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 “Skynet” Predicting the Future By Watching the Present

Ronald Saltinski
National University

Introduction
     John Lewis Gaddis in his book, The Landscape of History: How Historians Map the Past, comments that as historians, “Most of us consider it our business, after all, to turn our back on wherever it is we may be going, and to focus our attention, from whatever vantage point we can find, on where we’ve been. We pride ourselves on not trying to predict the future, as our colleagues in economics, sociology, and political science attempt to do. We resist letting contemporary concerns to influence us. We advance bravely into the future with our eyes fixed firmly on the past: the image we present to the world is, to put it bluntly, that of a rear end.”

     Of all the social sciences, historians have been the most resistant to considering or even “experimenting” with modern research techniques involving computer modeling, simulations, gaming, and powerful statistical and information visualization tools. Yet there is evidence that some historians are taping the power of technology to develop scenarios that foresee and predict future events or to put it bluntly, present the world from the “front end.”

“Big Data” and Knowing the Present
     Knowing about something that is going to happened has only been the gift of soothsayers. Economists have often been accurate in their forecast about commerce and finances but even they have been blindsided by unseen meltdowns in the national and global economies. Political scientists have as well been accurate and yet blindsided in their “landscape” of the future. After all, Sputnik was a shock, and no one predicted the fall of the Berlin Wall along with the total collapse of the Soviet Union. That was then and now is now. Social scientists have more analytical power at their fingertips than ever before, power that in all probability would have predicted economic meltdowns and even the fall of the Soviet Union.

     Over the past five years a “virtual” tsunami of digital information via the Internet has cast an increasing shadow over humanity. Everyday there are astronomical increases in the quantity and quality of information in every field of human endeavor - the physical sciences, biosciences, health sciences and the entire spectrum of social sciences and especially the social media - all in the form of “big data” bases. Present day data sets are immensely huge with current limits on the order of terabytes, exabytes and zettabytes of data that grow in size by virtue of the worldwide ubiquitous creation of digital information. From the perspective taken by the World Economic Forum, global “big data” is like a new economic asset like currency or gold.

     Knowing what (almost) everyone is thinking and doing is the stuff of which predicting future history is made. Knowing what people are thinking while inherently a private matter becomes a public matter as soon as people start communicating their thoughts. Knowledge of what people are doing is known by virtue of their movement or mobility. In the past “knowing” was extremely difficult, extremely complicated, extremely limited, and extremely expensive. Today “knowing” is extremely easy, extremely simple, extremely unlimited, and relatively cheap. Today people around the globe “speak their minds” whether by speaking or typing into their iPhones and iPads (or other digital devices for that matter). The world is becoming “the cloud.”

     One example of the huge complexity of “the cloud” is social networking which accounted for nearly 1 in every 5 minutes spent online globally in October 2011 ranking as the most engaging online activity worldwide. Social networking sites now reach 82 percent of the world’s Internet population age 15 and older that accessed the Internet from a home or work computer, or mobile devise, representing 1.2 billion users around the globe. The importance of Facebook cannot be overstated: In October 2011 Facebook reached more than half (55 percent) of the world’s global audience and accounted for 1 in every 7 minutes spent online around the world and 3 in every 4 social networking minutes.

     Mobile devices are fueling the social media addiction: In the United States, 64 percent of smartphone users accessed social networking sites at least once in October 2011, with 2 in 5 smartphone owners connecting via social networking nearly every day. In the Europe, 45 percent of smartphone owners accessed social networks on their mobile device during the month, with nearly 1 in 4 doing so on a near daily basis.

     The problem is locating patterns in a huge unstructured mass of emails and Internet clickstreams in “the cloud” that pose potential scenarios, national and global, for trends and actions across the social spectrum. In the end it comes down to storing everything digital and then analyzing as needed. While “experimental” oriented historians would covet such an opportunity it remains that the capacity to “mine” the “the cloud” lies with the power, money, and resources of governments.

Total Information Awareness - Social Networking Sites (mirror)

Government Surveillance of “The Cloud”
     In 2002 the American government created the Office of Information Awareness whose mission was to monitor and analyze electronic data from a diversity of sources. The program created to meet this need was Total Information Awareness (TIA). The TIA’s mission was to gather and store information across a spectrum of digital activities of every single person in the United States. The intent was to search and screen suspicious activities that might constitute a threat to national security. Congress suddenly eliminated TIA in 2003 amid criticism from the American Civil Liberties Union that TIA was mass surveillance without “warrant.”

     In 2011 TIA arose from the dead in the form of “Data Eye in the Sky” created by an agency of the U.S. Defense Department, the Intelligence Advanced Research Projects Activity (IARPA), to institute a  “data eye in the sky” project that would automatically collect information from the vast ocean of Internet-based social media including “digital trails” generated by billions of cell phones. The “data eye,” presumably a next generation surveillance satellite, will focus on corralling patterns of digital interactions that are then transmitted to supercomputers to analyze in such a way as to predict a host of future events - events in the national interest.

     In 2012 the fictional portrayal of an artificial intelligence system, Skynet in the trilogy of films, The Terminator, may become a reality with the National Security Agency’s (NSA) project Stellar Wind. James Bamford reported in Wired Magazine that project Stellar Wind will be situated in an underground bunker called the Utah Data Center complete with advanced supercomputers capable of collecting, storing and analyzing over 966 exabytes  (1018 bytes) of data per year of global Internet traffic. The facility will be capable of storing yottabytes 1024 bytes of information deemed appropriate for later scrutiny.

     Stellar Wind is reflective of George Orwell’s 1984 where “Thoughtcrime was not a thing that could be concealed forever. You might dodge successfully for a while, even for years, but sooner or later they were bound to get you.” In 2011 John Villasenor in a study for the Center for Technology Innovation at Brookings found that “For the first time ever, it will become technologically and financially feasible for governments to record nearly everything that is said or done within their boarders - every phone conversation, electronic message or email, social media interaction, and the movements of nearly every person and vehicle, and video from every street corner.”

Psychohistory and “The Cloud”
     If historical events take place because of “stuff” happening in an interwoven complexity of voluntary and involuntary actions and choices between the living organic world and the inorganic world of nature than if a formula could be derived from past historical events than future historical events could be predicted with great certainty. A systematic analysis of the maze of information about human dynamics integrating information about the physical world of nature, climate, etc., could provide a predictive pathway to future events.

     Science fiction writer Issac Asimov (1920-1992) in his 1951 novel Foundations imagined a form of “psychohistory” that “By combining the disciplines of history, sociology, and statistical analysis, future predictions about the behavior of large masses of people could be deduced.” “While one cannot foresee the actions of a particular individual, the mathematical analysis of large groups of people could predict the general flow of historical events.”

     Issac Asimov notion of “psychohistory” became feasible with the rise of the Internet and “big data.” Now, the social sciences have access to immense masses of data from all regions of “the cloud” of which a significant amount is social media. Psychohistory called for a huge (if not galactic) population for meaningful predictions of historical events. That requirement is more than sufficiently satisfied by the tsunami of information that flows across the Internet every nanosecond.

     The day is at hand when a “Machine That Would Predict the Future” has arrived. If you dropped all the world’s data into a black box, could it become a crystal ball that would let you see the future -- even test what would happen if you chose A over B?” Dr. Dirk Helbing of the Swiss Federal Institute of Technology has been funded with over a billion euros to create a massive computer system, the Living Earth Simulator (LES) that would model global-scale systems - economies, governments, political upheavals, cultural trends, epidemics, agriculture, climate, technological events, and more – using “torrential data streams, generated from formal form sources as well as social media in all forms.”

     Dr. Helbing discusses the nature of the LES and the benefits of managing the future via “the cloud” on YouTube.

     The LES will require an immense amount of computing power requiring shared information from supercomputers around the world creating a new Global Participatory Platform. Increasing the accuracy with which to predict the future will not come cheap. Machines already exist that can easily “digest” and analyze the “big data” at petaflops or 1015 floating point operations per second. More powerful 1018 exaflop machines are on the way. At the present time Japan holds first place for global supercomputers with the Fujitsu K Supercomputer with China close behind (Top 500 Supercomputers). The cost for such machines exceeds 100 to 200 million dollars.

     Issac Asimov’s psychohistory may have already become a reality with the prediction of recent revolutions in North Africa and Yemen (2010-2011). The Illinois Institute for Computing in the Humanities, Arts, and Social Sciences (Kaley Leetaru) conducted a massive analysis of documents over the past twenty years with day-to-day analysis of related regional social media (mostly Tweeter, emails, and cell phone activity) associated with North Africa and the Middle East. The researchers referred to this effort as “automated sentiment mining” and the reward was a prediction of violent revolutionary actions in Egypt and Tunisia weeks before they occurred.

     Another aspect of recent social upheavals in North Africa and the Middle East was determined in a study, Time-Critical Social Mobilization that found the Internet to have the capacity “to harness the collective abilities of large numbers of people to accomplish tasks with unprecedented speed, accuracy, and scale.” Monitoring and analyzing the manner and pace in which societies mobilize via “the cloud” will be the stuff of which the Living Earth Simulator may well antiquate or renovate the careers of historians.

Unique Research Tools to Analyze “The Cloud”
     In addition to computer power there will be the need for new and more exacting research tools to investigate large data banks. The most crucial tool requiring magnitudes of new and novel analytical power will be statistics. Marie Davidian and Thomas A. Louis in a recent editorial in Science said, “Big Data payoffs can be enormous, but there are many pitfalls. The potential for false discovery looms large.” Both Davidian and Louis further stress, “Close collaboration with statisticians is the best way to ensure that critical issues are identified and solutions found.” The capability to manage numerous variables in correlation statistics has been advanced by a suite of statistical tools called “Maximal Information-Based Nonparametric Exploration,” or MINE. The Broad Institute of MIT and Harvard University designed MINE statistical tools to “mine” huge masses of data seeking and “tease” out hidden relationships. The Broad Institute states that MINE is “essentially an “experiment” in a new way of doing science,” generating new ideas and connections that were ordinarily not readily apparent.

     One of the most promising research tools in recent years to investigate “big data” has been information visualization - visual representations that replace cognitive calculations with simple perceptual inferences that enhance comprehension for optimizing conclusions and decision-making. Information visualizations provide an ability to see clearly and intuitively interesting opportunities in large data sets, “big data,” that otherwise would remain hidden and unavailable for further investigation.

     For a quick and entertaining introduction to InfoVis via YouTube watch “Effective Information Visualization” by Matthias Shapiro:

Effective Information Visualization by Matthias Shapiro

     The IBM web site Many Eyes provides open resources for representing data in diverse visualization forms as well as using visualization tools to investigate large data sources. Tutorials and numerous examples and databases are provided for practice. The site also allows different persons to interact collectively for a given visualization-based research project. Many Eyes is free.

Conclusion
     Given the power of supercomputers and the “big data” generated by the “cloud” few doubt the ability to predict and perhaps influence the future of history. Machines like the Living Earth Simulator and their descendants will in all probability prove very accurate in foreseeing the future. There is only one unsettling quandary about cloud computing that is shared with quantum mechanics. The public report of the conclusions from “cloud” analyses can alter the conditions of the model that brought forth the conclusions. Alessandro Vespignani, Director of the Center for Complex Networks and Systems Research at Indiana University (Machine That Would Predict the Future) considers the quantum-related problem with “How can we develop models that include feedback loops or real-time monitors that let us continuously update our algorithms and get new predictions” even as the predictions affect their own conditions?

     Another issue is will society and policy makers actually consider and act on what machines like the Living Earth Simulator predict and foresee? Consider the universal agreement among scientists that climate changes posse extreme danger for the Earth and yet political policy makers refuse to plan for what will probably have cataclysmic consequences for global society in the near future.

References

American Civil Liberties Union. What is Wrong with the TIA Program. Retrieved from
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Asur, Sitaram. & Huberman, Bernardo, A. (2010). Predicting the Future With Social Media. HP Social Computing Labs. Retrieved from http://www.hpl.hp.com/research/scl/papers/socialmedia/socialmedia.pdf

Ball, Phillip. (2010). The Earth Simulator. New Scientist. 208 (2784)

Bradford, James. (2012, March 15). Inside the Matrix: NSA Stellar Wind. Wired Magazine.

Davidian, Marie and Louis, Thomas A. (2012, April 6). Why Statistics? Science. 336, 12.

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Gaddis, John Lewis. (2002). The Landscape of History: How Historians Map the Past. Oxford University Press: New York, NY.

Helbing, Dirk. (n.d) Complexity, Society and the Living Earth Simulator. YouTube Video:
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I.B.M. Many Eyes. http://www-958.ibm.com/software/data/cognos/manyeyes/

Leetaru, Kalev. (2011, September 5) Forecasting Large-Scale Human Behavior Using Global News Media Tone in Time and Space. First Monday, 16.

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World Economic Forum. (2012). Big Data, Big Impact: New Possibilities for International Development. Retrieved from
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