By Desiree L. DePriest, Purdue University Global

Human knowledge is said to have its origins in curiosity, heritage, or traditions. The need to survive created the hunter-gatherers, where tribes were formed, and food was shared. This human interaction required a common alphabet, language, or device among tribes. We did survive, and knowledge went forward. 

Philosophers’ knowledge initiated devices of the current or ancient belief systems be it African mythology, Indo-European, or medieval esoterica. Families, friends, and colleagues sit in discourse to exchange knowledge that came before them to this day. Socratic methods, Newton Optics and other philosophies of The Royal Society, APA-scientific formatting and various forms of mathematics used in political, religious, ritualistic or otherwise, are communicated upon devices. Until now, we have assumed it was the humans that prescribed, predicted or prophesized our common knowledge, but what if it is no longer that way?

Figure 1.  1044 by x6e38 on Flickr 

 

Algorithms are the math that computer devices use to organize knowledge. These algorithms are shaping our world through technologies of all kinds. Our communities are networked through devices that welcome us with advertisements, cookies (Hansel and Gretel-like electronic trails), bit torrents (descriptor nodes acting as seeds to send or receive files), and terms of service to sell your information. All of these are developed with algorithms. 

We cooperate with algorithms ad infinitum when a search engine or virtual assistant predicts our curiosities, or when automatic vacuum cleaners strategically mow our carpets. One could argue there is no reason for concern in all of these conveniences and to suspect encoding and decoding beyond life as normal is taking technology to the extremes. As centrism erodes, technology is being taken to the extremes.

Predictive and persuasive analytics are gathered from the algorithms designed to seduce and then commit the user to a certain way of thinking. This requires an interruption extreme enough to attract your attention to an ad, which gets distributed through your friend or email list, which sells more products or knowledge, and to make a profit (Godin, 2003). Ideas that spread win by attraction, regardless of what they are if they are extreme. The sale that is 70% off, the headlines poisoning the atmosphere by attacking the disabled, gold star parents, Muslims, Mexicans, Blacks, women, the press, or the rule of law are all extremes that attract attention. These are all algorithms sent through social networks and mass media, many of which are known by name. 

Netflix calls its algorithm “Pragmatic Chaos” which achieves a prediction accuracy improvement of more than 10% over their former algorithm (Piotte and Chabbert, 2009). Other algorithms are set forth under names such as Black Box, Boston Shuffler, The Knife, and Carnivoire (Slavin, 2011). 

 

Figure 2.  Spiral Fractal Pattern (Pixabay)  

The days of assuming that the human is guiding their own consumption are over. It is logical to consider that unaware humans are reacting to algorithmic combinations having a collective existence that affect us neurologically. It stands to reason that certain knowledge can cause joy or pain. Things seem to be speeding up, we are Pavlovian responders who are never too far away from our devices. Rheingold applies “The Tragedy of the Commons” where humans despoil any common pool even at cost to themselves; which shows activity in the reward center of the brain (2005). The algorithms in extremes create a physics of culture where human thinking attempts to absorb knowledge in milliseconds and microseconds (Slavin, 2011). The farther away from a signal, the longer it takes to get it and our mind/brain wants to receive it faster and even faster (Swartz, Stapp and Beauregard, 2003). This is the case with servers and their clients, VPNs and the new normal of human social networks. The technological ambition is to make every human being on the planet close to a server even if these are laid on the bottom of the ocean (Slavin, 2011). This suggests our initial relationship with larger less invasive algorithmic devices has now become smaller chips or photons yet faster, more efficient and more profitable. 

Social media companies who continue to say the user has choice fails to explain the choice is signing the terms of agreement, i.e. agreeing to the algorithms coming at you, or not having a presence on the site at all. If you do not sign the user agreements, you cannot use the service. It is the same with any website from ecommerce, health or insurance systems, political organizations to consumer cards, and ordering food or drivers. Travel sites, any kind of internet searches, and any e-store. All buy and sell your information, interrupt and seduce users, grab your friend list, and then interrupt and seduce them. Advertisers depend on like-demographics spreading the knowledge among them. Christakis, in the talk on Hidden Influences of Social Networks suggests that these connections create emotional contagions in human populations to four degrees of connection depending on location (2010). Similar to quantum entanglement, the tendency of individuals to associate and bond with similar others was found in 57% of Christakis’ research. This indicates the possibility of a strong correlate in buying habits, obesity and more importantly in consciousness. This allows the algorithm to embed in clusters of human consciousness and iterate at the fringes (Godin, 2003). Rheingold takes it a step further with algorithms that spread capitalism through new forms of wealth like Google’s AdSense (2005) in sites with thousands of followers. The pattern of collaboration, human communication, the way we now socialize and a variety of participatory media all have their bases in transitive and metacentric algorithms.

The notion that all physical behavior is explainable in principle solely in terms of a local device or algorithmic process is a holdover from physical theories of an earlier era (Swartz, Stapp and Beauregard, 2003). This paper is not suggesting we are all cyborgs in the traditional sense. Technology is evolving us into screen-staring, button-clicking new versions of human beings. We now rely on "external brains" (cell phones and computers) to communicate, remember, and even live out secondary lives in ambient intimacy (Case, 2011). Maintaining healthy curiosity, heritage or traditions requires control of our own decisions as much as humanly possible. Awareness of the algorithmic revolution worldwide gives humans’ choices between being totally hardwired by devices or taking the time to smell the flowers.

 

Case, A. (2011). We are all cyborgs now. Retrieved from https://www.youtube.com/watch?v=z1KJAXM3xYA. 

Christakis, Nicholas. (2010).  The Hidden Influence of Social Networks.   https://www.ted.com/talks/nicholas_christakis_the_hidden_influence_of_social_networks

Desjardins, J. (2014, June 10). How algorithms have changed the face of Wall Street. Retrieved from http://www.visualcapitalist.com/algorithms-changing-wall-street/ 

Godin, Seth (2003). How to get your ideas to spread.  https://www.ted.com/talks/seth_godin_on_sliced_bread#t-161923

Piotte, M. and Chabbert, M. (August 2009). The Pragmatic Theory solution to the Netflix Grand Prize. Retrieved from https://www.netflixprize.com/assets/GrandPrize2009_BPC_PragmaticTheory.pdf. 

Rheingold, H. (February 2005). The new power of collaboration. Retrieved from https://www.ted.com/talks/howard_rheingold_on_collaboration.   

Slavin, Kevin (2011). How Algorithms Shape our World.  https://www.ted.com/talks/kevin_slavin_how_algorithms_shape_our_world.

Swartz, J.M., Stapp, H.P. and Beauregard, M. (2003). Quantum physics in neuroscience and psychology: a neurophysical model of mind/brain interaction.  arXiv.org.  Retrieved from https://arxiv.org/abs/q-bio/0401019.  

Dr. Desiree L. DePriest is an IT/AI and instructional design professor at Purdue University Global (formerly Kaplan University) for 13 years. Desiree’s expertise is in information systems and artificial intelligence in business environments.  She holds a Ph.D., in Management & Organization with emphasis in Information Technology, along with two masters degrees (Telecom and IS respectively). Desiree has a Bachelor of Science degree in psychology and two certificates in ABA and I-O psychology which greatly assist in her work in the various areas of business intelligence, industrial and organizational motivation and attitudes. She is the Vice-chair of the IRB. Desiree created Purdue Global Internship Program – Technology (PGIP-T) (formerly KapTechnology) which is an internship for IT and business students wanting real world experience prior to graduation. She also created the Graduate Information Technology Association (GITA) and serves as Faculty Advisor. Desiree recently won the “Best Practices” award for her work in the internship from the American Association of Adult Continuing Education (AAACE). 

Her publications include research in persuasive and predictive analytics, artificial intelligence and augmented reality, and pattern recognition. Desiree’s recent interests have expanded to neural correlates of consciousness (NCC), quantum teaming (QT) and cognitive coupling (CC). Quantum Teaming is the equivalent to other quality management methodologies with particular focus on virtual team environments. Desiree presents throughout the year at conferences in these areas.  She is the author of Quantum Teaming: The Primer, available on Amazon.com.

Dr. DePriest will be presenting on this topic at 8 a.m. on Thurs. (Aug. 2).  All are invited to attend.  

She may be reached at dumanbeing@gmail.com.