Technological Disasters?

For our next class on April 16, I would like you to reflect upon the “high tech disasters” that we’ve been looking at for the past few weeks, specifically from the perspective of the Algorithms of Oppression reading, the Silicon Valley of Dreams chapter, and the Programmed Inequality reading.

Think about connections between these three, and whether they are similar to, or different from, previous “lower tech”  disasters that we have studied. Choose an article that somehow allows you to highlight an important insight or question that you’ve come up with, as you’ve thought about these disasters, their root causes, and the process of historical change. Upload a link to your article, as well as its title and one sentence on why you chose it, in a comment on this post by April 13th at 5pm. I will look them over and make them visible (so you can read each other’s articles, by April 14th.


Here are a few more articles I thought might spark discussion on the articles the class has provided:

Coding and Coercion (about how tech workers themselves are beginning to rebel against the tech industry; see also groups like Tech Workers Coalition and Listen Up, Tech!)

MySpace Tom beat Facebook in the long run: Wouldn’t you rather be a rich nobody than whatever Mark Zuckerberg is? (about the need to address and account for obsolescence in technologies–instead of getting caught up in the fiction that technologies can function forever)

A Feature, Not A Bug (about how the history of computing gives lie to one of our most beloved fictions: technological meritocracy–and the idea that it can save us)




    This is how much money you’re worth to Facebook. I chose this article because right now Facebook and other large tech companies provide a free service to their users. They in turn then use their user base as their product to make money from advertising. An alternative to making money off selling their users’ information for ads would be to make their users pay for the service. This article breaks down how much each user earns Facebook.


    This article adresses the impact of automation on relative employment levels of genders in the job market. Many jobs based on physical skills are projected to be replaced by robots and AI, which could reduce employment in labor-intensive industries, such as construction, which are typically dominated by men. However, service industries, such as restaurant servers are potentially at risk too, and jobs like this are largely employers of women. The balance of genders employed in the total job market is changing.

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