[EAS] Computers and the Practice of Science

Sat Mar 25 20:14:41 EST 2006

Dear Colleagues -

Calls for a Kuhnian "paradigm shift" in how 
science is done, given the evolution of 
computing, are not new. Stephen Wolfram's book "A 
New Kind of Science" and his many related 
lectures, are one such instance. But it has been 
happening cumulatively in many fields all along, 
e.g. genetics and high-energy physics.

This week's Economist reviews a broader vision of 
computer science's influence, including 
computer-based hypothesis formation:
<http://www.economist.com/science/PrinterFriendly.cfm?story_id=5655067> 
(and text below), in a report titled "Toward 2020 
Science," by some 34 eminent scientists
<http://research.microsoft.com/towards2020science/background_overview.htm>.

To quote The Economist:
"It is, perhaps, hardly unexpected that if 34 
scientists with an interest in computing are 
asked to comment on the importance of computer 
science, they will find that it is, indeed, "The 
Future". Even so, the team's case is a 
respectable one. Indeed, this week's issue of 
Nature has given it "earthquake 
coverage"-devoting several pages to news and 
comment about the report."

    --PJK

---------------
The scientific method

Computing the future
Mar 23rd 2006
From The Economist print edition

The practice of science may be undergoing yet another revolution

WHAT makes a scientific revolution? Thomas Kuhn 
famously described it as a "paradigm shift"-the 
change that takes place when one idea is 
overtaken by another, usually through the 
replacement over time of the generation of 
scientists who adhered to an old idea with 
another that cleaves to a new one. These 
revolutions can be triggered by technological 
breakthroughs, such as the construction of the 
first telescope (which overthrew the Aristotelian 
idea that heavenly bodies are perfect and 
unchanging) and by conceptual breakthroughs such 
as the invention of calculus (which allowed the 
laws of motion to be formulated). This week, a 
group of computer scientists claimed that 
developments in their subject will trigger a 
scientific revolution of similar proportions in 
the next 15 years.

That claim is not being made lightly. Some 34 of 
the world's leading biologists, physicists, 
chemists, Earth scientists and computer 
scientists, led by Stephen Emmott, of Microsoft 
Research in Cambridge, Britain, have spent the 
past eight months trying to understand how future 
developments in computing science might influence 
science as a whole. They have concluded, in a 
report called ""Towards 2020 Science", that 
computing no longer merely helps scientists with 
their work. Instead, its concepts, tools and 
theorems have become integrated into the fabric 
of science itself. Indeed, computer science 
produces "an orderly, formal framework and 
exploratory apparatus for other sciences," 
according to George Djorgovski, an astrophysicist 
at the California Institute of Technology.

There is no doubt that computing has become 
increasingly important to science over the years. 
The volume of data produced doubles every year, 
according to Alexander Szalay, another 
astrophysicist, who works at Johns Hopkins 
University in Baltimore. Particle-physics 
experiments are particularly notorious in this 
respect. The next big physics experiment will be 
the Large Hadron Collider currently being built 
at CERN, a particle-physics laboratory in Geneva. 
It is expected to produce 800m collisions a 
second when it starts operations next year. This 
will result in a data flow of 1 gigabyte per 
second, enough to fill a DVD every five seconds. 
All this information must be transmitted from 
CERN to laboratories around the world for 
analysis. The computer science being put in place 
to deal with this and similar phenomena forms the 
technological aspect of the predicted scientific 
revolution.

Such solutions, however, are merely an extension 
of the existing paradigm of collecting and 
ordering data by whatever technological means are 
available, but leaving the value-added stuff of 
interpretation to the human brain. What really 
interested Dr Emmott's team was whether computers 
could participate meaningfully in this process, 
too. That truly would be a paradigm shift in 
scientific method.

And computer science does, indeed, seem to be 
developing a role not only in handling data, but 
also in analysing and interpreting them. For 
example, devices such as "data cubes" organise 
information as a collection of independent 
variables (such as the charges and energies of 
particles involved in collisions) and their 
dependent measurements (where and when the 
collisions took place). This saves physicists a 
lot of work in deciphering the links between, 
say, the time elapsed since the initial collision 
and the types of particle existing at that 
moment. Meanwhile, in meteorology and 
epidemiology, computer science is being used to 
develop models of climate change and the spread 
of diseases including bird flu, SARS (severe 
acute respiratory syndrome) and malaria.

Roboboffin

Stephen Muggleton, the head of computational 
bio-informatics at Imperial College, London, has, 
meanwhile, taken the involvement of computers 
with data handling one step further. He argues 
they will soon play a role in formulating 
scientific hypotheses and designing and running 
experiments to test them. The data deluge is such 
that human beings can no longer be expected to 
spot patterns in the data. Nor can they grasp the 
size and complexity of one database and see how 
it relates to another. Computers-he dubs them 
"robot scientists"-can help by learning how to do 
the job. A couple of years ago, for example, a 
team led by Ross King of the University of Wales, 
Aberystwyth, demonstrated that a learning machine 
performed better than humans at selecting 
experiments that would discriminate between 
hypotheses about the genetics of yeast.

And it is in biology that computing science is 
likely to have its greatest impact. The report 
argues that cells and complex cellular systems 
can be seen as information-processing systems, so 
there is a natural fit between them and 
computational logic circuits. That could lead to 
new developments in biology, biotechnology and 
medicine, as well as in computer science.

It is, perhaps, hardly unexpected that if 34 
scientists with an interest in computing are 
asked to comment on the importance of computer 
science, they will find that it is, indeed, "The 
Future". Even so, the team's case is a 
respectable one. Indeed, this week's issue of 
Nature has given it "earthquake 
coverage"-devoting several pages to news and 
comment about the report. And Microsoft Research 
Cambridge also announced that it will provide 
¤2.5m ($3m) to support research that addresses 
policy areas outlined by the report, which 
include a reform of the education system and the 
creation of new kinds of research institutes. 
This is, admittedly, a small sum. If Microsoft 
wants the world to take its claims-and those of 
the scientists it commissioned to think about 
such things-seriously, then it should put more 
money where its mouth is. Otherwise the old guard 
might hang around rather longer than expected.