While checking out "glitch art" on Flickr, I came across this photo set entitled "Flickr coincidences." I'd be interested to see how algorithms and synchronicity study come together in the coming years. Not so much as déjà vu being a "glitch in the Matrix," as it were, but I like the idea of algorithms becoming the foundation for a new form of communication in which we can deconstruct symbols down to their semiotic roots, and begin to map out the synchronous ties that bind:—
Synchronicity is a word created by the Swiss psychologist Carl Jung to describe the alignment of "universal forces" with the life experiences of an individual. Jung believed that many experiences perceived as coincidences were not merely due to chance, but instead reflected the creation of an event or circumstance by the "co-inciding" or alignment of such forces1. The process of becoming intuitively aware and acting in harmony with these forces is what Jung labeled "individuation." Jung said that an individuated person would actually shape events around them through the communication of their consciousness with the collective unconscious2.
Jung spoke of synchronicity as being an "acausal connecting principle" (ie. a pattern of connection that is not explained by causality).
Then add a little pinch of…
In mathematics and computer science an algorithm (the word is derived from the name of the Persian mathematician Al-Khwarizmi) is a finite set of well-defined instructions for accomplishing some task which, given an initial state, will terminate in a corresponding recognizable end-state (contrast with heuristic). Algorithms can be implemented by computer programs, although often in restricted forms; mistakes in implementation and limitations of the computer can prevent a computer program from correctly executing its intended algorithm.
The concept of an algorithm is often illustrated by the example of a recipe, although many algorithms are much more complex; algorithms often have steps that repeat (iterate) or require decisions (such as logic or comparison) until the task is completed. Correctly performing an algorithm will not solve a problem if the algorithm is flawed or not appropriate to the problem. For example, a hypothetical algorithm for making a potato salad will fail if there are no potatoes present, even if all the motions of preparing the salad are performed as if the potatoes were there.
Different algorithms may complete the same task with a different set of instructions in more or less time, space, or effort than others. For example, given two different recipes for making potato salad, one may have peel the potato before boil the potato while the other presents the steps in the reverse order, yet they both call for these steps to be repeated for all potatoes and end when the potato salad is ready to be eaten.
Certain countries, such as the USA, controversially allow some algorithms to be patented, provided a physical embodiment is possible (for example, a multiplication algorithm may be embodied in the arithmetic unit of a microprocessor).