TRANSPARENT BUNDLES by Seth Goldstein

Welcome to the Readerverse

I always loved you

You always had a lot of style

I'd hate to see you on the pile Of ‘nearly-made-it' s

You've got the essence, dear

If I could have a second skin

I'd probably dress up in you

Belle & Sebastian, The Life Pursuit

Welcome to the readerverse. Just as pages and sites have their community in Ted Nelson's concept of the docuverse, so users and visitors have theirs in the readerverse. It is a place where responses are generated as the primary activity. This occurs when we are reading, browsing, searching, scanning, tuning into, subscribing and, generally, using the Internet passively, automatically. The readerverse shadows the more explicit actions of writing, commenting, rating, taging and coding.

Via my various widget logs, I have been trying to illuminate my own readerverse.  I write things and then listen for the barely audible click steps that you make when you visit; the slight pinging sound you make when your reader checks my RSS feed.  With some of the emerging blog statistics and Attention tracking services that are emerging, the web is increasingly rendering as visible what we have come to think of as invisible.

One way of thinking about this in the real-world would be imagine what it would be like if your gaze left a mark? What if when you looked at somebody, instead of that being your private experience, that the person  immediately felt that she was being watched by you? How would that change the way we behave? We feel free to watch certain things, listen to certain conversations, tune in to certain channels, without worrying about these Attention choices being exposed to others.

This is a fundamental media right: the preference we enjoy in knowing that our media choices (ie our decisions about what we choose to pay Attention to) are not only under our control but are private to us. Bishop Berkeley asked whether the tree really falls if nobody is there to observe it.  This applies to the physics of Attention. If my gaze is imperceptible to those I am paying Attention to, then I remain the  sole source of information on my media consumption habits. However, if my gaze has material properties that impact others, then there are by definition other sources of authority on my Attention data. 

Almost seventy years ago, Alan Turing,   the brilliant British computer scientist and war-time cryptographer, suggested that:

The behaviour of the computer at any moment is determined by the symbols which he is observing, and his "state of mind" at that moment. Turing, On Computable Numbers, 1938

Now isn't that interesting? A conception of computing, from 1938 no less, in which the computer's behavior is driven by the Attention it is paying.  Putting this in the context of Goldhaber's theory of the physics of Attention will lead us to important laws on how influence is created:

There is only so much attention (available from other humans), and many or most of us want more than we have.

In order to get attention one needs to express or do something — let us say, perform in some way. (This can be putting forth information, but that is not particularly what, e.g., a trapeze artist does.)

The more attention we get in comparison with the attention we pay in putting together our total performance, the greater our attention productivity.

The more attention we have, period, the more influential we are.

The more attention you get now, or have gotten in the past, the more attention you can get in the future. (Attention wealth is stored in the minds of the attention payers.)

Having others’ attention means you can rely on some attentiveness from them as well. Attentiveness is a willingness to satisfy your desires whatever they may be — as long as these desires do not go too much against what the attention payers (audients) would otherwise want.

Though all this has always been true, new attention technologies, and particularly the Internet, make all this work much more directly. They make it easy for more of us to seek attention, and if and when we get it, to have other desires satisfied as well.

Michael Goldhaber, February 2007

Media Futures 2006: 3/5, API: Introduction

API stands for Application Programming Interface.  In the context of Media Futures, an API routes the output from one's own unique Attention-processing Algorithm  into an Alchemical reaction triggered by the convergence of other human-driven APIs.

I wrote my first post about APIs in the Spring of 05, at a moment when APIs such as those of Flickr and del.icio.us were just starting to become becoming popular targets of developers.  Since then, the subject of APIs has become commonplace in any discussion of the future of media.  In fact AOL- that stalwart of old new media- is now obsessed with open APIs.  Tina calls it the “the liberation of egosystems.”  Open data transport has suddenly become de riguer among the even the most traditional media companies.  In less than two weeks, legions of their corporate development executives will descend upon SF to walk down the red carpet of the O’Reilly ceremony, ready to sign the top Web 2.0 talent to long-term studio deals.

But while we all fall over ourselves to proclaim our “openness,” we introduce a far heavier burden of trust into the mix.  Is one company’s “open” the same as another’s?  While I may be able to avoid data lock-in in that silo, how do i know for sure the next “open data” silo will be equally amenable to the mobility of my data?  These questions beg a deeper investigation into the history of APIs and their evolution both physically and electronically.

History

In a memorandum dated July 15, 1949, Warren Weaver, who held the position of director of the division of natural sciences at the Rockefeller Foundation from 1932 – 1955, wrote about the possibility of language translation by an electronic computer.  It was the first suggestion most had seen that such a thing might be possible, and as he draws the memorandum to a close, his words preview the emergence of the API:

Think, by analogy, of individuals living in a series of tall closed towers, all erected over a common foundation.  When they try to communicate with one another, they shout back and forth, each from his own closed tower.  It is difficult to make the sound penetrate even the nearest towers, and communication proceeds very poorly indeed.  But, when an individual goes down his tower, he finds himself in a great open basement, common to all the towers.  Here he establishes easy and useful communication with the persons who have also descended from their towers.

Thus may it be true that the way to translate from Chinese to Arabic, or from Russian to Portuguese, is not to attempt the direct route, shouting from tower to tower.  Perhaps the way is to descend, from each language, down to the common base of human communication – the real but as yet undiscovered universal language – and then re-emerge by whatever particular route is convenient.  Such a program involves a presumably tremendous amount of work in the logical structure of languages before one would be ready for any mechanization.

The key to examining the evolution of the role of the API in context of Media Futures lies, in fact, in the multiple resonances of its last term, Interface:  as a surface lying between two portions of matter or space, thus forming their common boundary; as a means or location of interaction between two systems or organizations; as an apparatus designed to connect two scientific instruments so that they can be operated jointly, the abstract concept of an interface contains in it the possibility of a very literal connection between two beings, two faces.  As a physical interface connects two pieces of hardware, a user interface connects a human and a computer and a software interface connects separate software components so that they may communicate with one another.  To interface is to come into interaction with a thing or being, to communicate, in manners both figurative and literal.

Mainframes

As a platform that allows a computer system, library or application to open itself to use by other computer programs, or to allow for the exchange of data between them, the APIs of yesterday were IBM mainframes and Microsoft SDKs, arcane languages of translation between hardware and software.

From the late 1950s through the 1970s, a number of American, German and British manufacturers (Burroughs, Control Data Corporation, General Electric, Honeywell, NCR, RCA and UNIVAC; Siemens and Telefunken; and ICL, respectively), produced such mainframes, computers used in large part by companies and government institutions for the purposes of bulk data processing in the context of, for example, the census or financial transaction processing.  IBM secured itself a position of power in the industry with the development of its 700/7000 series, based on vacuum tubes and transistors, and with its 360 series mainframe.  Unveiled in 1964, the 360 series was to be an all-around computer system, a series of compatible models for purposes both scientific and commercial – a series which, moreover, brought together features which were once only available in scientific or commercial computers, such as floating point arithmetic in the former and decimal arithmetic and byte addressing in the latter.  The 360 series also included supervisor and application mode programs and instructions and built-in memory protection facilities, making it one of the first computers manufactured with provisions specific to the use of an operating system.

Console of an IBM 360/67 mainframe

PCs

As the demand for the older mainframe systems fell off, new installations were seen mainly in the realms of finance and the government.  Personal computer networks came to challenge the mainframe.  It was during the rise of personal computing networks, though, that the APIs with which we are most familiar came into being and, in the case of Windows, achieved dominance. 

In 1975, the Altair 8800 was introduced in Popular Electronics, a personal computer that was affordable, user-friendly, and, some argue, the spark that set Apple Computer and Microsoft ablaze in their development of personal computers. The Apple II, though less capable and versatile than some of the larger computers of the day, gave computer enthusiasts an environment in which to develop their own programming skills and to operate simple office and productivity applications. 

The IBM PC released in 1981 took the personal computer into the realm of business, giving individual users word processing programs, spreadsheet programs and database programs which would change the way businesses stored, sorted and used their data. Four years later in 1985, in order to compete with the graphical user interfaces made popular by Apple, Microsoft released an add-on to MS-DOS – an operating environment known as Windows.

 

Though that release of Windows was not an operating system in the full sense of the term, it had pushed beyond the characteristics of a typical desktop, adopting some functions of operating systems.  Windows achieved a leg up on competing systems due in large part to the fact that MS-DOS dominated the early landscape of personal computing.  But the dominance of Windows (up until Google that is) is the API.  The APIs which enabled professional programmers to develop desktop applications on top of platforms (perhaps most notably the Microsoft Windows API), have now given way to APIs which feed off of the platform of the Internet.  And while Microsoft and the desktop are controlled by physical bodies, the Internet, despite the fact that certain companies do, in fact, oversee enormous pools of user data and have the ability to direct traffic as they see fit, is not governed by a particular body or set of bodies.  If the power flow of yesterday’s APIs was a vertical one, headed at top by the executives of companies like Microsoft, which allowed programmers to work off of their platform to develop applications to be used by the users at the  bottom, we might see the power flow of today’s APIs as closer to a horizontal one.   

Next:  The Thrilling Poverty of Physical Gestures

MEDIA FUTURES 2006: 2/5 ALGORITHM: History of Algorithm

An algorithm is a machine that can be used to reproduce a unique pattern of behavior.   The history of the word traces back to the Greeks and the instruments they used for mathematics; for example, the sieve.  In the context of Media Futures, imagine that algorithms are tightly woven filters that capture the full range of human Automata and slowly sift through them to produce the most meaningful, intentional gestures.

Ancient Algorithms

Finding its root in algorism, a reading of the name of Abu Ja’far Muhammad ibn Musa Al-Khwarizmi, the 9th century Persian mathematician who described a set of rules for solving both Linear and Quadratic equations, algorithm came to its present state by way of an 18th century European Latin translation and soon expanded its meaning to encompass all definite procedures for solving problems or performing tasks.  The very first algorithms are a part of the Babylonian mathematical legacy – a legacy which not only left us with algorithms for factorization, finding square roots and performing long division, but which also left us with the base 60 system that gives 60 minutes to an hour, 60 seconds to a minute, 360 degrees to a circle and 24 hours to a clock.  Babylonians were in fact able to calculate things with the same accuracy as Renaissance mathematicians due to their use of number tables, like the Plimpton Tablet, a table of Pythagorean Triples from about 1700 B.C.

While the Babylonians based their mathematical system in large part on algebra, the Greek system of mathematics was heavily based upon geometry.  It is speculated, though, that the founder of Greek science and mathematics, the philosopher Thales of Milet, visited Egypt and Babylon during his lifetime (634 – 546 B.C.) and brought back knowledge of their astronomy and geometry.  The Egyptians made great contributions in the fields of medicine, astronomy and applied mathematics, and while the former triumphs are well documented, there exist no records of the process by which they reached their mathematical conclusions.  Thales built on the knowledge brought back from his trips, inventing deductive mathematics and proving a number of theorems – a circle is bisected by a diameter; the base angles of an isosceles triangle are equal; and pairs of vertical angles formed by two intersecting lines are equal.

The foremost text on geometry came from fellow Greek Euclid, whose Elements put together former geometric knowledge with definitions, postulates and opinions – and, of course, Euclid’s elegant and rigorous proofs of the above.  In that text, he discussed the algorithm for finding the greatest common divisor of two numbers, which is today referred to as the Euclidean algorithm.  One hundred years later around 200 B.C., the world saw the next great algorithm – the Sieve of Eratosthenes, which was used to find prime numbers.

From Wikipedia: 

Sieve of Eratosthenes is a simple, ancient algorithm for finding all prime numbers up to a specified integer. It is the predecessor to the modern Sieve of Atkin, which is faster but more complex. It was created by Eratosthenes, an ancient Greek mathematician.

 

Another important site in the history of the algorithm was Alexandria, home to Hero, Ptolemy, and Diophantos.  Hero, whom we will remember as the inventor of the steam eolipile and other Automata, published widely on geometrics, optics and mechanics – as well as mathematics.  Though sources suggest his work is derivative of Archimedes and the work of the Babylonians, his Formula to calculate the area of a triangle in terms of its sides and his Method to extract a root are important contributions to the world of mathematics.  Ptolemy published widely on astronomy and geography and calculated the best approximation of ‘pi’ for his time.  And Diophantos, known as the ‘father of algebra’, wrote his thirteen-volume Arithmetica on the solution of algebraic equations and the theory of numbers and introduced the use of algebraic symbolism with an abbreviation for the unknown for which he was solving.

But Diophantos shares the title of the ‘father of algebra’ with the aforementioned Al-Khwarizmi, whose work was responsible for significant advances in the world of mathematics. 

It was Al-Khwarizmi’s work that promoted the use of Hindu-Arabic numerals that not only pushed forward the numeral system we use today, but that gives us the very term algorithm. From the very first algorithms of the Babylonians to those of Al-Khwarizmi – to John Napier’s 1614 method for performing calculations using logarithms to the 19th century work of Boole, Frege and Peano, which set out to reduce arithmetic to a series of symbols which could be manipulated by rules – to the work of Babbage, Lovelace and Turing, which took these rules and transformed them into agents of action in computing, these feats of problem-solving are instrumental in understanding man’s quest for a grasp of the workings of the world at large.      

Babbage and Turing

One great advantage which we may derive from machinery is from the check which it affords against the inattention, the idleness, or the dishonesty of human agents.
From Babbage’s 1832 work “On the Economy of Machinery and Manufactures”

In our discussion of rules that govern the Internet, we must turn to the work of Babbage and Turing, for it serves as the important foundation for computing at all.  Babbage’s work grew out in part out of a need for more accurate mathematical tables, which were essential calculating aids used in navigation and astronomy, insurance and civil engineering.  These tables were produced by human computers and by hand – and as such, they were prone to error in terms of computation and reporting.  Even the slightest errors in navigational or astronomical tables can be costly – so it is no surprise that in the years leading up to Babbage’s project, government sources were willing to fund projects that would minimize the costs of troubleshooting. 

For example, the British Nautical Almanac, the world’s first permanent table-making project – had a reputation for ever-improving accuracy since its inception in 1766.  But moving into the 19th century, that seaman’s bible swung into a dangerous territory of inaccuracy and error, and the British government recognized the promise of producing mathematical tables mechanically and typesetting them by the same machine. 

So Babbage set out, with financial support (and the admirals’ prayers) to improve the accuracy of those ever-important mathematical tables by constructing algorithm-driven machines.  It was a move that mechanized the production of thought, a move that would eliminate human folly in computation, transcription and typesetting.  The result would be better answers, answers which would in turn be used for giving new instructions, as inputs in other algorithms.   

Babbage never finished his Difference Engine – though, in 1832 his manufacturing engineer did construct a working portion of it, which measured two and a half feet high by two feet wide by two feet deep.  Babbage moved forward to conceptualizing what would be the world’s first programmable digital computer – the Analytical Engine.  Babbage’s designed the engine such that it would separate the sites of arithmetic computation from the storage of numbers.  The computation would be carried out through a series of steps recorded on punch cards, such as the ones used in the technology of the Jacquard loom. 

But however intriguing and important the technology seemed, Babbage’s Analytical Engine – due to factors financial and logistical – was never built.  It comes to us only through Ada Lovelace’s annotated translation of a French introduction to the machine – a piece of writing that established the algorithm for the computation of Bernouilli numbers, and a piece of writing that established the idea of computer programming.  Turing would later build on the work of Lovelace and Babbage, formalizing their concepts in the Universal Machine.

When Turing introduced the mathematical description of the Universal Machine in the 1936 paper “On Computable Numbers”, he set out to answer the Entscheidungsproblem, the third question left by mathematician David Hilbert.  Gödel had already answered Hilbert’s first two questions – No, mathematics was not complete, and it was not consistent.  Turing showed that mathematics was not decidable.  And that recipe to solve a particular problem, gave us an answer that begs the asking of a new set of questions.

MEDIA FUTURES 2006: 2/5 ALGORITHM: The Transition from Automata to Algorithm

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

Media Futures 2006: 1/5 Automata: The Human Computer

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.

Media Futures 2006: 1/5 Automata: Industrial Automata: From Performance to Prosthesus

Automata evolved from acting like us to acting on behalf of us.  What if it was possible for an automaton to do the work of a human?   Would the stuff of Aristotle's ruminations come to pass, eliminating the need for servants and slaves?  To realize that fantasy – as Albertus Magnus supposedly did in the 13 th century, with the construction of a life-size human domestic servant automaton – is to eliminate the need for humans to pay Attention to certain aspects of work in the home.  These automata promised to give owners a surplus of energy and attention, but at a cost.

Scientists have long recognized, Sir Geoffrey Jefferson argued in his 1960 "The Mind of Mechanical Man", that aside from the mind, “both animal and human bodies were nothing more than a collection of pumps, reservoirs, bellows, fires, cooling and heating systems, tubes, conduits, kitchens, girders, levers, pulleys and ropes.”   (Clearly, as John Stewart points out, little has changed since)

In this model, automata do not have minds, hearts, or souls.  This was all the better, since those human aspects might have forced the automata into unnecessary error.  These perfect machines began to gain power over the very humans who operated them, a power which became even more threatening when humans wrestled with the possibility that their creations might actually come to life.  What, then, would these exploited classes do?   Embedded in their very name are the seeds of revolutionary threat: robot (as human-shaped automata are widely referred to) comes from the Czech robota, meaning forced labor, and it is a term that was first used in Karel Čapek's 1921 play Rossum's Universal Robots, or R.U.R. 

 

 

The questions raised by this term in Čapek's play are central questions in the discourse of modernity – questions of the nature of man and machine and of the boundaries between the two.   Human-like machines threaten to come to life and overpower the control of their former masters; machine-like humans threaten to destroy life, overpowering any sense of humanity and the body of humanity itself.   

 

(Picture: Georg Grosz. Republican Automatons.)

From the faceless figures in Georg Grosz's Republican Automata (above) with hooks for hands and gears for souls, to the orphaned machine of Francis Picabia's The Child Carburetor (born of the work of man but devoid of his agency) the machine-like human and the human-like machine confuse our sense of where us stops and the machine we created to stand for us begins.

 

(Picture: Francis Picabia. The Child Carburetor.)

In 1950, Norbert Wiener wrote in his 1950 work on cybernetics "The Human Use
of Human Beings":

When human atoms are knit into an organization in which they are used, not in their full right as responsible human beings, but as cogs and levers and rods, it matters little that their raw material is flesh and blood.  What is used as an element in a machine, is an element in the machine.  Whether we entrust our decisions to machines of metal, or to those machines of flesh and blood which are bureaus and vast laboratories and armies and corporations, we shall never receive the right answers to our questions unless we asks the right questions.

Let us bear this careful warning in mind, as we evaluate the visions being articulated now by our most noble leaders of the Internet.  Take for example the recent speech by Ray Ozzie, Chief Software Architect at Microsoft to an audience of financial analysts:

But beyond infrastructure services, what's most unique and valuable about a very large-scale services platform is what I'll refer to as optimization. By optimization I mean the monitoring and utilization of both collective end-user behavior and individual behavior to rank content for the user. That ranked content might be the order of advertisements in a search or e-mail window, or the order of relevant news items or playlists or video clips or items in a marketplace that are presented to the user...Optimization always respectful of a user's privacy will be increasingly key to delivering great user experiences, and it's already a key factor in the area of profitability, because the larger the number of users that are connected to any services platform, the more behavioral the data that can be generated. The larger the number of PCs and other devices that are connected to that platform, the more behavioral data that's available; the larger the number of applications connected to the platform, both Web apps and desktop apps, the better our optimizations will be and the more profitable it will be for us and for our partners.

It is remarkable the extent to which Ozzie seems to ignore the fundamental Web 2.0 premise that users are in control, and that just because behavioral data may be generated automatically, that does not mean that the companies enabling such data (ie Microsoft) have necessary dibs on it.

Over history, automata were at once objects calling for our attention – objects meant to enrapture us in spectacle – as well as objects that offered to do our work without requiring our Attention.   This represented the threat of triumph over human mastery: that these automata might take on lives of their own, rendering humans obsolete and placing us at the mercy of the machine which always acts without emotion, error or thought.  The power of choice manifests itself in one's ability to ask, in Weiner's words, "the right questions."  Right questions might be those queries specifically which elude their engine's best attempts at matching them to willing advertisers.

Media Futures 2006: 1/5 Automata: A Brief History of Automata: Cranking Away Since Alexandra

 

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.

technorati tags:automata, mediafutures, root.net, attention, media, attentiontrust

Media Futures 2006: 1/5 Automata

  

Automatic Motion and the Gestures of Social Media

The Attention Economy is based on human behavior, behavior which includes the full range of physical gestures that we use to express our inner intentions.  These gestures could be saying something,  stretching our arms, walking past a group of people, or reading a book.

Many gestures end in themselves, as discrete actions.  Other gestures trigger subsequent gestures: for the person who performs the gesture (such as throwing a ball into the air and then catching it on the way down) or for the one that receives the gesture (such as calling somebody on the phone who then picks up their phone).  Since its introduction as mass consumer platform over ten years ago, the Internet has attracted an increasing amount of the latter: electronic gestures that use keyboards and mice (and increasing voice and video) to trigger subsequent gestures from others across the Internet.  It is not simply that more human behavior is being expressed through the Internet; entirely new kinds of human behavior are being created by virtue of the medium.  Many of these gestures are able to authenticate intentions with great subtlety so as to increase the ratio of signal to noise.

These are the gestures of social media, where influence is measured by the amount of Attention one gets relative to the amount of information one gives  The most influential online individuals combine a high pagerank that lands them above the Google fold (ie their unique algorithm) and a rich personal stream of syndicatable "what makes me me"-ness:  ie their natural API. 

The Turing test measures whether a computational response is mistakable for an actual human being.  George Dyson’s recent essay Turing’s Cathedral imagined this test to be central to Brin and Page’s agenda for Google.  They are trying to build an artificial intelligence whose automatic responses to queries seem natural and humanistic.  In order to experience the rich social media of a post-Web 2.0 landscape, however, we need to venture beyond the shadow of the Google page-rank Golem.  How can we trust an electronic reality based solely on the single perspective of pagerank (ie the link model), when our actual behavior seems more like, in the words of William James, a “blooming, buzzing confusion” of human electronic gestures.

"Egosystems, not Ecosystems"

Stallman, Torvalds, Doc Searls, R0ml and many others have established the underlying value of an Open Source ecosystem.  At the first public meeting of AttentionTrust.org in October 2005, Tim O'Reilly suggested that the next generation of the Web (3.0?) was going to be about "Data Inside".  And so if you apply the discipline of a truly Open system to all of the behavioral data that is expressed by these electronic gestures, you end up with a new organizing framework- a framework of egosystems which, for the first time, bind human behavior to the transport policies of Open Source ecosystems.  My wife Tina Sharkey came up with this brilliant expression, "egosystems, not ecosystems." in which the notion of an egosystem can be used to express the rich variety of our interactions across the Internet:  email, search, browsing, buying, tagging, chatting, and other electronic activities.  One egosystem may interact with other egosystems in infinitely different ways.  And so even at maximum resolution, this social media fabric appears richly woven and densely textured:  tiny threads of gestribution bundled transparently around eachother.

Enter the worms (which happen to be the subject of the last section of the last chapter on Arbitrage).  These little creatures that both consume and produce in equal measures provide the best model for understanding the physics of the Attention Economy.

Hamlet explains that:

We fat all creatures else to fat us, 
and we fat ourselves for maggots. Your fat king and your lean beggar is
but variable service- two dishes, but to one table.

So Hamlet 2.0 might say:

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.

What distinguishes social media from other forms of media is this worm-like behavior, where production and consumption occur simultaneously.  You can look at it as a form of therapy, where individual data is constantly being reorganized (quantitatively) to generate richer (qualititative) meaning.  This is the  Gillmor moment, when the naval-gazing gesture of an individual’s Attention feeds back, anonymously, into crystal-clear affinity pools of metadata.  Inference and influence reverberate off of eachother, turning a mess of discrete gestures into a continuous Gesture stream.

Attention Science

Attention has forever been described as an absence in terms of distractions, deficits and obligations.  Media Futures is a model for talking about Attention as something more; as an active substance that we create, express, share and remember.  This Attention substance- let's call them attentrons- operates at a size and frequency that makes it invisible to our naked eye.  Fortunately, none of us need travel very far to reach the Attention super collider, where we can test for traces of these attentrons.  The mashups that emerge on Digg are powerful reactions of data and people.  From the new dance clubs in Second Life ripple new patterns of social networks.  How can we analyze these seemingly spontaneous phenomena so as to make visible the elements and interactions that drive their behavior?

This is the project of Media Futures: to come up with a conceptual schema that synthesizes the  constructivist aspects of social media and the analytical rigor of the Attention Economy.  It is a language game:  as complex as Chess, and as fleeting as Chutes and Ladders.  Computer scientists in the 1950’s gave us the building blocks of Input, Store, View and Output;  MS-DOS gave us operations like copy, file, print and run; Unix gave us root access.  In the Attention OS, it's the 5 A's: Automata, Algorithm, API, Alchemy and Arbitrage.

Maggie Dillon has done a great job aggregating brief histories of each topic, both to establish its historical credibility and to expose the subtleties of its use over time.  This syntax of Media Futures is valuable, however, only in so far as it is applied to real social media use cases.  These new services require active minds, creative imaginations and lots of quality code.  What's missing is the sense of continuity between early computing history and the widget design for next week's release.  And that is what we are working on here.  Enjoy.

Next: History of Automata

THE WAR FOR ATTENTION: SUMMER 2006

Foreward

Since writing a series of essays on Media Futures in the Spring of 2005, I have spent the last year or so investing in and building out various data services.  These include: a lead generation marketplace at rootexchange.com, whose first vertical is mortgage;  a clickstream media platform at root.net, the command line for a new Attention-based OS; AttentionTrust and the promotion of its four principles of property, mobility, economy, and transparency (AttentionTrust.org is now the #2 organic search result for Attention on Google); the “crystallized attention” (tag) company del.icio.us, which was acquired by Yahoo!; and finally, Majestic Research, the investment firm that uses online consumer behavior for its equity models and which I co-founded in 2002.  Majestic is the name I used for this blog on typepad, and its subtitle transparent bundles was an attempt to describe how investment research and trading should operate. 

Sometimes it feels like I am working on a number of disconnected activities.  But enough of the time it feels like they are all connected in a deeper kind of way.  They all deal with consumer Internet usage; and more specifically, they share the common goal of maximizing the signal-to-noise ratio of online data in order to elicit the highest fidelity copy of an individual’s Attention.  This is not an easy problem to solve, as the interface between one’s mental focus and the TCP/IP protocol is indirect at best.  What we have as proxies are clicks, searches, tags, forms and other types of user generated media.  From the interplay of these artifacts we-- as in the royal Web 2.0 we-- are busy coding a social media fabric, the center of which always seems but one release away.

Unlike most media properties, Attention is inherently unstable and indeterminate.  Describing Attention is like making a movie inside of a house of mirrors, where it is impossible to keep the camera itself out of the picture.  It is because of this Heisenberg-like uncertainty principal that passive behavioral data provides the better indicator of pure Attention than explicit user generated content such as ratings, reviews and tags (which change the substance of Attention as they reflect it).  As we review the history of Attention, it seems always caught in its own shadow; artists and actors want Attention and create works and performances to “attract” and “capture” it.  Only recently have certain of us (guided by Goldhaber’s theories on the matter) come to see Attention in its own light: as a material substance that moves from one human being to another like a language or a liquid.  Our cognitive framework for Attention needs to shift from metaphors of coercion to metaphors of creation.

The distributor of Attention may indeed be influenced by that receiver who provides the most interesting information, but still the former maintains control over who gets his Attention.  It is this choice the individual has over where he spends his Attention that underlies the theory of Media Futures.  This new organon assumes that the user is in control of the media that he and his network of social and commercial relationships create.   With the traditional consumer now in control over the means of social media production, the traditional media company now needs a new value-creation model-- one based on consuming the most relevant electronic gestures of its audience, rather than one based on producing the most engaging content.

For a broader dialectical context, I would encourage you to  tune into the following writers

• Steve Gillmor
• Michael Goldhaber
• John Hagel
• Umair Haque
• Doc Searls
• AttentionTrust.org

Attention:  The underlying instrument of Media Futures

“Attention is scarce,” Michael Goldhaber writes, “because each of us only has so much of it to give, and it can only come from us – not machines, computers or anywhere else.”  It is in cyberspace, he argues, that a new type of economy comes into its own: this is the attention economy, an economy based on what is both “most desirable and ultimately most scarce.” 

Goldhaber’s principles of the attention economy enter into a long-standing dialogue among art historians and cultural theorists about the techniques and implications of attention in the production and reception of media.  As art historian Michael Fried argues in Absorption and Theatricality, it was first in the writings of Diderot that the terms of attention assumed critical in addition to rhetorical significance.  A painting, Fried writes, “had first to attract (attirer, appeller) and then to arrest (arrêter) and finally to enthrall (attacher) the beholder, that is, a painting had to call someone, bring him to a halt in front of itself, and hold him there as if spellbound and unable to move.”  Then, it was the media itself being consumed that did the work advertising does today: it was up to the media itself to call out to consumers for their attention.

The Beauty Salon

Of course, in today’s salons, we are more likely to consume the news of celebrity hook-ups than the spectacle of high art: that the salon is still a place for to see and be seen is telling.  In the eighteenth century, the salon was a privileged site for the bourgeoisie to consume, contemplate and discuss art and literature – truly a place for seeing and being seen.  We pay visits to an entirely different type of salon today: we go in preparation for – or to increase our chances of – the condition of being seen.  By doing work on our bodies – by taking clippers to our dead cells, by taking tweezers to our brows, we might too do our own advertising: we might attract, arrest and enthrall the passers-by.  We pay to increase our chances of being beheld – consumed, contemplated, discussed; we pay so that others might pay attention to us.

This is the to be seen half – but that which we see in salons, besides other guests questing to improve their own appearances, is the set of people important enough to be seen by the masses: celebrity.  Magazines like People and Us Weekly, which adorn the waiting areas, promise a behind-the-scenes look at the lives of people who have entertained us on stage or on the big screen, or perhaps even written books for our edification or delight.  These celebrities have captured the public’s attention with their work, and they certainly capture the public’s attention with their play.  And the placement of celebrity magazines in salons suggests the possibility that by altering our appearance, perhaps in the fashion of the star du jour, we might capture more attention.  At the end of this line of fantasy is the possibility of our own presence in such a magazine, the possibility that the banalities of our own lives will be represented in the world of others and put out for consumption by third, fourth, millionth parties.  We will be worthy of attention.

The Internet Salon

The truth is that our own private gestures are constantly being recognized, represented and put out for public consumption – and in real time.  Moreover, these gestures are at the same time being plugged into calculations to predict our future behavior, calculations which promise a personalized experience to those who click (and profit to those who calculate).  The playing-out of these phenomena takes place, of course, on the Internet.  This is an economy of attention – one, as Goldhaber argues, that is different from any economy seen before: “In its pure form, it doesn’t involve any sort of money, nor a market or anything closely resembling one.  It involves a quite different pattern of life than the routine-based, industrial one…What matters is seeking, obtaining and paying attention.”  The economy’s “characteristic form of property” is “the attention that is readily available to its ‘owner’ from other people, which depends on what attention this owner has gotten in the past”; it is a property “located, quite literally, in ‘the minds of the beholders.”

In his work on the attention economy, Goldhaber views the movement toward cyberspace as analogous to the move of western European civilization to the New World of the Americas around the time of the birth of the market economy.  “Unimpeded by the remains of feudalism,” he writes, “the market-industrial system in fact took most complete hold here in North America first.  From here, much later, it swept back to complete its conquest of the western European motherland, along with the rest of the globe.”  Similarly, “Cyberspace will be the ‘place’ where the new economy moves ahead most dynamically, but the strength gained in the process will eventually sweep back to dominate the rest of life.”

If Attention is indeed the substance of focus (that which registers our interests by indicating our choice for certain things and choice against other things), then Internet is the most fertile ground for the development of the Attention Economy;  for the Internet (and particularly web services) allows the recording and sharing of our choices, of our Attention, in real-time.  These choices of ours are manifested by the binary gestures of the keyboard and mouse.  With each click, our own narratives expand.  With each move to create a tag or a link, our narratives expand.  With each search, with each subscription, our narratives expand to tell the story of which team we follow, where we will be taking our next vacation, which conference we are planning to attend.  The gestures of our lives are recorded, and we become represented – on “Top 100” lists, blogrolls and Flickr badges of different  sizes.  And the narratives of our electronic Attention gestures have even crossed back into offline mass media: on CNN’s headline news or American Idol’s SMS voting.  We may not be followed by paparazzi, but airtime on national television is a start.   

The sociological, psychological and economic forces at play in this discussion warrant extended research.  As such, it is a daunting task to wrestle with the history of social media and probe into its future development.  The Internet is a dynamic site of all sorts of production and consumption, a place where familiar models are broken and reinvented, a place where the material being consumed is dynamic, produced on the fly.  We have tags, wikis, social networks and other forms of social media – we have new forms of media being created by everyman for everyman, and at any time, in any place.  And works in these media are being created at a far higher rate than they are being consumed.  Power and value shift, become redefined; the very possibilities of our personhood shift, become redefined.
The more we express ourselves electronically, the more residue we leave behind in this ever-growing, ever-changing landscape – shadows of our digital actions scattered about held together not by gravity, biology, optics but by algorithms and APIs.  The economics of behavioral data, and the electronic media gestures that constitute this data, reveal themselves in an analysis of Attention.   This is the goal of updating Media Futures one year later:   Over the coming weeks, I will write the five-boned skeleton of A’s into the skin of Attention: 

It is a body of work that seeks to better understand our gestures in social media, the very articulations of our attention and intentions – a pyramid topped by Attention and flanked by:

• Automata- Human inspiration
• Algorithm- Patterns of behavior
• API- Natural expression
• Alchemy- Value creation
• Arbitrage- Economic discovery

This is a model I see as most compelling in examining the delta of change, the fertile crescent lying between Wall Street and Madison Avenue.


Note:  I am fortunate to be working with an extremely thoughtful and lyrical research assistant in Maggie Dillon, who recently graduated Princeton and who will be studying art history and media theory next year at the University of Cologne.  She likes to refer to herself as a "an aspiring poet and brewer from the country's heartland," which is clearly the kind of midwestern pragmatic spirit that this blog needs more of!

Thread 6: Lew Ranieri responds to Questions

QUESTIONS AND ANSWERS

Q:  It’s not easy to become an insurance company but it’s easy to become a broker.  So the question is, have you guys attacked any of that piece of it, not just the originations, but also the insurances that accompany them?

Ranieri:  There is nothing that says in the same way you get his lead from online you cannot deliver all this other kinds of information online, which is normally difficult in a traditional process.  Unless the consumer proactively tries to break out of the corral, it doesn’t happen.  Here he’s already out of the corral; he’s online.  You follow?  And I think what you’re going to see is a lead may become simply a sequence of leads.  The lead won’t simply be a lead for a mortgage.  You might sell the lead four times to four mortgage companies; but you may sell that same lead beyond that, because as sure as God made little green apples, there will be a sequence of insurance companies or title companies who want that same information.

Q: This is a question about the Exchange that you have built.  As you and I both know going way back in the lead generation business, it’s a supply driven business so if you can’t get the supply then there’s nothing to exchange.  So even though I agree with Lew that this could potentially be a big win for mortgage brokers because they’re getting more leads, better leads, a price based on the real value … even though I believe it could be a win for the consumer because probably they’re getting well-priced goods and services, I don’t see any reason in the world why any of the companies out there that are generating real estate or mortgage leads would want to cooperate.

Goldstein:  We call them aggregators, and they are generating supply across the industry:  LowerMyBills, Nextag, LendingTree, LoanWeb, Adteractive, there’s a number of them.  Many are quite good and are generating high quality mortgage leads that lenders are purchasing.  The Exchange is open and available to them at minimal cost as an opportunity to discover price and to clear inventory that only has 24 hours before it goes stale.  Some of them may have their own direct relationships where they’ll sell the lead once or twice, but for the third or fourth time they might use the Exchange.  Most of these aggregators purchase their media inventory from publishers.  A consumer of one of these aggregators is typically coming in through a search engine or a banner.  The natural suppliers of this inventory are the newspapers, the search engines, the media companies, all of whom up until now haven’t really had a channel to sell leads directly through.  They have had to sell impressions and trust that they are getting a fair price for their impressions relative to the value of the underlying leads they could be generating.  Many publishers are indeed getting fair prices, but there are some publishers who have relevant search terms or relevant content areas that might monetize better it they were able to go directly to our Exchange.  And so we are committed to enabling both traditional publishers who are capturing the direct attention of the consumer and aggregators who, in most cases, are purchasing media to generate leads. 

Ranieri: In the regular, non-refi mortgage business, that volume is not controlled by an aggregator; as an example, it’s controlled by realtors.   Realtors turn those leads into money simply by, at this point, becoming a mortgage company to convert the lead into their own servicing.  I think I could argue if this process is as efficient and powerful as I believe it will be, they will be a lot better off just accessing our Exchange.  It will be much more cost effective.  Every homebuilder in the country decided they had to become a mortgage company to capture that portion of the revenue.  Our Exchange will give them the ability to exit a business they really never wanted to be in.  They just want to keep that portion of the income that came from the result of building the house.  This gives them a much more cost efficient way of doing that.

Q:  That’s why I’m saying it’s great for the demand side but maybe it’s not so great for the supply side.  If I’m a publisher and I’m making $10,000 a month from an aggregator, why should I drop them and sell leads directly to your Exchange?  I think you’re going to get some resistance.

Ranieri: One of the largest mortgage companies in America at the beginning of all this was Loomis and Nettleton, and they were a monopoly.  They viewed the advent of the mortgages security market as a risk, as something that was competition because in those days mortgage companies were brokers.  They weren’t what mortgage companies are today.  They actually simply brokered a loan between thrifts or between thrifts and pension funds.  And here I was suggesting that mortgage companies become originators:  get into the mortgage business themselves, take the mortgages they create and turn it into a security and sell it.   So that their whole business wouldn’t be going to the Arizona Banking Conference and lining up four new thrifts to sell them into.  But I was preaching heresy.  And this great, giant company, Loomis and Nettleton decided “a pox on my house” and that they weren’t going to change.  And unfortunately it turned out for them that I wasn’t all wrong.  And there’s no longer a Loomis and Nettleton. 

Goldstein: But there were plenty who adapted to the evolution.

Ranieri: It was actually good for mortgage companies.  In fact, if it was bad for anybody it was bad for the thrift who wanted to show up at 10 and go golfing by 3.  The mortgage companies inherited the earth. 

Q: Your comments about refinance product were focused largely on refinancing to a fixed rate product, any thoughts on the option ARM product?

Ranieri:  We’re talking about a very sensitive topic so I’ll just take it on head-on.  Option ARMs in their original design were created for middle income, upper-middle income people who understood the nature of the risk in the option arm and for whom it worked very well because they could manage the risk.  They could de-lever if they so chose.  That was the issue; you could de-lever.  When the option ARM started to be used as a vehicle to qualify the unqualified, it became an abuse, in my opinion.  Actually, the first arm was called a floater.  The first ARM structure wasn’t called an ARM, it was called a floater and the rest of us called them sinkers because in the next cycle they never ever hit par again.  So an option arm in its most aggressive form where you have a 1%, then it rolls to a 1% initial for 90 days, 4% and then it rolls to fully indexed after the year.  And you can choose to stay at 1 percent.  Think about it.  That’s an 85% loan to value and you choose to stay at 1%. In less than two years you’ll be at 115% loan to value and you can’t go anywhere.  I’ll write in blood for any of you who want to have this bet with me.  I will tell you there’s a 100% correlation between equity and foreclosure.  Nobody lets you take a house that he has net equity in and nobody tries to stop you when he has negative net equity.  So you drive a loan up to 115% in two years, unless housing’s appreciating to offset that, you are going to have an unhappy amount of delinquency and loss on foreclosure.  So I think the option arms are a very useful product as long as you don’t use them for what they were never designed for.

Q: Servicing value?

Ranieri:  Servicing value will follow, depending on who’s buying the servicing.  Thrifts were for a very long time very naïve about the risks to certain kinds of consumer and option ARMs and so the option ARMs were 5/8’s of a point regardless of whether they were upper-middle class or being used as a way to qualify the unqualified.  Then the FDIC, the regulators, the federal financial oversight group came out with guidelines and said to financial institutions, banks, credit unions and council and state insurance companies: “If you do this, I have news for you.  You can do it.  We won’t stop you.  It’s not technically illegal, but when we come in, we’re going to ask you to do a series of algorithms and if you cap out in two years we’re going to make you write these things down; we’re going to make you take reserves against it.” And so the aggressive AM arm loans now are trading at pretty substantial discounts to the 5/8s and 3/4s of a point based on those regulatory algorithms.

(Thread 6/6 of RootExchange/s speaker series: #2 June 13, 2006 with Seth Goldstein interviewing Lew Ranieri at NY office of Root Markets)