A.I. News and the A.I. EconomyJulie Beal The A.I. algorithms are constantly mining the Web, to analyse social media, blogs, and real-time news feeds, to predict the markets; in fact, they price the news. The computers have been programmed to interpret the news, as quickly as A.I. possible, in order to get the edge on trading. The race is on to find the latest technology to gain a microsecond advantage over competitors. Drones and algorithms are now used to source and write the news reports, but could it go even further? Could some of our daily news be covering events that were planned to happen, just to get that edge? Wall Street has changed a lot: the shouting commotion of the stock market has been replaced with the eerie hum of hundreds of computers, housed in large, temperature-controlled rooms. Each computer is running proprietary algorithms, trading at lightning-fast speed. The algorithms these computers operate are so fast that what they do cannot be understood by humans. Were talking thousands of trades per minute. Were talking very clever computers that can understand the news and communicate with each other. Its a game: bids are made, and then retracted, hundreds of times per second, in an effort to fool the other algorithms. They also react to each other, so there are algorithms to try and fool other algorithms, (and create noise in the system), and yet others which hunt them down, called sharks. Then of course there are yet more algorithms to look for the sharks, and so it goes on. Its wild in there. The law cant touch it, because its too complicated. The very best physicists and mathematicians are the only ones who understand the algorithmic programs theyve devised (theyre known as quants). The ones with the most money have the best chance of coming up with the most advanced, and capable, algorithms which trump the rest, and of employing specialist high frequency traders on news(HFTNs) to collect, process and exploit news faster than other market participants. According to the New York Times, Trading on the news The key issues with high frequency trading are speed, specialist knowledge, and the money to pay for super computers and privileged services. It takes 500,000 microseconds for a person to just click a mouse but in this game, traders are paying through the nose to gain even a microsecond advantage over competitors, because being only five microseconds behind the leaders means losing. This has forced traders to co-locate to be near the exchange; the shorter the cable, the better. Its all about, the time it takes to transmit the trade orders to the electronic exchange. Speed to market is a major competitive advantage. The HFT that gets a trade to the exchange a microsecond faster than a competitor wins. Millions have been spent on acquiring sites which are close to the NYSE, but now the leaders of the pack are actually housed in the stock exchange itself. The latest thing is to employ new technology to cover the distance between stock exchanges. Getting the news Another way to acquire a competitive edge in the markets is to be the one with access to the primary source for the news, which comes from private data providers, and includes press releases, government statistics, and business news. A two-tiered system has emerged, where certain companies can pay to get their news faster than (almost) everyone else. After all, A company called Anova Technologies provides the latest technology to make the speed of news transmission the best it could ever be; aspiring to supply the end-game route, Anova uses millimetre microwaves to reduce the distance covered to, just 2.1 kilometres longer than the theoretical possible set by the curvature of the earth. The company has now teamed with AOptix to offer a hybrid service which incorporates laser technology, to ensure the fastest speeds possible, whatever the weather. Reporting the news Drones are also being exploited for news; there are plans to use them as microwave relay stations to span the Atlantic, as well as to acquire news in the first place. Mini spies will buzz in the skies, to gather and transmit data before others can.Drone journalism is now being taught at the University of Missouris School of Journalism, where students learn how to fly drones to carry out investigative journalism. The university has partnered with local NPR affiliate KBIA, who contributed $25,000 to build the drones for the course. There is also a Drone Journalism Lab at the University of Nebraska-Lincoln, which, teaches students how to operate unmanned autonomous vehicles (UAVs) and how to interpret the footage and the ethics using the military robots, as well FAA regulations. The idea being, as with all drone use, that it is safer than sending in a human. Its also cheaper for the news agencies than flying helicopters and paying staff. Besides, according to Harley Geiger, a policy attorney with the Center for Democracy and Technology in Washington D.C., (Watch out for the nano humming birds, funded by DARPA! They can fly inside or outside, forwards, backwards, or hover.) Understanding the news Another important aspect to creating the news is understanding the sentiment of the market; advertisers, researchers, governments, corporations, law enforcers, and the military, regularly mine social media and news articles to gauge the overall mood of the public, and therefore how they will react to a given stimulus. Thomson Reuters News Analytics uses Lexalytics natural language processing system to process and score text for: Sentiment analysis is fundamental to understanding the markets; it has always been the mood of the markets which drives trade on the stock exchanges. But now, sentiment analytics can be used to track and predict the Dow Jones on a daily basis with 88% accuracy, i.e. there is a correlation between the two. Companies such as Lexalytics can analyse data for content and meaning, looking for keywords in headlines, such as rumour, or panic, and especially for information released by the government, police, and corporates. However, texts can be ambiguous, so programs are written to cope with sarcasm, etc. Theyre even able to analyse public statements by corporate bosses, and check them for honesty! Thomson Reuters MarketPsych Indices (TRMIs) tracks and quantifies attitudes, tones, themes, and other psychological aspects. Plans are now afoot to write programs which canautomatically digest broadcast and closed-caption television. Of course, these techniques may not necessarily be used in isolation Lexalytics was put to use to track activists at the NATO summit, building identity profiles of individuals by combining realtime social media monitoring with sentiment analysis. Crafting the news When attributes of an identity are gathered through multiple forms of surveillance, they begin to tell a story about that person; in the same way, elements of news data can be reformulated as a story, or news article. Meaning is extracted, and crafted to form a new narrative. This is the art of storytelling, turned into a science by the likes of DARPA, which has been very busy uncovering the universal properties of narratives, with the aim of promoting preferred ideologies within given cultural populations. Theyre interested in how people react psycho-chemically and behaviourally to the news they hear, the stories theyre told, and how these can be shaped so as to control societies or individuals. Stories have been found to influence peoples emotions and cognition; their decision making, memory, and reasoning, and the formation of identity.The perspective from which a story is narrated is also crucial. Stories can trigger neuro-chemical responses, which then influence the behaviour of an individual. The release of dopamine, for instance, can be triggered by a story, and is linked to the reward mechanism in the brain. Oxytocin is another commonly triggered neurochemical, linked to the modulation of trust. Telling a story right could mean winning hearts and minds: SEE PROPAGANDA 2.0 FOR SHEEPLE! The logical structure (i.e. plot) of narratives has been found to have universal patterns, typically following Freytags triangle, of beginning, middle, and end. Scientists are able to map these patterns as narrative networks on computers, and manipulate their elements in such a way as to exploit their effects, such as carrying a message or moral. The reactions of the viewer are mostly subliminal; you dont even know its happening. News articles are just one type of story, as are the stories we tell each day to recount our experiences, and to make sense of the world. The art of storytelling is also being used by marketers to bring life to brands, and by policy makers seeking to influence opinion. Narrative networks can be modelled using universal plot lines and even characterful expressions, which can then be used to generate reports from news data fed to them in real-time. So not only are there programs which can read the news, there are programs which can actually write the news. No human involved, just data being processed and re-hashed as articles for humans to read, and traders and algorithms to react to. Narrative Science is a company which can generate content in article format from large data sets; in fact, the company offers the service as a way for corporations to make sense of the mass of information now available. Re-formulated as a story, the data is manageable and therefore rendered as actionable intelligence, rather than a big confusing mess. Narrative Science is able to manufacture tailored stories from any given data set: When asked what percentage of news would be written by computers in 15 years, Kristian Hammond from Narrative Science sighed and said, More than 90 percent. (When you control the narrative, you control the conversation, Rick Horowitz) Making the news? Buy the rumour, sell the news sums up a well-known trading strategy, handed down from Richard Wyckoff in the 1930s, and refers to the ability to profit from rumour headlines and timely action in the stock market. The flash crash of 2010, when the algorithms simply walked away from the market has heightened concern about thevulnerable state of the financial ecosystem, in which algorithms are able to, Like the other global ecosystems, it has gotten too complex, and that makes it weak. Now that flash crashes are only a tweet away, news management has reached its most critical stage. A.I. news and the A.I. economy make up a global, digital,trackable ecosystem which can be manipulated (whatever the currency) using the tools of complexity science, but no-one can watch the algorithms, and, as long as theres competition, the game is on. The possibility therefore remains that some might want to go one step further, and actually create the news in the first place. After all, you cant beat that, can you? FURTHER INFORMATION AVAILABLE IN THESE VIDEOS: TEDxNewWallStreet Sean Gourley High frequency trading and the new algorithmic ecosystem:http://www.youtube.com/watch?v=V43a-KxLFcg Kevin Slavin: How algorithms shape our world: TEDxConcordia Yan Ohayon The Impact of Algorithmic Trading: This article first appeared at Get Mind Smart Julie Beal is a UK-based independent researcher who has been studying the globalist agenda for more than 20 years. Please visit her website, Get Mind Smart, for a wide range of information about Agenda 21, Communitarianism, Ethics, Bioscience, and much more. 