This last module tackled some issues of the methods that our data is manipulated, and how it came to be that such data came to be synonymous with our being. We delved into some social history that explained the early uses of data acquisition to monitor and act upon certain prejudices. The use and implementation of certain methods to track characteristics; this often seems to be associated with devilish intentions, as is the case with redlining practiced by the bank system in the first decade of the 20^th century. However, not all projects that seek to gather information have these ill intents in mind when setting out. Most projects seek to gain access to this data to better understand or describe a specific trend, modality or occurrence in our environment.

As with any collection of intelligence, it can be used as malignant information for causes that seek to take advantage of, or establish their dominion over, a specific area. All of this becomes possible via our data, it has come to be tantamount to who we are, representing out habits, likes, and agendas. In this age of digital literacy, the fight for who owns this data has been at the center of many great conflicts of our time. It comes to fruition in events like political races and hot topics, where people are systematically categorized or lured away from their belief system to benefit a second party.

The digital age will not bring forth a ‘cyber-war’ for our data, that has already commenced with e-mail tampering and fraudulent scams that rob our identity based on a 9-digit social security. No, the digital age will come to a tipping point where our data will become more valuable than any currency or good. Giving the possessor the ability to control entire populaces based off our 1’s and 0’s our preferences and dislikes.

Macro Mondays theme: Personal dreams
My personal dream is to spread the knowleadge of Creative Commons. Share, remix, reuse- legally
Read more about Creative Commons at http://creativecommons.org

As a creative, the methods of preserving my work have been laid out and practiced by the artist before me for decades. But those same practices were not always the norm, prior to the dawn of Authorship and Creative Copyright, the Internet was a plane full of counterfeit and unauthorized remediation.

The very people that sought to make money, were being cheated from their earnings by innocent and malignant viewers; while some sought to Copy & Paste for the mere liking of content, others sought to monetize the publication of a work and profit from it. Creators a  nd Vendors alike felt the need to lay a foundation for usage in terms of any original content.

Today these copyright and ownership agreements have gone far beyond the intended purpose, corporations and business have come to ‘Brand’ ideas based on the people they hire. An idea is no longer personal, it’s the company’s.

Yet the next phase of this ownership battle extends onto the realm of AI, meaning that there are people trying to create a being who can self-create and copyright it’s entire portfolio of pieces. This however, in my opinion, will be futile endeavor. Not only can an algorithm not create an indistinguishable idea or content, but it can’t seek to gain inspiration in the same methods a human can. An algorithm cannot forge a trend or start an art movement, for the reason that it will only ever create based on what it has learned, what already exists; combining the components in new ways, fashions and sizes. They can never come of age, to form a unique style capable of jump starting an entire generation’s likes and iconic fad.

As a collective mass, we can certainly teach an algorithm the means to identify a major trend or a positive style, but it cannot create a new one, one that appeals to section of society that is too complex to fit into any other category. A machine can only ever replicate and predict, but creation is an innate ability that will only ever belong to conscious beings; of which only those that can facilitate links between X and Y, in a manner that Z epitomizes both, can.

The second module in our curriculum tackled the subject of ‘mapping’, a term that can vary in definition based on the area of focus. To experts like Serena Ferrando and Michael Papio, it might mean a very literal map that holds significant information in a more visual format. Comparatively, Marc Olsen and Massimo Riva might expand the definition to include a detailed view of the text’s spread, identifying underlying patterns and figurative uses of words.

We learned of specific algorithms that are now being applied, and refined, onto thousands of texts from ancient manuscripts; helping to comb through and recognize hidden themes that would not have otherwise been clear. But as we sift through thousands of works, we always run the risk of over accelerating, in terms of mapping and topic modeling, that means that we might overshoot the results of these algorithms, in doing, we can omit hundreds of possible matters.  Queries that aspire to result in figurative or metaphoric instances, might return negligible results, or opposingly neglect related apt information.

Of course, it’s not all overshooting either, these algorithms allow us to analyze massive amounts of texts, plenty more than one could analyze personally in a hundred lifetimes. The methodology might seem bizarre, and even silly at times, but it is an attempt to discover latent messages, hidden throughout the entire body of works by Petrarch or other ancient writers. While this sort of expectation might only come after tens of new refinement stages, it is a much more secure way to gauge the text, in a bias-free manner.

The attempts to visualize a text also tackles a very difficult task, relating the ancient world to the new. Many of the landmarks, locations, or features depicted or written about might have gone with the centuries. So, locating and marking the sites, becomes an ever more daunting task, considering that maps from that era also might not have survived the ages. The module identifies some of the key issues, solutions and discussions/projects pertaining to this idea of algorithmic presented results, many of which use varying categories and types of codes to analyze the different bodies of works.