Does Human Knowledge Double Every 5 Years?

Chinese Papers in Nanotechnology

Well, I was going to wait before starting on nanotechnology, but I don't have a convenient place to park this information, so you get it in toto:

From PhyiscsToday.org: "A paper by Ping Zhou and Loet Leydesdorff (PDF) suggests that China is rapidly developing research expertise in nanotechnology. Six years ago, US-based scientists published 50% of the papers in the journal Nanotechnology and China accounted for zero. Today 25% of papers in the journal are from US-based scientists and 15% from China. Zhou and Leydesdorff report that between 1999 and 2005, for 85 journals in the fields of chemistry, physics and material sciences that are relevant to nanotechnology, the number of papers published by China rose exponentially to 8.34%, while papers published by other countries either remained steady or declined. China's overall world share in science journals is 6.52%, suggesting that China is aiming to be at the forefront of research into nanotechnology."

The paper this article is based on talks about a ratio between GDP and R&D, the return of overseas scholars and other factors. The paper then details research that looks like what we're trying to do here--except they're doing it a lot more... scientifically. They even call it scientometric analysis! I'm going to steal that...

Where I am using crude statistics available for free and for fun, they use "indicators like total publications, total citation rates, percentage of world share of citations, as well as the top one percent of most highly cited papers in order to measure scientific output."

Something else I'm going to have to look at--"For the input indicators, we used the OECD's Main Science and Technology Studies published online and in print (OECD 2004)." Like me, they experienced difficulty in searching large databases of publications. They found their own solution, but it won't help me going forward.

Some interesting findings:

• Between 1999 and 2004, China moved from 10th to 5th place in terms of overall scientific publications
• The overall US share has dropped from 35% to 30% between 1992 and 2004 (but if the overall number is rising, who cares?)
• Countries where English is commonly spoken (and written, obviously) appear to have an advantage when it comes to having your paper cited by others
• More than 4,400 science and technology journals were published in China in 2001
• Half a million articles are published annually in Chinese journals
• It appears that Chinese scientists read the work of scientists in other countries, but that international scientists don't read (or at least don't cite) work published in Chinese journals (with the exception of some Chinese journals that are published in English)
• The Chinese government declared nanotechnology a critical R&D priority in 2001, and a group of commissions and ministries issued a strategic plan for development of nanotechnology through to 2010
• Definitions are tough. It was hard for the researchers to find all nano-related papers, and only nano-related papers. (I know what that's like--and what it means. You actually have to read, instead of count, and that takes time)
• The paper's authors use really, really cool graphs to show their work. I am extremely jealous

Now I just have to find out where they got those numbers at the end of the news release...  they could have listed those 85 journals...

Human Knowledge and Mars

(This part is repeated from the previous post): NASA and the Smithsonian Institute maintain a database called the Astrophysics Data System. Harvard University is kind enough to host it here. Available to you and I is an abstracting service which will return brief descriptions of articles found by keyword searches. You see where I'm going here?

For a description of coverage and limitations of the database, click here. Then, let's have some fun.

A search for the word Mars in titles and abstracts performed on April 21 2007 returned 20,978 results.

(This is where the new stuff starts): Here we report on 5-year periods going back to 1900. We show annual percentage growth on the previous 5-year total. It isn't pretty--much more like real life than any smooth logarithmic curve. In 22 five-year periods, we show an annual percentage growth above 14% (shown in bold) in only 3 five-year periods(you need a 14.87% annual growth to double every five years). In 7 of the five-year periods, there is a decline in publications (inefficient post, wars, depressions, Mars being further away... lots of logical reasons why this might have occurred).

The serious question is, if our studies of Mars, which have benefited from major government funding from several large governments, and have also benefited from being topical, exciting, and having large sources of data available recently, do not show exponential growth, where would we expect to actually find a doubling of human knowledge every five years? If not here, where?

What I think it shows me is that when there is a lot of funding, real news, a research goal, and the availability of new and important data, we focus on the subject, do the research and improve knowledge. But for extended periods, things just sort of tick along, improving respectably in many years, but showing declines in others. What do you make of the following?

Click if you want to see the numbers.

Human Knowledge and Mars

NASA and the Smithsonian Institute maintain a database called the Astrophysics Data System. Harvard University is kind enough to host it here. Available to you and I is an abstracting service which will return brief descriptions of articles found by keyword searches. You see where I'm going here?

For a description of coverage and limitations of the database, click here. Then, let's have some fun.

A search for the word Mars in titles and abstracts performed on April 21 2007 returned 20,978 results. Let's pretend for the sake of argument that this represents all human knowledge ever gained about Mars. (This may be as close to the truth as we will ever get on this weblog when searching for information about fields of study--but it is obviously not true, so take it with a grain of salt.)

What is the CAGR (Compound Annual Growth Rate) in publications? Well, if we were really strict, we would measure from the date of the first document, which is... 1644. That would give us a CAGR of 2.32% and we would all get very depressed. But a more realistic starting point would be 1830, when regular publications started. This would remove only 10 documents from our total, and would yield a CAGR of 5.78%. That's much better, but far short of doubling every five years. (At that rate, human knowledge about Mars would double every 12.34 years.) Nonetheless, half of the documents in the database have been published since 1993. (Hey--that doubled in 14 years... is the rate of doubling slowing down?)

Just the metadata I got from the site is fascinating, and I'll be referring to it later, looking for short term bursts and lags (and wondering if Mars' distance from the Earth is one of the causes, for example). But here's some interesting information.

The most recent, published in April 2007, is titled "Subsurface Radar Sounding of the South Polar Layered Deposits of Mars and written by Plaut, Jeffrey J.; Picardi, Giovanni; Safaeinili, Ali; Ivanov, Anton B.; Milkovich, Sarah M.; Cicchetti, Andrea; Kofman, Wlodek; Mouginot, Jérémie; Farrell, William M.; Phillips, Roger J.; and 14 coauthors

Document #3001 is titled "Review of the trajectory and atmospheric structure reconstruction for Mars Pathfinder", written by Withers, Paul; Towner, Martin; Hathi, Brijen; Zarnecki, John

Document #6001 is titled "History and perspectives of scientific ballooning," by Frank Lefevre. Hmm. Well, document #6002 is "Stability and evolution of the climate system of Mars," written in 2001 by Stability and evolution of the climate system of Mars

Document #9001 is titled "Mobilization of dust on the Mars surface by the impact of small cosmic bodies," written in 1997 by Rybakov, V. A.; Nemtchinov, I. V.; Shuvalov, V. V.; Artemiev, V. I.; Medveduk, S. A.

Document #12001 is titled "Dry Carbonate Formation on Mars: A Plausible Sink for an Early Dense CO2 Atmosphere?", written in 1990 by Stephens, S. K.; Stevenson, D. J.

Document #15001 is titled "Stratigraphic relationships within Martian polar CAP deposits" written in 1982 by Howard, A. D.; Cutts, J. A.; Blasius, K. R.

Document #18001 is titled "The major Martian dust storms of 1971 and 1973" written in 1974 by Martin, L. J.

The very first document, written in 1644 by Grandami, Jacques, is titled "Nova demonstratio immobilitatis terrae petita EX virtvte magnetica."

If that's a little dense for you, the second, written in 1672 by Flamstead, John, is "An Extract of Mr. Flamstead's Letter Written to the Publisher from Derby Novemb. 16. 1672. Concerning the Appulses, by Him Calculated for A. 1673. of the Moon, and the Other Planets to Fixed Stars; Together with an Observation of the Planet Mars, Made by the Same"

Human Knowledge and Mars

I off-handedly chose Mars as a subject for investigation, basically because there have been several missions to the Red Planet in the past 5 years. Those missions were expensive, they were designed to gather knowledge about Mars... so if human knowledge is doubling every 5 years in any given sector, we might imagine that one of the sectors is Mars. Well, I actually have an ulterior motive, but that's for the end of this post.

The Exploration of Mars is beautifully detailed on Wikipedia. The first probe to actually get close to Mars was in 1962, the Soviet mission Beta Nu 1. It was followed by the US Mariner 4 in 1964. So we have been collecting data from space missions for 45 years. The 1996 Mars Global Surveyor effectively returned more data than all previous missions combined, and the data is available to the public.

The Mars Pathfinder landed on Mars on July 4, 1997, and a remote controlled rover called Sojourner decamped from the lander and went walkabout. Pathfinder returned 16,500 images from the lander and 550 images from the rover, as well as 15 chemical analyses of rock and soil and extensive data on winds and weather. This was followed by a spate of unsuccessful attempts to return to Mars.

In 2001 the run of bad luck ended when NASA's Mars Odyssey orbiter arrived. Its mission is to use spectrometers and imagers to hunt for evidence of past or present water and volcanic activity on Mars. In 2002, it was announced that the probe's gamma ray spectrometer and neutron spectrometer had detected large amounts of hydrogen, indicating that there are vast deposits of water ice in the upper three meters of Mars' soil within 60° latitude of the south pole.

NASA sent a pair of twin rovers toward the planet as part of the Mars Exploration Rover Mission. On 10 June 2003, NASA's MER-A (Spirit) Mars Exploration Rover was launched. It successfully landed in Gusev Crater (believed once to have been a crater lake) on 3 January 2004. It examined rock and soil for evidence of the area's history of water. On July 7, 2003, a second rover, MER-B (Opportunity) was launched. It landed on 24 January 2004 in Meridiani Planum (where there are large deposits of hematite, indicating the presence of past water) to carry out similar geological work.

Mars Reconnaissance Orbiter is a multipurpose spacecraft designed to conduct reconnaissance and exploration of Mars from orbit. The $720 million USD spacecraft was built by Lockheed Martin under the supervision of the Jet Propulsion Laboratory, launched August 12, 2005, and attained Martian orbit on March 10, 2006.

The MRO contains a host of scientific instruments such as the HiRISE camera, CRISM, and SHARAD. The HiRISE camera is used to analyze Martian landforms, whereas CRISM and SHARAD can detect water, ice, and minerals on and below the surface. (In case you haven't guessed, I'm just copying from Wikipedia here.)

Now, the Wikipedia article on Mars itself is quite long. It contains very little material that could have been written before the past 45 years--the planet was mapped in 1840, some basic astronomical information has been long known, but almost all of what Wikipedia thinks is important is recent, and most of it really, really recent. Of the 79 citations at the bottom of the article, 30 were written after 2004.

So I'm ready to admit that human knowledge about Mars has doubled every 5 years since 1962. I'll be searching for more evidence to back this up. But here's my ulterior motive: I think that new sectors, or sectors that have big money thrown at it, or sectors where there is a clear public good to be obtained from applied research, might well indeed experience exponential increases in knowledge. But are they sustained? Does knowledge gained transfer readily to similar sectors? (Do we, for example, know as much about Venus or Mercury?) If new knowledge gained in the past 5 years about Mars (and I include getting to Mars, data collection design, etc.) leads to similar increases in knowledge about other planets in our solar system, then I think we're on to something here.

Wow!

I was about to click out of the Lawrence Livermore Laboratory's website when I stumbled across this news release: "Lawrence Livermore National Laboratory’s institutional “Grand Challenge” scientific computing program has allocated 83.7 million CPU hours to 17 research projects ranging from astrophysics, chemistry, materials and biosciences to earthquake and climate simulation on Laboratory supercomputers."

... "Research projects were selected by the Laboratory’s Deputy Director for Science and Technology, the Laboratory Strategic Program Board and the Laboratory Science and Technology Office. To be considered, proposals had to “address a grand-challenge-scale, mission-related problem that promises unprecedented discoveries in a particular scientific and/or engineering field of research, and if successful, will result in high-level recognition by the scientific community at large.”

... "For example, a multi-institutional group of climate scientists will conduct the most detailed multi-decade global climate simulations ever performed as part of the larger effort to understand how climate changes over time. “By performing these climate simulations of unprecedented detail and fidelity and making them available to the climate research community, we have the potential to dramatically advance our understanding of climate and how it may be affected by anthropogenic factors,”

Grand Challenge recipients have been allocated time on Atlas, the new 44 teraFLOP (trillion floating operations per second) machine and Thunder, a 22 teraFLOP machine -- systems dedicated to unclassified research through the Laboratory’s Multi-programmatic and Institutional Computing program. Central processing unit or CPU time is measured across the multiple CPUs in a computer. For example, two CPU hours can be one CPU used for two hours or two CPUs used for one hour. High performance computers generally consist of thousands of CPUs; the Atlas system contains 9, 216 CPUs."

You know, it's stories like this that make me optimistic about the future.  "Over the last 10 years, high performance computing resources dedicated to unclassified institutional research have increased more than a thousand fold from 72 giga (72,000 million) FLOPS in 1997 to 81 teraFLOPS today."

This is what the Singularity protagonists are pointing to. Prosaic sad sacks like me are stubbornly waiting to see the results of the research performed. Something inside me grumbles that a well-designed program wouldn't need 82 million hours to execute... (this from someone who's never written a line of code in his life).

On the other hand, there are specific sectors where this exercise in and of itself might result in the doubling of human knowledge.

And Still More About Human Knowledge and Global Warming

If you go to climateprediction.net you can volunteer your computer's spare time to help run climate models. I found the site thanks to an article at NewScientist.com. The project, started in 2002, appears to have run the Hadley model 172,229 times (at the time I checked), apparently with minor changes in assumptions to check on the different outputs that result. Check here for the aggregated results of the first 27,000 runs. (I think--I didn't spend a whole lot of time on the site.)

This is exactly what I would expect to find if human knowledge is advancing rapidly and incorporating multi-disciplinary tools and knowledge to forge ahead. Hope I find a lot more like this.

Yet More on Human Knowledge and Global Warming

Okay, stick with me here. The IPCC summary for policy makers (PDF) of their draft report on Global Warming was issued in February--the draft will be released in May. It used data from over a dozen climate models in preparing their reports. The 2001 report relied heavily on a model developed by the UK's very own Hadley Centre. The policy summary notes the following problems with the climate models they used:

• systematic biases in simulation of the Southern Ocean, which is important for the transfer of heat between the atmosphere and the oceans
• on-going problems in simulating the El Nino - Southern Oscillation (ENSO) cycle, which is a major factor in the Earth's climates
• poor simulation of precipitation events: "in general, models tend to produce too many days of weak precipitation (<10 mm per day) and too little precipitation overall  in intense events (>10 mm per day)"
• substantial uncertainty in the simulation of feedback from sea-ice, which are coupled with polar cloud formation and transpor of heat through the polar oceans

Given the potential gravity of worst-case scenarios of the effects of global warming, you cannot wait for perfect data before attempting to make policy decisions. But these are not trivial issues.

This should be a hotbed of scientific activity, and we should see lots of research being done on the issues above. In particular, we should see attempts to harness Moore's Law, which baldly states that computer power has doubled every 18 months to 2 years in the recent past to make climate models more detailed, easier to test and quicker to run. So what do we find?

Here are some positive indications:

• (I thought this was much more exciting until I looked at the publication date of 2002) (From Science Daily) "Atmospheric scientists from Lawrence Livermore National Laboratory have performed the first global climate simulations with spatial resolutions of roughly 50 km (30 miles). This capability will be used to assess climate change and its societal impacts. Typical global climate simulations use spatial resolutions of about 300 kilometers (186 miles), which limits their ability to simulate climate and climate change on a regional scale "
• This (also from Science Daily, but from 2007) is the type of article I was hoping to find: Open Source Software Toolkit Plays Key Role In New Climate Simulations  Science Daily — The Model Coupling Toolkit created by the U.S. Department of Energy's Argonne National Laboratory played a key role in the climate simulations used in preparing the new U.N. report "Climate Change 2007: The Physical Science Basis." The Model Coupling Toolkit (MCT) is an open source software library for constructing parallel coupled models from individual parallel models. MCT is designed for high performance and portability. All of the simulations of the Community Climate System Model used the Model Coupling Toolkit." This is good--although the skeptic in me wonders if it means that any errors in the Model Coupling Toolkit are therefore replicated in all models that use it...
• The University of Arizona researcher Joellen Russell, working with a group of researchers from National Oceanographic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, published (in December 2006) a paper called "The Southern Hemisphere Westerlies in a Warming World: Propping open the Door to the Deep Ocean,” which may specifically address some of the IPCC study's self-identified areas of weakness. Although I'm just interested in the fact that the research took place within the past 5 years, the results (that the Southern oceans can absorb more carbon dioxide and additional heat, perhaps reducing the rate of global warming), are not in strict accordance with what the IPCC is publishing.

I'll do a sequel to this post very soon. I don't like blog posts that go on forever, and besides, breakfast is waiting.

Back to Work

I'll be writing a lot more about the Singularity later. Let's go back to the basic building blocks that will educate my later writing.

We return to the numbers of people in higher education. If this number is growing exponentially, there might be reason to think human knowledge will too, in future. Specifically, in India, we find "India's provision for higher education rose from a meagre 200,000 at the time of Independence to an astronomical 5,000,000 college and university places by 1998." Those words come from Gajaraj Dhanarajan, President and CEO, The Commonwealth of Learning, Vancouver, Canada. He was speaking in August of 2000 at the 11th General Conference--Universities as the Gateway to the Future.

Let's see--India achieved independence in 1947 (right? Might be off a year--Nope. Google says August 15, 1947). If Indian university students had doubled in number every five years since then, starting from a base of 200,000, they should now have 516 million university students. So, if they have started growing exponentially, it is recently. (How many university students should India have? Using figures from Dhanarajan's speech, to have the same rate of university enrollment as Canada {5%}, for example, India should have had 50 million university students in 2000. Room for improvement here).

This is actually fairly important. The Compound Annual Growth Rate (CAGR) for the Indian university population is 5.51%. The CAGR needed to double in five years is 14.87%. A CAGR of 5.51% means the population doubles every 13 years, instead of five. We won't get where we need to be at this rate.

If you've been reading from the bottom up, you'll be able to join in the refrain--"Great growth. Not doubling."

Time to Get Serious

If you type the search string "human knowledge doubles every five years" into Google today, it will return about 1,580,000 results.

The first result is from a Bellagio newsletter reporting on a conference, and it uses the sentence as if it were a given. The second is from President Clinton's 1998 speech to the AAS, where he asserts it as a given. The first post in this weblog quotes from it.

The third result is why I started this weblog. Here is part of the opening from The Low Beyond, by Eliezer Yudkowsky.

1: The End of History

It began three and a half billion years ago in a pool of muck, when a molecule made a copy of itself and so became the ultimate ancestor of all earthly life.

It began four million years ago, when brain volumes began climbing rapidly in the hominid line.

Fifty thousand years ago with the rise of Homo sapiens sapiens.
Ten thousand years ago with the invention of civilization.
Five hundred years ago with the invention of the printing press.
Fifty years ago with the invention of the computer.

In less than thirty years, it will end.

At some point in the near future, someone will come up with a method of increasing the maximum intelligence on the planet - either coding a true Artificial Intelligence or enhancing human intelligence.  An enhanced human would be better at thinking up ways of enhancing humans; would have an "increased capacity for invention".  What would this increased ability be directed at?  Creating the next generation of enhanced humans.

And what would those doubly enhanced minds do?  Research methods on triply enhanced humans, or build AI minds operating at computer speeds.  And an AI would be able to reprogram itself, directly, to run faster - or smarter.  And then our crystal ball explodes, "life as we know it" is over, and everything we know goes out the window. "

Yudkowsky, like Ray Kurzweil and other advocates of what is known as the Singularity, extrapolates progress in computing sciences from past performance increases in computer efficiency, networking and falling prices for computation and memory. At some point in our lifetimes, computing will be so fast, so efficient, so networked and have access to so much memory, that we will be able to create artificial intelligence (AI). We will then be able to assign this AI the task of creating an even better computing machine, as well as assisting human intelligence in solving real world problems. Because of the increased capabilities of AI (which include indefatiguability and no need for coffe breaks as well as very high intelligence and concentration), progress will be so rapid that life as we know it will change dramatically and in a very short timeframe.

I really want this to be true. But I am afraid that a) we are exaggerating our progress on many fronts and b) even if we can build this better box, we will need to improve our knowledge exponentially before the box is built so we know what to put into it. And I see no evidence as yet that we'll be able to fill the box.

We'll be talking a lot about this--and I hope to involve some of the protagonists in the discussion. But if this isn't your cup of tea, you can adjust your visits to this site accordingly.

Whew--We Find That Something Has Doubled

It would have been truly strange not to find some area where there is evidence of a doubling of activity. I actually think we'll find more as we go on. But the past two weeks have been somewhat discouraging, so I'm happy to report that we see clear evidence of a doubling in the growth rate of patent filings in China over the past 5 years, and a doubling of the total number of academic patent filings worldwide between 1995 and 2000.

An article titled 'Rapid Patenting Growth By Academic Institutes In The People's Republic Of China' by Simon Pratt, published in June 2005 shows a doubling of the growth rate (not the actual numbers) of patent filings by academic institutions in China, and a doubling of academic patent filings worldwide by universities between 1995 and 2000 (see chart below). Sadly, that growth rate has not been sustained since 2000.

It is not unalloyed good news--worldwide, academic patent filings are a response to governmental decisions to allow universities to retain, license and exploit intellectual property, so there may just be substitution here--the same patent might previously have been filed by an individual at the academic institution or someone who had access to the reseach. But I'm so happy to find something relevant that has doubled in five years that this seems like a minor quibble.

Here is the chart showing the number of academic patent filings worldwide since 1980. As with all the charts on this weblog, clicking on the chart will bring it up in a readable size.