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Ancestors & Algorithms

A collection of observations draws together contemporary political events and ancient future-telling practices. These can be considered human and non-human strategies in forecasting what a political future might look like – for better or worse.
In 2000, Dan Greaney, the writer of The Simpson’s cartoon, imagined Donald Trump as the president of the United States in the episode Bart to the Future, and he admits that the idea “was pitched because it was consistent with a vision of America going insane”1. The show creates an unimaginable scene, the embodiment of its viewer’s worst nightmare and hilarious fantasy that has since become reality.
A global dissatisfaction with liberal democracy has cleared the political stage for right-wing populists such as Trump and many others to propagate their ideals of white supremacy, harking back with nostalgia to a time of proposed prosperity, jobs, safety and “greatness”2which has never existed in the manner which they suggest.
Timothy Snyder, a historian from Yale University, names this brand of propaganda, the “politics of eternity”3 by way of describing the rhetoric’s endless loop of reference to the past in reaction to the liberal democracy of the present. He proposes that the biggest challenge in moving forward into the future is to avoid unconscious and gradual slippage into the  “politics of eternity” becoming the status quo. Our collective challenge will be to remind ourselves that there was a moment in history when other political constructions were viable.
Political forecasting, via highly targeted use of big data, otherwise known as micro targeting was put to use on an unprecedented scale during the 2016 United States Presidential election campaign. Mass collection and use of the data of millions of American’s credit card spendings, shopping habits and Facebook preferences to name a few were mobilised and analysed by both democrats and republicans to manipulate voter behaviour, suggesting that the future of political power rests in the hands of the party or candidate with valuable access to the most sophisticated tools, namely algorithms for analyzing personal and therefore psychological data derived from citizens without them even being aware of it.
Writer and media scholar Richard Grusin reflects on the use of media by Trump’s campaign in the run up to the 2017 election results. He names it a strategy of “evil mediation,”4 a term coined by Matthew Fuller and Andrew Goffey’s book Evil Media 5. He highlights several key aspects believed to have greatly influenced Trump’s win. A major factor was that the Trump campaign managed to permeate and fill all forms of print and digital media landscapes regardless of the content or political message appropriateness. He successfully managed to be published and re-published endlessly by haters and fans, which effectively resulted in him dominating and drowning out all other political voices. Grusin claims that regardless of if the American public supported him or not, subconsciously and perhaps even unwillingly they had already witnessed him populate and dominate all media platforms, making it seem as if his presidency was imminent or inevitable.
Grusin believes that Trump’s campaign was greatly enhanced through “non- representational and non-cognitive means by capitalising on the affective immediacy of our social media and the elusive violence that can be enacted on its users.” Trump paid millions of dollars to a London-based company called Cambridge Analytica, who seem to be in possession of the data of most voting Americans, to implement personality-targeted marketing to create and enhance network neighbourhoods. On the corporate website of Cambridge Analytica 6, the company boasts to have aided greatly in Trump’s victory, and openly explains its policy of creating algorithms to control voter emotions, through timely and psychologically manipulative placement of social media advertising.
Political propaganda may have been understood in the past as implementation of persuasive images, stories and arguments have taken on a far more elusive and monstrous form. Vast networks of data, which citizens have willingly or unknowingly contributed to data banks are correlated and analysed by companies. Data is consequently transformed and mediated back to us in the form of manipulative, false and highly targeted computational propaganda, which morphs and evolves as our cookie trail travels through cyber-space. Whichever candidate or party can obtain the most targeted and detailed version of algorithm technology is the ultimate winner.


Predicting the future has not always been determined by artificial intelligence. Ancient civilizations have channeled and mediated through their ancestors in much the same way as we turn to technology today to provide answers in uncertain times.
During the Shang dynasty in Ancient China (1600 BC–1046 BC) kings and divinators or oracles would ask their ancestors questions in order to answer important political questions. Queries included “Will we win the upcoming battle?”, “How many soldiers should we commit to the battle?”7 “Why does the king have headaches?”. In their search for certainty we are reminded of Google searches to find answers about diseases or relationship problems, ancestors were being tapped into for their databank of life experience and wisdom. Questions were carved onto oracle bones made from ox scapula or turtle shells and during a ritual which evoked the ancestors, a sharp tool in combination with intense heat was plunged into the bone. According to the patterns of cracks, which appeared on the surface of the bone, future predictions were interpreted by the king or the divinators. Answers to questions were consequently carved into the bones too, and today provide the earliest and most extensive record of the Shang dynasty.
In Ancient Egypt dream interpreters, who could function as priests, surgeons, herbalists and teachers were considered a valuable tool for future guidance. Dream temples were the single most popular spiritual healing institution in the Mediterranean world and were restful sanctuaries designed to induce, incubate and interpret dreams using early forms of hypnosis. Visitors would be put to sleep, after which dream healers would interpret their trip to the “underworld”8 and successful cures were honored with inscriptions on the walls of the sanctuaries, acting as proof and advertisement.
The most well-known example of dream translation to influence politics may be the story of Joseph’s dream interpretation from the book of Genesis in the Bible. Joseph interprets the Egyptian pharaoh’s dream, predicting a serious future drought in the country and as a consequence, the pharaoh was able to prepare by storing food. Dreams and their meanings were archived and categorized as good or bad omens in the Egyptian Dream Book, a hieratic papyrus that probably dates to the early reign of Rameses II (1279–1213 BC).
In Ancient China and Egypt alike, a select few had access to knowledge and methods of extracting meaning from mystical rituals, a lot like the computer scientists of today, it depended on who controls information and what their intentions were, as to how predictions would influence politics. In South Africa today, practices of traditional healing and forecasting are used broadly by more than half of the population with healers outnumbering traditional doctors of Western medicine. The rituals, spells, forecasts and muti (traditional medicine) which Sangomas or inyanga prescribe are highly revered and feared in many communities.
A typical session would include the throwing and reading of bones, dominoes, dice, coins, shells and stones and depending on how they fall, objects would channel messages from the visitors ancestors. Today there remain strong links between Sangoma powers and politics, especially considering that most politicians such as president Jacob Zuma grew up in communities where traditional healers played a central role. President Zuma has faced various corruption, rape and fraud charges, which he continually manages to evade and which have consequently earned him the nickname and twitter hashtag #Phunyu-kabamphethe (escape when caught). This Zulu term refers to Sangoma muti “which is used by criminals to make either their victims or charges placed upon them, miraculously disappear.”9
Channeling ancestral knowledge and predictive algorithms show an innate human desire to draw sense from a world, which is incoherent and unpredictable by means of mysterious and complex technology. Then and now, our strategies face many of the same problems. The guru, dream interpreter or the analyst channeling information might take on a neutral or objective position in scraping, seeing or collecting data, but it is the translation or compilation of the information by the king or the political party and their desires, which determines the power that information potentially holds.
Having said that, there is an alarming amount of blind trust that is placed in algorithmic results. Trump is known to have arranged and continuously altered his rally location appearances 10 during the 2016–17 campaign depending on up-to-the-minute data determined by Facebook engagement measurements ahead of the event. The non-human power of analytics might have been an accomplice to him being in the right place at the right time and gaining power, but would the non-human also have been to blame if things had not gone according to plan? South African parliament is no stranger to the mention of mystical practices during political debates; in 2015, president Zuma was questioned in parliament about his ongoing dubious links to the licensing of mines, and when it happened that he could not answer a difficult question, he simply replied with “I can’t be a Sangoma”11 and suddenly, the ancestors were far too mysterious to comprehend.
GREANEY, Dan. 19 March, 2000. Bart to the Future. Fox Network, USA.
GREASSEGGER, Hannes; KROGERUS, Mikael. 28 January, 2017. The Data That Turned the World Upside Down. Motherboard/Vice online.
KOSINSKI, Michal; MAIER-BORST, Haluka. 7 December 2016. Don’t blame Big Data for Donald Trump. Riff Reporter.
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