What’s Old is New (and Conglomerated into 4 Mega Corporations)

Cloud computing makes a lot of sense. When you think about all the computational power that is lost Simply because no one is using the system, you begin to see one of the major benefits of cloud computing: more computational power and storage available to more users at a cheaper price point. This idea has deep roots within the history of computation, going as far back as the 1960s with the implementation of time-sharing as a revolution of accessibility to computational power. Timesharing allowed “a central computer to be shared by a large number of users sitting at terminals. Each program in turn is given use of the central processor for a fixed period of time” (Arms). This computational model was efficient when computers were unruly and expensive. Gradually, the minicomputer won out over massive mainframe models, and the personal computer became the de-facto form of computation. However, the benefits of sharing powerful resources are again becoming transparent with the contemporary rise of cloud computational models. For better and worse, cloud computation is contemporarily conglomerated into the “big four:” Google, AWS, IBM, Microsoft.

A positive and negative effect of contemporary cloud computing is the standardization of inputs and outputs that a cloud computing model requires. As Ruparelia says, “to truly deploy a cloud, you need to consider how to standardize your service offerings, make them available through simple portals, track usage and cost information, measure their availability, orchestrate them to meet demand, provide a security framework, provide instantaneous reporting, and have a billing or charging mechanism on the basis of usage“ (Ruparelia, Page 7). This standardization means that users do not have access to full power of the cloud computing system, just a mediated form of it as dictated by the big four companies that create the cloud architecture.

One of the most blatant and obvious negatives of the conglomeration of cloud services is the potential for security breaches and a loss of data privacy. When user data is conglomerated into one database or platform in the cloud (one that has linkable personal identifiable information ready and available), a hacker has a large incentive to steal this data. With the implementation of cloud computing, a hacker doesn’t need to hack hundreds of computers before they stumble upon a juicy target; now, a hacker just needs to pwn a single cloud database to steal thousands of users’ information.

In addition to cloud computing increasing the power and ease of the explicitly malicious actors stealing personal information, conglomerated user data in several cloud platforms – especially cloud platforms that have cross-service terms of service and privacy policies– gives heightened power to collect and sell behavioral data. Most of this data is viewed as payment for free services, but many users do not understand the scope of identification that can occur with such data collection. Having different types of data accessible within a conglomerated cloud service increases the ability and efficacy of corporate surveillance.

Arms, W. (n.d.). The Early Years of Academic Computing. Retrieved March 27, 2019, from The Early Years of Academic Computing website: http://www.cs.cornell.edu/wya/AcademicComputing/text/earlytimesharing.html
Blagdon, J. (2012, March 1). Google’s controversial new privacy policy now in effect. Retrieved March 27, 2019, from The Verge website: https://www.theverge.com/2012/3/1/2835250/google-unified-privacy-policy-change-take-effect
Mack, Z. (2019, March 26). Shoshana Zuboff on understanding and fighting surveillance capitalism. Retrieved March 27, 2019, from The Verge website: https://www.theverge.com/2019/3/26/18282360/age-of-surveillance-capitalism-shoshana-zuboff-data-collection-economy-privacy-interview-vergecast
Ruparelia – 2016 – Cloud computing.pdf. (n.d.).
Ruparelia, N. (2016). Cloud computing. In The MIT Press Essential Knowledge Series. Cambridge, Massachusetts: The MIT Press.