Posted:July 6, 2006

In 2002 Joel Mokyr, an economic historian from Northwestern University, wrote a book that should be read by anyone interested in knowledge and its role in economic growth. The Gifts of Athena : Historical Origins of the Knowledge Economy is a sweeping and comprehensive account of the period from 1760 (in what Mokyr calls the “Industrial Enlightenment”) through the Industrial Revolution beginning roughly in 1820 and then continuing through the end of the 19th century. The book (and related expansions by Mokyr available as separate PDFs on the Internet) should be considered as the definitive reference on this topic to date. The book contains 40 pages of references to all of the leading papers and writers on diverse technologies from mining to manufacturing to health and the household. The scope of subject coverage, granted mostly focused on western Europe and America, is truly impressive.

Mokyr deals with ‘useful knowledge,’ as he acknowledges Simon Kuznets‘ phrase. Mokyr argues that the growth of recent centuries was driven by the accumulation of knowledge and the declining costs of access to it. Mokyr helps to break past logjams that have attempted to link single factors such as the growth in science or the growth in certain technologies (such as the steam engine or electricity) as the key drivers of the massive increases in economic growth that coincided with the era now known as the Industrial Revolution.

Mokyr cracks some of these prior impasses by picking up on ideas first articulated through Michael Polanyi‘s “tacit knowing” (among other recent philosophers interested in the nature and definition of knowledge). Mokyr’s own schema posits propositional knowledge, which he defines as the science, beliefs or the epistemic base of knowledge, which he labels omega (Ω), in combination with prescriptive knowledge, which are the techniques (“recipes”), and which he also labels lambda (λ). Mokyr notes that an addition to omega (Ω) is a discovery, an addition to lambda (λ) is an invention. One of Mokyr’s key points is that both knowledge types reinforce one another and, of course, the Industrial Revolution was a period of unprecedented growth in such knowledge. Another key point, easily overlooked when “discoveries” are seemingly more noteworthy, is that techniques and practical applications of knowledge can provide a multiplier effect and are equivalently important. For example, in addition to his main case studies of the factory, health and the household, he says:

The inventions of writing, paper, and printing not only greatly reduced access costs but also materially
affected human cognition, including the way people thought about their environment.

Mokyr also correctly notes how the accumulation of knowledge in science and the epistemic base promotes productivity and more still-more efficient discovery mechanisms:

The range of experimentation possibilities that needs to be searched over is far larger if the searcher knows nothing about the natural principles at work. To paraphrase Pasteur’s famous aphorism once more, fortune may sometimes favor unprepared minds, but only for a short while. It is in this respect that the width of the epistemic base makes the big difference.

In my own opinion, I think Mokyr starts to get closer to the mark when he discusses knowledge “storage”, access costs and multiplier effects from basic knowledge-based technologies or techniques. Like some other recent writers, he also tries to find analogies with evolutionary biology. For example:

Much like DNA, useful knowledge does not exist by itself; it has to be “carried” by people or in storage
devices. Unlike DNA, however, carriers can acquire and shed knowledge so that the selection process is quite different. This difference raises the question of how it is transmitted over time, and whether it can actually shrink as well as expand.

One of the real advantages of this book is to move forward a re-think of the “great man” or “great event” approach to history. There are indeed complicated forces at work. I think Mokyr summarizes well this transition when he states:

A century ago, historians of technology felt that individual inventors were the main actors that brought about
the Industrial Revolution. Such heroic interpretations were discarded in favor of views that emphasized deeper economic and social factors such as institutions, incentives, demand, and factor prices. It seems, however, that the crucial elements were neither brilliant individuals nor the impersonal forces governing the masses, but a small group of at most a few thousand peopled who formed a creative community based on the exchange of knowledge. Engineers, mechanics, chemists, physicians, and natural philosophers formed circles in which access to knowledge was the primary objective. Paired with the appreciation that such knowledge could be the base of ever-expanding prosperity, these elite networks were indispensible, even if individual members were not. Theories that link education and human capital of technological progress need to stress the importance of these small creative communities jointly with wider phenomena such as literacy rates and universal schooling.

There is so much to like and to be impressed with this book and even later Mokyr writings. My two criticisms are that, first, I found the pseudo-science of his knowledge labels confusing (I kept having to mentally translate the omega symbol) and I disliked the naming distinctions between propositional and prescriptive, even though I think the concepts are spot on.

My second criticism, a more major one, is that Mokyr notes, but does not adequately pursue, “In the decades after 1815, a veritable explosion of technical literature took place. Comprehensive technical compendia appeared in every industrial field.” Statements such as these, and there are many in the book, hint at perhaps some fundamental drivers. Mokyr has provided the raw grist for answering his starting question of why such massive economic growth occurred in conjunction with the era of the Industrial Revolution. He has made many insights and posited new
factors to explain this salutory discontinuity from all prior human history. But, in this reviewer’s opinion, he still leaves the why tantalizingly close but still unanswered. The fixity of information and growing storehouses because of declining production and access costs remain too poorly explored.

Jewels & Doubloons An AI3 Jewels & Doubloon Winner

Posted by AI3's author, Mike Bergman Posted on July 6, 2006 at 10:03 pm in Adaptive Information, Book Reviews | Comments (1)
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Posted:June 29, 2006

It is the sheer complexity associated with many decisions that defies the orderly application of the rational calculations of economic theory.

— Paul Ormerod

Paul Ormerod’s Why Most Things Fail: Evolution, Extinction and Economics
begins with the observation that failure is everywhere but is not the subject of standard analysis by the economics profession.  Since the advent of the modern corporation, 22% of the top 100 companies at any given time drop from the elite rankings in the next decade, 10% of all companies fail each year (granted, mostly the newbies), and 50% of globally successful companies go extinct within the lifetime of a modern human.  Why?

Ormerod brings a journalist’s and economic historian’s perspective to the question.  He snorts at general equilibrium theory as being fundamentally at odds with how the real economy works.  Standard supply curves?  NO.  Demand curves?  NO.  Setting price at marginal costs?  NO.  Perfect competition?  NO.  Perfect information?  NO.  Eventually rising marginal costs with greater production?  RARELY.

Indeed, his attack on conventional economic thinking caused the reviewer in the Financial Times to rejoin:

For the foes he attacks are straw men. The simplifying assumptions of perfect competition and general equilibrium analysis are just that: no serious economist is unaware of their limitations. Economic models are not reality, but tools to help us think about reality. Only late in the day does Ormerod reluctantly admit the difference between claiming that economic agents act in a certain way for certain reasons, and arguing that for simplifying purposes, they act as if they do.

Yet the book peters out with a limp call for companies to "Innovate! Innovate!" This sounds like the guff of management textbooks. Actually it is worse. Other books about corporate failure that reach the same conclusion have an organisational theory behind them. Richard Foster and Sarah Kaplan, in Creative Destruction, suggest that companies fail because they cannot reallocate resources as rapidly as markets. Clayton Christensen, in The Innovator's Dilemma, says established companies cannot embrace discontinuous improvements. Ormerod has nothing to say about the internal innovation process: his analysis is a system analysis.

I’m not surprised that professional economists would find this book lacking.  Yet for most of us that have only taken Economics 101 or mostly get our economics from pop economists on news and business programs, Ormerod raises important questions and brings forth important ideas.  There is indeed much that the conventional economics community has gotten wrong or has been too simplistic about.  This book is a very good re-entry into economics if you have been away for a while.

Ormerod’s major thesis — and what caught my eye in getting the book in the first place — is that there are many parallels between biological evolution and the behavior and extinction of firms.  For this, Ormerod especially points to both systems as being characterized by much uncertainty and complexity.  No argument there.

In knocking down the pins of conventional textbook answers, Ormerod covers topics such as game theory, bounded rationality, probablity theory and power laws, invoking names and characters such as Von Neumann, Hayek, Stiglitz and others along the way.  His thesis also allows him to explore the question of exogenous and endogenous causes with some freshness.

Strangely, though, he is virtually silent on the real commonality between economic and biological systems — namely the central importance of information — and gets into a very strange and indefensible analysis of punctuated equilibria and extinctions for species spanning 550 million years in comparison to visual correlations that create an "immediate impression of similarity" with graphs of firm extinctions over the past 83 years.  As Ormerod states,

The relationship that describes the connection between the frequency and size of extinctions in biological species is the same as that which describes the extinctions of companies.  The timescales differ dramatically, but frequency and size are connected identically [my emphasis] in both.

Hogwash.

Ormerod gravely mixes samples, causality and power curves.  Indeed, similar power curves can be constructed for Web site popularity or term frequencies in the English language (among many others), which surely have nothing to do with "truths" about the extinctions of economic firms.  Also, given Ormerod’s thesis, he could have gotten some additional interesting mileage from Iansiti and Levien’s business ecosystem theory of The Keystone Advantage.

There is certainly insight that uncertainty makes it difficult to foolproof against the future and is one reason why things fail, also certainly compounded by complexity.  I also think Ormerod is able to make a pretty good case for how acquiring knowledge can help buffer against these factors. 

So, I give this book 5 stars for readability and provoking thought; indeed, it has gotten me to get re-acquainted with recent economics literature.  But I can only give it 1 to 2 stars for its logical side due to its mis-labored analogies and poor analysis.

BTW, for an intro to more serious discussions about the relationships of evolution and economics, see writers such as Nelson and Winter, Galor, Mokyr, or Ziman, among others, or the listings at IDEAS: Papers on Economics and Evolution from the Max Planck Institute.

Posted by AI3's author, Mike Bergman Posted on June 29, 2006 at 11:13 am in Adaptive Information, Adaptive Innovation, Book Reviews | Comments (0)
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Posted:June 27, 2006

I don’t generally rant on this blog, but after having just about puked on too many Web 2.0 references, I’m now choking on new Web 3.0 references.  (For those not in the know, Web 3.0 is the "real" semantic Web stuff, while Web 2.0 is that oh-so tired tagging and mashup shit.)

Well, the escalation now appears clear.  We’re now seeing a proliferation of Web 3.0 posts today in order to set some distinctions.  Don’t like 3.0, not enough horsepower?  How about I see that and raise you to 4.0?  But why end there?  After all, high school was terribly fun and clever. . . .   

So, the heck with it.  I decided to jump right to the jugular:

Hey, ninety eight point six, it’s good to have you back again. oh,
Hey, ninety eight point six, her lovin’ is the medicine that
saaaved me,
Oh, I love my baby.

It’s so cool to be on the cutting edge . . . .

Posted by AI3's author, Mike Bergman Posted on June 27, 2006 at 6:32 pm in Semantic Web, Site-related | Comments (1)
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Posted:June 26, 2006

I recently re-read a book from David M. Levy from 2001 entitled, Scrolling Forward: Making Sense of Documents in the Digital Age to re-check it for some quotes and citations. The book retains its original flavor of keen insight with a general overall sense of disappointment that more of the mark could have been hit.

The first contribution of the book is to provide insight on what exactly is a document. Like many common and prosaic words, the idea of what constitutes a document proves to be more than a little challenging. As Levy says, the word document is often:

. . . used to designate the kinds of materials that have traditionally appeared on paper, such as legal contracts (e.g., wills) and identity papers (e.g., passports). This is much narrower that the use I intend, which is broad enough to include not only things written on paper but videotapes, films, audiotapes, and all manner of digital materials, including text files, spreadsheets, and Web pages.

(Here are a couple of definitional challenges. On the one hand, an entire paper document can be reproduced as a single Web page or split into numerous parts and therefore many Web pages. Alternatively, an encyclopedia could be interpreted as a single document in one case, or each of its split-out articles as separate documents in their own right.)

Levy illustrates the real role of a document as an artifact of historical fixity by the case of the lowly sales receipt, dozens of which pepper our daily lives and go without notice. The paper receipt most often contains information on the amount, location, for what and time of the transaction, say for buying a deli sandwich.  But through the Middle Ages and into the 1700s, witnesses (wit, to know) were required to vouch (act as a witness) that any economic transaction had indeed taken place. In other words, a simple and taken-for-granted paper document such as the sales receipt (or voucher) was a key enabler in oiling the wheels of commerce.  A simple slip of paper replaces the hassle and expense of a physical witness.

Other documents, of course, enabled coordination of train schedules, ledger accounting and other economic benefits, plus, also of course, the spreading of ideas and knowledge, fiction and non-fiction. Levy tells similar stories regarding the emergence of greeting cards, post cards and the postal service.

Levy works best when he attempts to fulfill his stated aim of placing documents within their own cultural time and place. The story is thus anecdotal and diverse from Woody Allen's Annie Hall to Walt Whitman's Leaves of Grass. The result is this book is a surprisingly literal treatment given the author's doctoral background and then professorship in information science.

While attempts are made to relate this material to information and library science, indeed to the emergence of the digital age, the book ends up feeling fragmented and scattered, lacking an articulated thesis. For example, no mention whatsoever is made of Elizabeth Eisenstein's 1979 classic book, The Printing Press as an Agent of Change, which postulated the role of written documents in the Reformation and the Scientific Revolution, among other historical epochs. The concluding chapters ramble from earthquakes to car advertising to "existential/religious perspectives." After a promising start, I felt like the air had been let out of the balloon by book's end.

I obviously enjoyed this book enough to read it again, and I recommend it to others mostly because of its episodic keen insights. Finally, I should note that any book with documents as its subject should take the time to include an index — shame, shame.

Posted by AI3's author, Mike Bergman Posted on June 26, 2006 at 9:24 pm in Adaptive Information, Book Reviews | Comments (1)
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Posted:June 25, 2006

The term ‘information architects’ was first coined by
Richard Saul Wurman in his 1997 book of the same name:

There is a tsunami of data that is crashing onto the beaches of the
civilized world. This is a tidal wave of unrelated, growing data formed in bits and bytes, coming in an unorganized, uncontrolled, incoherent
cacophony of foam. None of it is easily related, none of it comes with any organization methodology.

Now for the good news: There is a dune on the beach. There is a breakwater in the ocean that is clearly emerging in these last fleeting moments of the 20th century. The breakwater is indeed breaking up the tsunami of data and focusing it in a more organized way to answer our questions and concerns. There is a new breed of graphic designers, exhibition designers, illustrators and photographers, whose passion it is to make the complex clear.

I call this new breed of talented thinkers Information Architects . . .

Though ‘information architecture’ was perhaps first popularized and adopted from librarians or practitioners in information science, there is of course a substantial overlap with those computer scientists who are concerned with such areas as information retrieval, text indexing and categorization, classification, metadata and user interfaces and experience.  However, like many other domains that have similar topic interests but different academic training, largely different networks and terminology may develop.  (The example of pattern matching comes to mind where researchers in communications, streaming media, bioinformatics, information retrieval, and statistics — among others — too rarely share algorithms and insights.)

I have recently discovered a very useful source of information arcitecture materials, called IAwiki.net.  Launched in 2001 by Eric Scheid, the wiki now contains more than 1,000 topic pages from ACM to XML and links to about 300 IA professionals.

So, if you have interest in any of the nouns mentioned in this post, check out this wiki.  I think you will find plenty of value and may choose to offer insights of your own.

Posted by AI3's author, Mike Bergman Posted on June 25, 2006 at 6:28 pm in Adaptive Information | Comments (0)
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