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Mr Beavin explains that ITAR may define technology “exports” as any disclosure to foreign nationals, such as web posts, international scientific meetings and exchanges, conferences and technical data. “The academic world is used to sharing and it really makes it hard for scientific exchange. Nobody wants to be slapped with a gigantic fee or go to jail. It is scaring everyone into not talking, and that’s crippling for science.”

Bill Joy, a founder of Sun Microsystems, cited the bomb in a famous 2000 article in the magazine Wired on the dangers of robots in which he argued that some technologies were so dangerous they should be “relinquished.” He said it was common for scientists and engineers to fail “to understand the consequences of our inventions while we are in the rapture of discovery” and, as a result, he said, “we have yet to come to terms with the fact that the most compelling 21st-century technologies — robotics, genetic engineering and nanotechnology — pose a different threat than the technologies that have come before. They are so powerful they can spawn whole new classes of accidents and abuses.”

This technology might be useful, even life-saving. But it would inevitably produce environmental effects impossible to predict and impossible to undo. So a growing number of experts say it is time for broad discussion of how and by whom it should be used, or if it should be tried at all.

Similar questions are being raised about nanotechnology, robotics and other powerful emerging technologies. There are even those who suggest humanity should collectively decide to turn away from some new technologies as inherently dangerous.

Dr. Arkin said robotics researchers should consider not just how to make robots more capable, but also who must bear responsibility for their actions and how much human operators should remain “in the loop,” particularly with machines to aid soldiers on the battlefield or the disabled in their homes.

But he added that progress in robotics was so “insidious” that people might not realize they had ventured into ethically challenging territory until too late.

Chris Anderson’s and Peter Norvig’s idea that theory will not be needed when everything will be measured is an interesting perspective. But in my opinion new theories will emerge when we will be able to fully understand those masses of new data. Not just through machine learning approaches or static network analyses but also by using advanced computer simulations and other tools that will track network dynamics. The theories that will emerge from looking at these massive and diverse datasets, collected from natural and man-made systems, are those complex systems design principles that emerge when you take a step back and look at common features shared among different systems. Speaking of man-made systems, hardware and robotics, as well as synthetic biology seems to be the next two frontiers. When we get to a point that we almost fully understand natural systems, we will always have to continually study the complex systems that we are creating.

With a new analytical technique, a fingerprint can now reveal much more than the identity of a person. It can now also identify what the person has been touching: drugs, explosives or poisons, for example.

I then talked about three major initiatives that I am working on with colleagues at IBM, which illustrate this evolution toward complex IT-based systems: cloud computing; globally integrated business systems; and virtual worlds.

Systems can no longer be understood with well defined deterministic principles, but require more statistically oriented approaches - think of the difference between classical mechanics and quantum mechanics.  Models of such complex systems require considerable, empirically based approximations - think of the difference between modeling a computer's processing unit and modeling the World Wide Web.  Systems become unpredictable and can no longer be viewed as machines that you automate with computers.  You need a combination of talented people and real time, information-based tools to deal with such complex, unpredictable systems.

When the work touches on issues that worry the public, affect the economy or polarize politics, the news media and advocates of all stripes dive in. Under nonstop scrutiny, conflicting findings can make news coverage veer from one extreme to another, resulting in a kind of journalistic whiplash for the public.

This has been true for decades in health coverage. But lately the phenomenon has been glaringly apparent on the global warming beat.

Scientists see persistent disputes as the normal stuttering journey toward improved understanding of how the world works. But many fear that the herky-jerky trajectory is distracting the public from the undisputed basics and blocking change. “One of the things that troubles me most is that the rapid-fire publication of unsettled results in highly visible venues creates the impression that the scientific community has no idea what’s going on,” said W. Tad Pfeffer, an expert on Greenland’s ice sheets at the University of Colorado.

To support clarity, Stephen H. Schneider, a climatologist at Stanford, helped create a glossary defining what is meant by phrases like “very likely” (greater than 90 percent confidence) in the reports from the Intergovernmental Panel on Climate Change. In a news media universe where specialized reporting is declining and a Web mash-up of instant opinion and information is emerging, Dr. Schneider said, it is ever more important for scientists to take responsibility for communicating in ways that stick, while sticking with the facts.

He said his advice for scientists who wanted to “dampen the whiplash effect” was to “discuss the ‘So what?’ implications of the work explicitly, rather than leaving that step to advocates or politicians, or reporters.”

Increasingly, scientists are taking their message straight to the public. Realclimate.org, Climatepolicy.org and Climateethics.org are among Web sites where issues are explored in an ongoing way, rather than in response to news releases and scientific papers. Other new Web ventures, like ClimateCentral.org at Princeton and the Yale Forum on Climate Change and the Media, focus on improving media coverage.

In my Perspectives series I’ve been exploring some key relationships between Microsoft and external partners: Mercy Corps, NASA, the Library of Congress, the community of scientific and scholarly publishers, and individual scientific researchers including George Hripcsak and Dennis Baldocchi.

EARTH—Former vice president Al Gore—who for the past three decades has unsuccessfully attempted to warn humanity of the coming destruction of our planet, only to be mocked and derided by the very people he has tried to save—launched his infant son into space Monday in the faint hope that his only child would reach the safety of another world.

"There is nothing left now but to ensure that my infant son does not meet the same fate as the rest of my doomed race," Gore said. "I will send him to a new planet, where he will, I hope, be raised by simple but kindly country folk and grow up to be a hero and protector to his adopted home."

In the final moments before the Earth's destruction, Gore expressed hope that his son would one day grow up to carry on his mission by fighting for truth, justice, and the American way elsewhere in the universe, using his Earth-given superpowers to become a champion of the downtrodden and a reducer of carbon emissions across the galaxy.

"On his new planet, Kal-Al's Earth physiology will react to the radiation of a differently colored sun, causing him to develop abilities far beyond those of mortal men," political analyst Sig Schuster said. "He will be faster than a speeding Prius, stronger than the existing Superfund program, and able to leap mountains of red tape in a single bound. These superpowers will sustain him in his never-ending battle against conservatives, wealthy industrialists, and other environmental supervillains."

"In brightly hued tights, it will be harder for people there to ignore him when he takes on his new planet's lobbyists, auto manufacturers, and enemies of justice," Schuster said. "A bold and eye-catching unitard will give Kal-Al, last son of Earth, a formidable tool for protecting his new planet, a power more awesome than any his father could have dreamed of: the power of charisma."

Such a photon counter is essential if quantum cryptography is to work, because it will allow what are known as quantum repeaters to be built. In a classical telecommunications system the signal has to be boosted by a repeater every 80km or so. But a traditional repeater destroys the quantum states of the photons, such as their planes of polarisation. That does not matter for classical telecoms, but matters very much for quantum cryptography, which relies on the fact that no eavesdropper can intercept the message without changing those quantum states, and thus giving away the fact that he is on the line.

Summary

In accordance with Division G, Title II,  Section 218 of PL 110-161 (Consolidated Appropriations Act, 2008 ), the NIH voluntary Public Access Policy (NOT-OD-05-022) is now mandatory. The law states:

The Director of the National Institutes of Health shall require that all investigators funded by the NIH submit or have submitted for them to the National Library of Medicine’s PubMed Central an electronic version of their final, peer-reviewed manuscripts upon acceptance for publication, to be made publicly available no later than 12 months after the official date of publication: Provided, That the NIH shall implement the public access policy in a manner consistent with copyright law.

We should aim to create an open scientific culture where as much information as possible is moved out of people’s heads and labs, onto the network, and into tools which can help us structure and filter the information. This means everything - data, scientific opinions, questions, ideas, folk knowledge, workflows, and everything else - the works. Information not on the network can’t do any good.

The challenge of achieving a more open culture is also being confronted in popular culture. People such as Richard Stallman, Lawrence Lessig, Yochai Benkler, Cory Doctorow, and many others have described the benefits openness brings in a networked world, and developed tools such as Creative Commons licensing and free and open source software to help promote a more open culture, and fight the forces inhibiting it. As we have seen, however, science faces a unique set of forces that inhibit open culture - the centuries-old subsidy of old ways of sharing knowledge - and this requires a new understanding of how to overcome those forces.

If you’d like to read more, I recommend Bill Hooker’s series of essays on open science, Mitchell Waldrop’s article in Scientific American, and the Science Commons as starting places. There are some great communities of people online engaged in building a more open scientific culture - many of those people can be found in the Life Scientists and Science2.0 rooms on FriendFeed. Check them out.

The conclusion of all this statistical work was that, as more and more
articles are readily available online, researchers, on average, cite
fewer articles. The articles that are cited are newer, and fewer
distinct articles receive attention. The results of the explosion of easily available articles, according to Evans, is
that "researchers can more easily find prevailing opinion, they are
more likely to follow it, leading to more citations referencing fewer
articles." As a side effect of this, a scientific consensus will typically form more
rapidly. The other side of this is that papers containing ideas that
don't catch quickly will be forgotten by the scientific world much
faster.

His initial call to arms on Wednesday contained some partisan elements. He was accusing the Democrats of trying to limit member access to sites such as Twitter.

JC: That's an easy question, wind energy is an important part of the solution to make America energy independent. We need to basically check all the boxes on the list of things we need to do to make America energy independent, but we need to do it without subsidies. I strenuously oppose subsidies for any industry out there and it is heavily subsidized as is ethanol, as are biofuels, as are a number of other alternative energy sources. And I particularly resent the fact that the majority party in Congress passed a, I think it was a 15 billion dollar tax increase on just the American oil companies late last year and then handed the money over to the alternative energy guys so essentially part of the money you're paying at the pump when you're you know filling up your car with a $70 tank of gas, a chunk of that money is going straight to these alternative energy guys that are heavily subsidized.

JC: Top priority to me is to double the budget of the National Science Foundation, Congress needs to double the budget of the National Institute of Health, we need to double the investment that we're making in energy research, particularly in the Department of Energy and create a Manhattan style project of making America energy independent in the next ten years and at the same time making sure that we maintain our competitive edge in the world through a massive investment in the National Science Foundation and then also I think we should do a Manhattan style project of curing cancer with an investment in the competitive peer review process at the National Institutes of Health.

But I would point you to, I've been a subscriber to the Journal of Nature and Science for many, many, many years, I'm an amateur astronomer, I'm an amateur geologist always loved planetary sciences. I'm a mineral and fossil collector. I've always been fascinated with science, so I read those journals cover to cover, I don't pretend to completely understand a lot of the molecular the biological articles that I read, but I've a pretty good grasp on a lot of the others, and I have seen articles for example recently in one of the November 2007 issues of Nature they reported on a group of Japanese scientists who added five growth factors to adult stem cells and converted those adult skin cells into pluri-potent skin cells that could then grow into any number of different things.

There may be something to this observation. Many sciences such as astronomy, physics, genomics, linguistics, and geology are generating extremely huge datasets and constant streams of data in the petabyte level today. They'll be in the exabyte level in a decade. Using old fashioned "machine learning," computers can extract patterns in this ocean of data that no human could ever possibly detect. These patterns are correlations. They may or may not be causative, but we can learn new things. Therefore they accomplish what science does, although not in the traditional manner.

For a long time we were stuck on the idea that the brain somehow contained a "model" of reality, and that AI would be achieved by constructing similar "models." What's a model? There are 2 requirements: 1) Something that works, and 2) Something we understand. Our large, distributed, petabyte-scale creations, whether GenBank or Google, are starting to grasp reality in ways that work just fine but that we don't necessarily understand.

Perhaps understanding and answers are overrated. "The problem with computers," Pablo Picasso is rumored to have said, "is that they only give you answers."  These huge data-driven correlative systems will give us lots of answers -- good answers -- but that is all they will give us. That's what the OneComputer does --  gives us good answers. In the coming world of cloud computing perfectly good answers will become a commodity. The real value of the rest of science then becomes asking good questions.

Instead Google operates a very large dataset of observations which show that for any given spelling of a word, x number of people say “yes” when asked if they meant to spell word “y.” Google’s spelling engine consists entirely of these datapoints, rather than any notion of what correct English spelling is. That is why the same system can correct spelling in any language.

As Pinker tells us, language acquisition is an example of the problem of induction — making generalizations about the future from historic data.  Both humans and increasingly “machines” run continuous experiments in order to adjust their internal models.  

Drew Berry, one of the world's foremost animators working in biomedical visualisation, has concentrated much of his work on cellular visualisation - animating the behaviour, dynamics and physical properties of DNA, bio-molecules and proteins.

Each of the animations is founded on the latest scientific data sets, such as X-ray crystallography, so that details such as molecular shapes, sizes and real-time dynamics are distinctively accurate. Through the animations, an audience can be placed face-to-face with a neuron pulsing with electric messages, or inside an artery to view the rush of blood cells, or hover above the growing knot of flesh in a tumour.