow these machine learning tools to process semantic nuance, especially as it relates to burgeoning social movements or countries with lower internet access. Dr. Gebru’s refusal to retract this paper ultimately lead to her dismissal from Google.

• Technology Based Environmental Impact
• Limitations of Digital Technologies
• Algorithmic Bias
• Machine Learning
• Data Mining

• 
• 2 min
• azfamily.com
• 2018

Facial recognition technology has found a new application: reuniting dogs with their owners. A simple machine learning algorithm takes a photo of a dog and crawls through a database of photos of dogs in shelters in hopes of finding a match.

• Assistive Technologies
• Computer Vision
• Machine Learning