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.

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Posted:May 15, 2006

There is often no substitute for learning about subjects than from the key practitioners and thinkers behind them. Even though one noted researcher in this field, Hamish Cunningham at the University of Sheffield, a specialist in human language technology (HLT), does sometimes cite the low 5% retention of information from a lecture, I am finding repeated viewings and rewinds to be a pretty effective way to learn:

[The original Learning Pyramid analysis traces back to the 1960s and is now attributed to the NTL Institute; the actual picture is from Dr. Tom Bayston at the University of Central Florida. It would be interesting to know whether repeated viewings of online videos, or simultaneous video + Powerpoints act to increase retention. (Actually, blogging about something may be at the higher end of retention within the Learning Pyramid.) I'm also finding that the combination of video/slides with the audio explanations to be immensely helpful.]

Nonetheless, I have previously reported on some great online Semantic Web videos, for example, one by Henry Story and another by Tim Berners-Lee, and faced with a rainy day I tried to be more comprehensive in my discovery.

I found many distribution points, but was most taken with a series of video tutorials and training sessions from SEKT (Semantically-enabled Knowledge Technologies), a three-year, EU-sponsored project that ends at the end of 2006.

SEKT – Online video presentations. SEKT offers 19 different ones; some with syncrhonized slides or alternatively slides (PPTs) separately. My three favorites (block out four hours!!!) are:

Besdies these, here are some other good intro to advanced videos that you can watch off the Web:

So, wait for that rainy day, grab some hot chocolate, and enjoy!

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Posted by AI3's author, Mike Bergman Posted on May 15, 2006 at 3:51 pm in Jewels & Doubloons, Semantic Web | Comments (0)
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Posted:April 10, 2006

On March 14, Tim Berners-Lee returned to Oxford University for a keynote address sponsored by the e-Horizons Institute in affiliation with the Oxford Internet Institute, the Oxford e-Research Centre and the School of Electronics and Computer Science of the University of Southhampton. Sponsorship for the presentation was provided by the British Computer Society.

The 100-min talk entitled, “The Future of the Web,” is available for online viewing or download via a number of different formats. After a slow start, TBL hits his stride and some of his slides (see this W3C listing) are especially good, particularly in the latter part of the presentation.

The major thrust of the talk is on the semantic Web, with attention to why adoption may be perceived as slow, with social and policy factors affecting that. Berners-Lee cogently recalls that the original WWW Web took about five years before it transitioned from geeks to commercial, and he predicts the same for the semantic Web. While it is true we now have the phenomenon of the Web coloring (or “colouring” depending on your semantics) expectations about the pace of adoption of the semantic Web, I thought this quote from the talk was the best by TBL in looking back to his original Web efforts in 1990:

It was really difficult to explain to people what the Web would be like before the Web. The fact it was so difficult to explain to people what the Web was like before the Web [existed] is now extremely difficult to explain to anybody after the Web.

In other words, like all broadly accepted breakthroughs, after acceptance it is hard to understand what life was like before them or why it was so amazing they were innovated and got adopted in the first place.

Check out this talk. It will re-instill perspective and give you a glimpse as to how constant efforts eventually produce results if the vision is compelling.

Jewels & Doubloons An AI3 Jewels & Doubloon Winner

Posted by AI3's author, Mike Bergman Posted on April 10, 2006 at 8:47 pm in Jewels & Doubloons, Semantic Web | Comments (1)
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