How Big Data and Algorithms Are Slashing the Cost of Fixing Flint’s Water Crisis

The Conversation, 09/08/2016

Beyond tech companies such as Amazon and Google, big data has a significant effect on science, engineering, and even plumbing. As the government in Flint, Michigan has worked to correct the dangerous levels of lead contamination reported earlier this year, researchers at the University of Michigan have aggregated and analyzed data for homes in the area. Their analysis is providing new insights into how the government can best direct their efforts, to reduce costs and increase impact.

Stanford Engineers Propose a Technology to Break the Net Neutrality Deadlock

Stanford News, 9/13/2016

The debate over net neutrality has largely focused on whether Internet service providers should allow some content providers to negotiate faster/cheaper access to their content for users. This article describes a prototyped system that would allow users to designate which content they want to special access to. Net neutrality has been seen as a digital divide issue; wide adoption of a user-choice system would change the parameters in that debate.

IoT Early Warning System Helps Save People From Mudslides

Network World, 08/24/2016

This article describes an early warning system for mudslides and flood in rural El Salvador that uses a mesh network of simple devices, within local villagers’ needs and cultural structures. The article can be used to highlight differences between the U.S., where a vast array of technological advances can aid in mitigating disasters, and remote areas of the world where many of the basic technologies involved, such as cell-phone networks, do not exist or are not reliable.

A Beauty Contest Was Judged by AI and the Robots Didn’t Like Dark Skin

The Guardian, 9/8/2016

Beauty.AI developed a set of algorithms to judge photos according to five factors in human standards of beauty; it disproportionately chose photos of white people. The article discusses the potential consequences of emergent bias in algorithms and/or datasets in general, including more consequential examples like predictive policing.

The Ad-Blocking Browser That Pays the Sites You Visit

Wired, 9/1/2016

The Brave web browser (released earlier this year) allows only ads that don’t track users from site to site; it has now added a feature to record how much time users spend on different sites and allow them to send micropayments to those publishers. The article raises examples of how the web has impacted the economics of media and publishing, and also touches on online tracking, data anonymization and de-anonymization, and even Bitcoin.

Inferring Urban Travel Patterns From Cellphone Data

MIT News, 8/29/2016

Researchers are using data on the locations people make calls from to model the movement patterns of Boston commuters; the system may replace or supplement surveys of residents. The article discusses the benefits of gathering and processing more data more quickly and cheaply, though students may be able to identify some disadvantages of using call data.

How an Algorithm Learned to Identify Depressed Individuals by Studying Their Instagram Photos

MIT Technology Review, 8/19/2016

Researchers have developed a machine-learning algorithm that achieves 70% recall in identifying depressed individuals by characteristics of their (pre-diagnosis) Instagram photo posts. This is a great example of a medical development with great potential for benefit (early diagnosis and treatment) that also raises serious concerns (privacy, misuse of the information, misprediction). It’s also an example of Mechanical Turk being used as a research platform.

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