Seth Goldstein

In the beginning there is the Automata.  It is the prime mover: an intention that drives human action.

Over time, the record of these actions, both individually and across people,  establish a unique pattern of behavior that is known as an Algorithm.  In the context of Media Futures, an algorithm is a computing engine designed to process behavioral data and convert it into content that engages ones Attention.

You can imagine an Algorithm like a strange Rube Goldberg machine with a complex set of routers, pulleys and chutes that turn a certain input into an equally certain output. 

Recall our reinterpretation of Hamlet:

We encourage others to participate so that we may consume them
and we make ourselves interesting for the blogosphere.  Your Internet CEO and your Joe Blogger are just different algorithms- two APIs, but to one network.

Each decision that I make as to what to pay Attention to, and the physical gesture that I use to effect this choice (search, click, form, sign in, etc) establishes a little personal algorithm that gets joined with all of my other personal algorithms.  Together, this bundle of personal information algorithms establishes and maintains my persistent, stable electronic identity.  This is a deeper, more authentic version of me than simply a numeric ID that establishes my offline physical presence.  The me that makes me me online is one that I actively create and reinforce every moment based on a series of interlocking gears (which I control based on data I produce).

 

And now if you pull up from the tree of me as an individual to the forest of all of us in society, then you see a much broader fabric.  The fabric represents Social Media, each of its infinite threads representing one individual’s momentary micro algorithmic gesture. 

One would assume that each of these mini decisions was distributed to the edges, and that the control over it was determined by its owner.  But this would be to ignore the gravity of the Attention economy, which is Influence.  On the Internet, Influence is measured by the amount of Attention one gets relative to the amount of information one gives  The most influential online individual is able to syndicate a limited but steady stream of what makes me me-ness through his personal API and nevertheless generate a high pagerank that lands him above the Google fold.

The area that I am most interested in exploring in this current chapter on Algorithm is the rub between what you are searching for and where you emerge from other people’s searches.  This is located between (1) the record of your Attention (for example as expressed recently by AOL through their disclosure of "anonymous" search histories) and (2) the position you occupy within the pagerank universe based on what keywords produce results that point to you, above the fold.

For me,  these keywords might include: "Seth Goldstein"  "Media Arbitrage"  "Algorithm Futures" "Transparent Soft Dollars"

Coming next, a brief history of Algorithm

While the recent inventions of Web 2.0 and User Generated Content (UGC) seem to be radical departures from the computing culture we grew up in, their organic social metaphors are in fact rooted in the beginning of computer science.  In the 1940’s and 50’s work of Alan Turing, John Von Neumann and Norbert Weiner, most discussions of the future of computing evolve into a study of the brain.  The natural automata of human thought, the way in which our ideas express our independence, this is the machine intelligence that technologists tried to design into early computers.   

Alan Turing was fascinated by Automata and its relationship to natural human thought.  In his 1950 “Computing Machinery and Intelligence,” Turing outlined an experiment that was able to determine whether a computing machine could be defined as having the capacity to think.  The Turing test functions as follows: Human “X” and respondent “Y” take part in a teletype conversation, but X cannot know whether Y is human or a machine.   If, after a specified amount of time, X believes that Y has responded like a human, and Y is a machine, then Y can be defined as having that human capacity of thought.

In his biography of Turing, William Aspray writes that this:

“was among the earliest investigations of the use of electronic computers for artificial-intelligence research…He attempted to break down the distinctions between human and machine intelligence and to provide a single standard of intelligence, in terms of mental behavior, upon which both machines and biological organisms could be judged.   In providing his standards, he considered only the information that entered and exited the automata…Turing was moving toward a unified theory of information and information processing applicable to both the machine and the biological worlds.”

The fusion of machine and biology is promoted as a core computer architectural principle in the Interim Progress Report on the Physical Realization of an Electronic Computing Instrument:  Julian H. Bigelow, James H. Pomerene, Ralph J. Slutz and Willis H. Ware; Princeton: The Institute for Advanced Study; 1 January 1947.  This report was prepared for John Von Neumann, and the rest of the IAS authorities, on the development progress of a machine based entirely on mathematical equations.

Left to right: James Pomerence, Julian Bigelow, von Neumann and Herman Goldstine

Von Neumann had joined Princeton’s Institute for Advanced Study as a Mathematician in 1933.  About 10 years later he started concentrating on something less theoretical and more practical (which alienated many of his colleagues): building an electronic computing machine.  This project was a deep meditation on the act of creation.  Some of the greatest minds, across a variety of disciplines (math, biology, engineering, physics) converged in Princeton to help Von Neumann “physically realize” his ideas. 

IAS Report, 1947

According to the report, Organs are:  “portions or sub-assemblies of the machine which constitute the means of accomplishing some inclusive operation or function; as “arithmetic organ.”  Note how the processor in this case is able to extend its influence onto others in an “inclusive operation.”  The organ of social media was anticipated already then, in 1947, even without an Internet to enable it at scale.   

Von Neumann continued to extend his computer research towards an understanding of the human brain.  He described this specifically in his introduction to his 1958 work The Computer and the Brain:

In 1948, Norbert Weiner, the leader of cybernetics wrote Control and Communication in the Animal and the Machine.  His use of the word animal is different than Turing’s logic or Von Neumann’s brain, but he is similarly concerned with the organs of information and their ability to relay information between systems:

“It is a noteworthy fact that the human and animal nervous systems, which are known to be capable of the work of a computation system, contain elements which are ideally suited to act as relays.  These elements are the so-called neurons or nerve cells… The mechanical brain does not secrete thought <as the liver does bile>, as the earlier materialists claimed, nor does it put out in the form of energy, as the muscle puts out its activity.  Information is information, not matter or energy.”

Weiner, Control and Communication in the Animal and the Machine, 1947

In late 2004, the creator of del.icio.us Joshua Schachter described to me that tags were simply crystallized attention.  Both terms interested me: while attention has become my chief investigation, the transparent materialism expressed by “crystallized” has also been a key focus.  When you put these together, you get, in Weiner’s words, a “secretion” of passive behavioral data.

Seth Goldstein, April 2006

Just because a tag is a form of  information doesn’t mean that it lacks physicality  Without being matter or energy, can a tag be made of something else, something that comes closer in nature to mirror neurons?  Attentrons.  Remember that mirror neurons are a form of biological material.  These mirror neurons fire when the subject performs an action, but also when it observes somebody else performing an action.  In this latter case, the successful firing of a mirror neuron is based entirely on its ability to passively mimic the behavior of somebody else.  In this quiet absence of a human impulse, attention is full.

 

If every instrument could accomplish its own work, obeying or anticipating the will of others.  If the shuttle could weave, and the pick touch the lyre, without a hand to guide them, chief workmen would not need servants, nor masters slaves.

So wrote Aristotle of the possibilities of the automaton: an object acting of itself, something bearing the power of spontaneous motion.  The advent of such a mechanism not only promised to change labor – eliminating the need for servants and slaves – but also had the potential to change media production and publication. 

In tracing the development of the automaton from its roots in ritual articulated objects to its contemporary versions, (particularly in the context of robots and models of cellular automata in computability theory and theoretical biology), it is useful to keep Aristotle’s commentary from the fourth century B.C. in mind. 

The history of automata begins with “creation” itself.  Genealogies of these self-replicating objects extend back to the creation myths of every religion and culture – from the story of God’s creation of Adam to the story of Prometheus, who made the first man and woman on earth from clay, which he animated with the fire he stole from heaven.  Moreover, the earliest articulated objects from prehistory of early historic times probably served both artistic and religious purposes: used by shamans, priests, and entertainers, these simple clay or wooden dolls with turning heads, arms, legs and hands could provide the illusion of movement as it occurs in nature, thus adding emotional impact to plays and fables.   

This baker kneading dough is an articulated Egyptian toy, one which was
probably found in the tomb from the time of the XII dynasty onwards.
By being deposited in the tomb, the baker became forever bound to his
master, accompanying him into the Beyond to continue to perform his
duties through the rest of time.

The purposes of automata were not strictly in the realm of morality and spirituality.  Hero of Alexandria (who is credited with the invention of the crank, the cam-shaft and a system of rotations and counterweights, as well as with having demonstrated the principles of the vacuum and the incompressibility of water) used automata to illustrate scientific principles.  In his Treatise on Pneumatics from A.D. 62, he laid out applications of science in the forms of singing birds, sounding trumpets, animals that could drink and coin-operated machines.  Hero’s most famous automaton, though, is the steam eolipile, which, in showing the expansion of gas when heated and the force of reaction in its escape, is regarded as an ancestor of the steam engine:



Above all, automata were sources of delight and entertainment: mechanical orchestras, living snuff boxes and cuckoo-clocks.   From King-shu Tse’s 500 B.C. flying magpie of wood and bamboo to Jacques de Vaucanson’s A.D. 1738 duck, which could eat, drink, splash around the water and digest its food like a real duck, inventors imitated nature for the delight of man:

 



Over time, the makers of automata moved from simply trying to recreate the motion of creatures in the natural world to trying to use these motions to accomplish the work of those very creatures.  This is not to say that entertainment automata disappeared – after all, fake talking human heads like Roger Bacon’s from the 13th century still capture the wonder (and horror) of onlookers at circus fairs and carnivals, as do automaton scribes, dancers and singers in the tradition of those seen below (and in the tradition of “It’s a Small World”). 

 

Picture: The Jaquet-Droz Writer, 1774.  Artifact courtesy of the Neuchâtel Museum.

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