Does Human Knowledge Double Every 5 Years?

Sobering News

The post below from yesterday, which details the stately, rather than exponential, increase in granted patents in the U.S., has really got me thinking, and I think we'd better report on the state of play here.

Let's detail those areas where we have seen adequate growth to double human knowledge every 5 years:

Update: We have since found other areas where the CAGR is sufficient to double human knowledge every five years:

Update 2: A modest review revealed errors in my calculations regarding oncology. Its position has changed (and not for the better).

Prions, where academic journal publications have increased at a CAGR of 25.57%, and patents have increased by 33.76%

Software, where academic journal publications have increased at a CAGR of 22.83% and patents have increased by 33.53%

Post-graduate enrollment in China, which has increased at a CAGR of 22.38% (although see below for more discouraging information about the growth of tertiary education worldwide)

(All percentages are CAGR (compound annual growth rate.)

1. Nanotechnology, with a blistering growth in publications of 97.16% per year. Patents, 76.15%.

2. Global Warming publications, with a of 16.85%

3. Total Chinese patent applications, at 25% per annum

4. Chinese computing patents, 58.29%

5. Chinese telecommunications patents, 30.26%

(was oncology)

7. Epidemiology patents, 22.76%

So far, that's it.

Now let's look at where we did not find anything like doubling every five years (remembering that we need a CAGR of 14.87% to double in five years time):

Update: We have now found other areas where human knowledge does not appear to be growing at a rate that will double in five years time:

Worldwide university enrollment, which has a CAGR of 4.85%

Alzheimer's disease, where academic publications have a CAGR of 9.65% and patents a CAGR of 11.26%

Programming, where academic publications have a CAGR of 12.55% and patents a CAGR of 12.83%

Chinese university enrollment, with a CAGR of 9.76%

1. U.S. patents granted, 5.21%

2. Epidemiology publications, 8.85%

3. Shale oil extraction, publications 5.59%, patents, 2.61%

4. Publications on Mars, 5.78% (see also here and here)

5. U.S. Book publishing, 5.14%

6. Indian university enrolment since 1947, 5.51%

7. Climate Models, 12.66% (Very close to 5-year doubling rate of 14.87%)

8. Improvements in Climate Models, 13.76% (Also very close)

9. Growth in publication of scientific and technical papers, 1995-1999

             OECD 0.1%

             U.S., -1.8%

             Canada, -2.2%

             UK, -0.1%

             Netherlands, -0.5%

10. Publications in astrophysics, 4% (since 1970)

11. Growth in percentage of cancer patients surviving 5 years after diagnosis, 0.7% (1960-2005)

12. Drop in percentage of soldiers dying from wounds received in battle, 1.54% (1941-2006)

13. Projected growth in number of scientists (U.S.), next ten years, 7.18%

14. Patent filings in India, last five years, 8.45%

15. Increase in patent filings, World International Patent Office, 1 year, 6.4%

6. Oncology pubications, 9.23% (revised)

Considering I cherry picked areas that I thought would be most likely to show robust growth, this is scary.

          

Back to Global Warming

And back to Scirus, the compendium of scientific publication. Okay, it's a search engine returning titles of journals, patents, etc.

What are we to make of the fact that searching for global warming on Scirus returns 100,000 more results than a similar search for nanotechnology? It's been studied for 20 years longer than nanotechnology, so global warming should reflect that... But there are 8,000 fewer academic articles in the database (28,000 for nanotech vs. 20,584 for global warming). What does that mean?

We found 5,184 patents on the Scirus database for nanotechnology. For global warming... 9,419. Scientists and technologists have been studying global warming for more than twice as long, so that may mean nothing. But, let's look at the statistics and see what they tell us.

As shown below, playing by the same rules as we did for nanotechnology and the study of Mars, we hereby proclaim a base year of 1975, as it saw 18 journal articles published and one patent filed. That gives us 31 years to measure growth. This indeed gives us a CAGR (Compound Annual Growth Rate) of 16.85%, which in fact does show doubling every five years! Hooray, we have another winner!

The CAGR for patents is higher yet--26.08%. (But again, it seems to have leveled off in 2002.) We saw below that growth was disappointing in the subsector of climate modelling, but it's being more than made up for elsewhere.

But, given the potential gravity of the consequences of global warming, am I the only one to look at the growth rates of human knowledge in this field, compare them to the growth rates for nanotechnology, and feel slightly disappointed?

The data is below. Click if you want to see the numbers.

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.

Global Warming and Hypothesis 3

If you've read the beginning days of this weblog (which today celebrates two weeks of actual existence), you might recall that I am trying to test three hypotheses. The third is that we are disproving (or falsifying) incorrect assumptions, hypotheses and opinions at a rate that effectively doubles human knowledge (knowing something is not true is really, really important). This is just as important in global warming as with anything else.

Critics of global warming have for years pointed to the fact that satellite observations, taken from a single dataset, showed slight cooling in the tropical troposphere since 1979. Since this conflicted with what climate models predict, this was a serious problem for those attempting to warn the public about global warming.

So they went and got more data, which is what you're supposed to do. This 2005 news release from the Lawrence Livermore Lab (close to where I grew up), shows that further research found better data that agrees with modern climate models.

As there is still considerable controversy about global warming, there's a whole lot more falsifying and disproving that needs to be done, probably on both sides of the fence. If you think about it, the  beneficiaries of this disproof of the previous data are the critics of global warming as well as those who strongly believe, as critics now actually have to examine their assumptions, look for more or better data, or find explanations for what this research showed.

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.

More on Human Knowledge and Global Warming

In an article titled 'General Circulation Models of the Atmosphere,' Spencer Weart tell us that John von Neumann began advocating using computers to study the climate back in 1946, shortly after his computer ENIAC became operational. Getting grants from the Navy, the Air Force and the Weather Bureau, the study of climate began.

So 1946 was the starting point. For the next 25 years, the American Meteoroligical Society's  entire spectrum of journals (including the Journal of Applied Meteorology, the Bulletin of the American Meteorological Society, Journal of Atmospheric Sciences, Journal of Physical Oceanography, Monthly Weather Review and more...) published a total of 111 papers containing the phrase "climate models" somewhere in the text or title. The first one was titled 'The Unusual Weather and Circulation of the 1948-1949 Winter,' by William H. Klein. It was published in April 1949, 58 years ago. Two articles were published containing that phrase in 1950.

Let's pretend that each paper published with the phrase "climate models" is one unit of advancing human knowledge. If human knowledge doubles every five years, how many papers should be published in 2005? We know that the percentage growth should be 14.87%, and we know we should expect to see 2,048 articles in 2004. So... drum roll please... it's 881. Less than half of what we would expect. Lest you think it was just an off year, in 2005 it was 899 and in 2006 it actually dropped to 894.

I can think of a dozen possible explanations--a presidential administration unfriendly to the concept, waiting on the IPCC to publish findings in 2007... but the fact is, if we have doubled our knowledge of climate models in the past 5 years, we're not writing about it in America.

Is the rest of the world making up for America's shortfall? Well, not if you're depending on the International Journal of Meteorology, which returns 8 results for a search on climate models over a 25-year span. (But I think it's a search issue.) The International Journal for Climatology returns 37 results. I'm sure I'm missing important sources, but none are jumping up and biting me. The Royal Meteorological Society has 36 results. The UK government is considerably more supportive of research into global warming than the current American administration. I really thought there would be more.

Human Knowledge and Global Warming

A Google search for "improvements in climate models" returns 2.64 million results. Of those, Google Scholar claims 138,000 articles about the search term.

Of the first 20 results in Google Scholar, only one was written after the year 2000. Published in the Journal of Climate, it describes The Community Climate System Model, Version 2.  However, searching with the same term on the Journal of Climate's search engine returns 3,348 results.  Sorting in reverse chronological order, the first 10 were published this month, April 2007. In fact, I counted 279 entries published in the past year. Here are the annual results for fifth years historically:

2006: 273

2001: 203

1996: 162

1991: 54

1986: 49

1981: 24

1976: 14

1971: 3

1966: 0

Global warming is a popular field for researchers and government funding is there. Advances in computer hardware and software means that improvements in global climate models are possible, as well as desirable.

The fact that the last time entries doubled over a five-year span was between 1991 and 1996 is a bit disturbing. A new field of science with optimum research conditions that cannot sustain doubling of cutting edge knowledge after a mere 25 years cannot bode well for those who depend on doubling every five years.

Maybe the papers are four times as good...

It Should Be Lumpy, Right?

We wouldn't expect a uniform doubling of human knowledge within a 5-year timeframe, right? Even if this is a law as inexorable as Moore's (and that doesn't seem as inexorable as it once was, or am I reading the Dell ads wrong?), one would reasonably expect that human knowledge would advance a little in some areas and a lot in others. You with me?

Given what the world's attention has been focused on since 2002, here are some of the areas where I think human knowledge should have increased fastest:

• Epidemiology, thanks to SARS and Avian flu
• Biofuels
• Vaccines
• Proteome
• Oil extraction from rock and shale
• Mars
• Genetically Modified Organisms
• Fishery management
• Global warming
• Solar activity
• The Long Tail
• Stem cell cultivation
• Infectious diseases

I will treat this as a proxy list of subject areas to explore. I'm going to be digging around to see if we've seen dramatic advances in any or all of these. I'll probably dedicate a few posts to each of them. Got any suggestions?