Algorithms Versus Hive Minds: A Premonition of Democracy's Future

Algorithms Versus Hive Minds: A Premonition of Democracy's Future

Rick Searle (Institute for Ethics and Emerging Technology, Willington, CT, USA)
Copyright: © 2016 |Pages: 13
DOI: 10.4018/IJT.2016070103


From the time of its emergence onto the public scene the Internet has been understood in light of both its dystopian potential for total surveillance and control and its utopian possibilities to enable enhanced forms of freedom. This paper argues that these two potentials are deeply interconnected and that the both the field of Technoethics and long term sustainability of democracy itself requires that we understand and address the connections between our fears and hopes regarding the Infosphere.
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Surveillance Society And Rise Of Algorithms

Not all that long ago, people talked of the Internet as if it were a new and distinct domain- cyberspace- something separate from the real world with which we had long been acquainted. That is no longer the case, for what has happened over the last generation is that cyberspace has consumed the real world, it has become the overlay through which our reactions with reality are mediated. (Wertheim, 1999)

A peculiar model of how this mediation should work is now found across multiple domains. It is found in the way security services operate, along with much of finance and commerce; it is the basis for new ways of responding to crime, and is deeply influencing the way we organize the cities of our increasingly urbanized planet. It is ultimately a model of power that has been made possible by the shrinking size of computer components and the spread of ubiquitous connectivity. It is a model that bears a chilling resemblance to Pesce’s feared panopticon.

Well before the Snowden revelations, in an article largely ignored, James Bamford laid out how the NSA had built a massive data center in the desert of Utah where:

.....the NSA has turned its surveillance apparatus on the US and its citizens. It has established listening posts throughout the nation to collect and sift through billions of email messages and phone calls, whether they originate within the country or overseas. It has created a supercomputer of almost unimaginable speed to look for patterns and unscramble codes. Finally, the agency has begun building a place to store all the trillions of words and thoughts and whispers captured in its electronic net. (Bamford, 2012)

Subsequent revelations would uncover just how deep the tentacles of this architecture

surveillance went, and just what a danger it was to traditional notions of privacy and civil liberties. Yet, as to the question of who had built this architecture, who had planted us with devices that recorded where we were and the people we interacted with: we had done it to ourselves.

The NSA could only even imagine building such a system because the private sector had been permitted to build an entire communications architecture on the basis of mass surveillance. It had taken the aftermath of dot com bubble and bust for companies to come up with a model of how to monetize the Internet, and almost all of the major tech companies that dominate the Internet, at least in America- and there are only a handful- Google, Face Book and Amazon, now follow some variant of this model.

That model was to aggregate all the sharing that the Internet seems to naturally produce and offer it, along with other “compliments” for “free” in exchange for one thing: the ability to monitor, measure and manipulate through advertising whoever uses their services. (Economist, 2012) The model went by the name of “personalization” and demanded in the words of Kevin Kelly: “... total transparency. That is going to be the price. If you want to have total personalization, you have to be totally transparent. (Stibel, 2009)

The idea of ubiquitous monitoring only made sense if the flood of information it produced could be effectively organized and searched for valuable pieces of data.

Here was where the revolution in algorithmization and artificial intelligence came into play. In the early 21st century much of individual social interaction came to be mediated by sorting algorithms from recommended movies to selected books, music, and even lovers. (Steiner, 2012)

Monitoring of individuals allowed them to be classed as “types” on the basis of which those individuals became “targets” for, among other things, products, criminal investigation, or scams. Due to the fact that the Internet had become one of the primary ways the individual interacted with the world algorithms defined who an individual was, if not to herself, then for others. (Pariser, 2011)

In this era of “Big Data”, power flows towards those able to identify and act upon meaningful patterns. This has meant the empowerment not just of those with the best algorithms at discerning patterns, but of those that can act upon this information with the most speed. The area where such algorithmization is furthest along is in finance. (Patterson, 2010)

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