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I am a former Microsoft programmer who wrote a book (for a general audience) about the future of software called After the Software Wars. Eric Klien has invited me to post on this blog. Here are several more sections on AI topics. I hope you find these pages food for thought and I appreciate any feedback.

The future is open source everything.

—Linus Torvalds

That knowledge has become the resource, rather than a resource, is what makes our society post-capitalist.

—Peter Drucker, 1993

Imagine 1,000 people, broken up into groups of five, working on two hundred separate encyclopedias, versus that same number of people working on one encyclopedia? Which one will be the best? This sounds like a silly analogy when described in the context of an encyclopedia, but it is exactly what is going on in artificial intelligence (AI) research today.1 Some say free software doesn’t work in theory, but it does work in practice. In truth, it “works” in proportion to the number of people who are working together, and their collective efficiency.

In early drafts of this book, I had positioned this chapter after the one explaining economic and legal issues around free software. However, I now believe it is important to discuss artificial intelligence separately and first, because AI is the holy-grail of computing, and the reason we haven’t solved AI is that there are no free software codebases that have gained critical mass. Far more than enough people are out there, but they are usually working in teams of one or two people, or proprietary codebases.

Deep Blue has been Deep-Sixed

Some people worry that artificial intelligence will make us feel inferior, but then, anybody in his right mind should have an inferiority complex every time he looks at a flower.

—Alan Kay, computer scientist

The source code for IBM’s Deep Blue, the first chess machine to beat then-reigning World Champion Gary Kasparov, was built by a team of about five people. That code has been languishing in a vault at IBM ever since because it was not created under a license that would enable further use by anyone, even though IBM is not attempting to make money from the code or using it for anything.

The second best chess engine in the world, Deep Junior, is also not free, and is therefore being worked on by a very small team. If we have only small teams of people attacking AI, or writing code and then locking it away, we are not going to make progress any time soon towards truly smart software.

Today’s chess computers have no true AI in them; they simply play moves, and then use human-created analysis to measure the result. If you were to go tweak the computer’s value for how much a queen is worth compared to a pawn, the machine would start losing and wouldn’t even understand why. It comes off as intelligent only because it has very smart chess experts programming the computer precisely how to analyze moves, and to rate the relative importance of pieces and their locations, etc.

Deep Blue could analyze two hundred million positions per second, compared to grandmasters who can analyze only 3 positions per second. Who is to say where that code might be today if chess AI aficionados around the world had been hacking on it for the last 10 years?

DARPA Grand Challenge

Proprietary software developers have the advantages money provides; free software developers need to make advantages for each other. I hope some day we will have a large collection of free libraries that have no parallel available to proprietary software, providing useful modules to serve as building blocks in new free software, and adding up to a major advantage for further free software development. What does society need? It needs information that is truly available to its citizens—for example, programs that people can read, fix, adapt, and improve, not just operate. But what software owners typically deliver is a black box that we can’t study or change.

—Richard Stallman

The hardest computing challenges we face are man-made: language, roads and spam. Take, for instance, robot-driven cars. We could do this without a vision system, and modify every road on the planet by adding driving rails or other guides for robot-driven cars, but it is much cheaper and safer to build software for cars to travel on roads as they exist today — a chaotic mess.

At the annual American Association for the Advancement of Science (AAAS) conference in February 2007, the “consensus” among the scientists was that we will have driverless cars by 2030. This prediction is meaningless because those working on the problem are not working together, just as those working on the best chess software are not working together. Furthermore, as American cancer researcher Sidney Farber has said, “Any man who predicts a date for discovery is no longer a scientist.”

Today, Lexus has a car that can parallel park itself, but its vision system needs only a very vague idea of the obstacles around it to accomplish this task. The challenge of building a robot-driven car rests in creating a vision system that makes sense of painted lines, freeway signs, and the other obstacles on the road, including dirtbags not following “the rules”.

The Defense Advanced Research Projects Agency (DARPA), which unlike Al Gore, really invented the Internet, has sponsored several contests to build robot-driven vehicles:


Stanley, Stanford University’s winning entry for the 2005 challenge. It might not run over a Stop sign, but it wouldn’t know to stop.

Like the parallel parking scenario, the DARPA Grand Challenge of 2004 required only a simple vision system. Competing cars traveled over a mostly empty dirt road and were given a detailed series of map points. Even so, many of the cars didn’t finish, or perform confidently. There is an expression in engineering called “garbage in, garbage out”; as such, if a car sees “poorly”, it drives poorly.

What was disappointing about the first challenge was that an enormous amount of software was written to operate these vehicles yet none of it has been released (especially the vision system) for others to review, comment on, improve, etc. I visited Stanford’s Stanley website and could find no link to the source code, or even information such as the programming language it was written in.

Some might wonder why people should work together in a contest, but if all the cars used rubber tires, Intel processors and the Linux kernel, would you say they were not competing? It is a race, with the fastest hardware and driving style winning in the end. By working together on some of the software, engineers can focus more on the hardware, which is the fun stuff.

The following is a description of the computer vision pipeline required to successfully operate a driverless car. Whereas Stanley’s entire software team involved only 12 part-time people, the vision software alone is a problem so complicated it will take an effort comparable in complexity to the Linux kernel to build it:

Image acquisition: Converting sensor inputs from 2 or more cameras, radar, heat, etc. into a 3-dimensional image sequence

Pre-processing: Noise reduction, contrast enhancement

Feature extraction: lines, edges, shape, motion

Detection/Segmentation: Find portions of the images that need further analysis (highway signs)

High-level processing: Data verification, text recognition, object analysis and categorization

The 5 stages of an image recognition pipeline.

A lot of software needs to be written in support of such a system:


The vision pipeline is the hardest part of creating a robot-driven car, but even such diagnostic software is non-trivial.

In 2007, there was a new DARPA Urban challenge. This is a sample of the information given to the contestants:


It is easier and safer to program a car to recognize a Stop sign than it is to point out the location of all of them.

Constructing a vision pipeline that can drive in an urban environment presents a much harder software problem. However, if you look at the vision requirements needed to solve the Urban Challenge, it is clear that recognizing shapes and motion is all that is required, and those are the same requirements as had existed in the 2004 challenge! But even in the 2007 contest, there was no more sharing than in the previous contest.

Once we develop the vision system, everything else is technically easy. Video games contain computer-controlled drivers that can race you while shooting and swearing at you. Their trick is that they already have detailed information about all of the objects in their simulated world.

After we’ve built a vision system, there are still many fun challenges to tackle: preparing for Congressional hearings to argue that these cars should have a speed limit controlled by the computer, or telling your car not to drive aggressively and spill your champagne, or testing and building confidence in such a system.2

Eventually, our roads will get smart. Once we have traffic information, we can have computers efficiently route vehicles around any congestion. A study found that traffic jams cost the average large city $1 billion dollars a year.

No organization today, including Microsoft and Google, contains hundreds of computer vision experts. Do you think GM would be gutsy enough to fund a team of 100 vision experts even if they thought they could corner this market?

There are enough people worldwide working on the vision problem right now. If we could pool their efforts into one codebase, written in a modern programming language, we could have robot-driven cars in five years. It is not a matter of invention, it is a matter of engineering.

1 One website documents 60 pieces of source code that perform Fourier transformations, which is an important software building block. The situation is the same for neural networks, computer vision, and many other advanced technologies.

2 There are various privacy issues inherent in robot-driven cars. When computers know their location, it becomes easy to build a “black box” that would record all this information and even transmit it to the government. We need to make sure that machines owned by a human stay under his control, and do not become controlled by the government without a court order and a compelling burden of proof.

This is a crosspost from Nextbigfuture

I looked at nuclear winter and city firestorms a few months ago I will summarize the case I made then in the next section. There is significant additions based on my further research and email exchanges that I had with Prof Alan Robock and Brian Toon who wrote the nuclear winter research.

The Steps needed to prove nuclear winter:
1. Prove that enough cities will have firestorms or big enough fires (the claim here is that does not happen)
2. Prove that when enough cities in a suffient area have big fire that enough smoke and soot gets into the stratosphere (trouble with this claim because of the Kuwait fires)
3. Prove that condition persists and effects climate as per models (others have questioned that but this issue is not addressed here

The nuclear winter case is predictated on getting 150 million tons (150 teragram case) of soot, smoke into the stratosphere and having it stay there. The assumption seemed to be that the cities will be targeted and the cities will burn in massive firestorms. Alan Robock indicated that they only included a fire based on the radius of ignition from the atmospheric blasts. However, in the scientific american article and in their 2007 paper the stated assumptions are:

assuming each fire would burn the same area that actually did burn in Hiroshima and assuming an amount of burnable material per person based on various studies.

The implicit assumption is that all buildings react the way the buildings in Hiroshima reacted on that day.

Therefore, the results of Hiroshima are assumed in the Nuclear Winter models.
* 27 days without rain
* with breakfast burners that overturned in the blast and set fires
* mostly wood and paper buildings
* Hiroshima had a firestorm and burned five times more than Nagasaki. Nagasaki was not the best fire resistant city. Nagasaki had the same wood and paper buildings and high population density.
Recommendations
Build only with non-combustible materials (cement and brick that is made fire resistant or specially treated wood). Make the roofs, floors and shingles non-combustible. Add fire retardants to any high volume material that could become fuel loading material. Look at city planning to ensure less fire risk for the city. Have a plan for putting out city wide fires (like controlled flood from dams which are already near cities.)

Continue reading “Nuclear Winter and Fire and Reducing Fire Risks to Cities” | >

I am a former Microsoft programmer who wrote a book (for a general audience) about the future of software called After the Software Wars. Eric Klien has invited me to post on this blog. Here is my section entitled “Software and the Singularity”. I hope you find this food for thought and I appreciate any feedback.

Futurists talk about the “Singularity”, the time when computational capacity will surpass the capacity of human intelligence. Ray Kurzweil predicts it will happen in 2045. Therefore, according to its proponents, the world will be amazing then.3 The flaw with such a date estimate, other than the fact that they are always prone to extreme error, is that continuous learning is not yet a part of the foundation. Any AI code lives in the fringes of the software stack and is either proprietary or written by small teams of programmers.

I believe the benefits inherent in the singularity will happen as soon as our software becomes “smart” and we don’t need to wait for any further Moore’s law progress for that to happen. Computers today can do billions of operations per second, like add 123,456,789 and 987,654,321. If you could do that calculation in your head in one second, it would take you 30 years to do the billion that your computer can do in that second.

Even if you don’t think computers have the necessary hardware horsepower today, understand that in many scenarios, the size of the input is the primary driving factor to the processing power required to do the analysis. In image recognition for example, the amount of work required to interpret an image is mostly a function of the size of the image. Each step in the image recognition pipeline, and the processes that take place in our brain, dramatically reduce the amount of data from the previous step. At the beginning of the analysis might be a one million pixel image, requiring 3 million bytes of memory. At the end of the analysis is the data that you are looking at your house, a concept that requires only 10s of bytes to represent. The first step, working on the raw image, requires the most processing power, so therefore it is the image resolution (and frame rate) that set the requirements, values that are trivial to change. No one has shown robust vision recognition software running at any speed, on any sized image!

While a brain is different from a computer in that it does work in parallel, such parallelization only makes it happen faster, it does not change the result. Anything accomplished in our parallel brain could also be accomplished on computers of today, which can do only one thing at a time, but at the rate of billions per second. A 1-gigahertz processor can do 1,000 different operations on a million pieces of data in one second. With such speed, you don’t even need multiple processors! Even so, more parallelism is coming.4

3 His prediction is that the number of computers, times their computational capacity, will surpass the number of humans, times their computational capacity, in 2045. This calculation seems flawed for several reasons:

  1. We will be swimming in computational capacity long before then. An intelligent agent twice as fast as the previous one is not necessarily more useful.
  2. Many of the neurons of the brain are not spent on reason, and so shouldn’t be in the calculations.
  3. Billions of humans are merely subsisting, and are not plugged into the global grid, and so shouldn’t be measured.
  4. There is no amount of continuous learning built in to today’s software.

Each of these would tend to push Singularity closer and support the argument that the benefits of singularity are not waiting on hardware. Humans make computers smarter, and computers make humans smarter, so this feedback loop is another reason that makes 2045 a meaningless moment in time.

4 Most computers today contain a dual-core CPU and processor folks promise that 10 and more are coming. Intel’s processors also have parallel processing capabilities known as MMX and SSE that is easily adapted to the work of the early stages of any analysis pipeline. Intel would add even more of this parallel processing support if applications put them to better use. Furthermore, graphics cards exist primarily to do work in parallel, and this hardware could be adapted to AI if it is not usable already.

With our growing resources, the Lifeboat Foundation has teamed with the Singularity Hub as Media Sponsors for the 2010 Humanity+ Summit. If you have suggestions on future events that we should sponsor, please contact [email protected].

The summer 2010 “Humanity+ @ Harvard — The Rise Of The Citizen Scientist” conference is being held, after the inaugural conference in Los Angeles in December 2009, on the East Coast, at Harvard University’s prestigious Science Hall on June 12–13. Futurist, inventor, and author of the NYT bestselling book “The Singularity Is Near”, Ray Kurzweil is going to be keynote speaker of the conference.

Also speaking at the H+ Summit @ Harvard is Aubrey de Grey, a biomedical gerontologist based in Cambridge, UK, and is the Chief Science Officer of SENS Foundation, a California-based charity dedicated to combating the aging process. His talk, “Hype and anti-hype in academic biogerontology research: a call to action”, will analyze the interplay of over-pessimistic and over-optimistic positions with regards of research and development of cures, and propose solutions to alleviate the negative effects of both.

The theme is “The Rise Of The Citizen Scientist”, as illustrated in his talk by Alex Lightman, Executive Director of Humanity+:

“Knowledge may be expanding exponentially, but the current rate of civilizational learning and institutional upgrading is still far too slow in the century of peak oil, peak uranium, and ‘peak everything’. Humanity needs to gather vastly more data as part of ever larger and more widespread scientific experiments, and make science and technology flourish in streets, fields, and homes as well as in university and corporate laboratories.”

Humanity+ Summit @ Harvard is an unmissable event for everyone who is interested in the evolution of the rapidly changing human condition, and the impact of accelerating technological change on the daily lives of individuals, and on our society as a whole. Tickets start at only $150, with an additional 50% discount for students registering with the coupon STUDENTDISCOUNT (valid student ID required at the time of admission).

With over 40 speakers, and 50 sessions in two jam packed days, the attendees, and the speakers will have many opportunities to interact, and discuss, complementing the conference with the necessary networking component.

Other speakers already listed on the H+ Summit program page include:

  • David Orban, Chairman of Humanity+: “Intelligence Augmentation, Decision Power, And The Emerging Data Sphere”
  • Heather Knight, CTO of Humanity+: “Why Robots Need to Spend More Time in the Limelight”
  • Andrew Hessel, Co-Chair at Singularity University: “Altered Carbon: The Emerging Biological Diamond Age”
  • M. A. Greenstein, Art Center College of Design: “Sparking our Neural Humanity with Neurotech!”
  • Michael Smolens, CEO of dotSUB: “Removing language as a barrier to cross cultural communication”

New speakers will be announced in rapid succession, rounding out a schedule that is guaranteed to inform, intrigue, stimulate and provoke, in moving ahead our planetary understanding of the evolution of the human condition!

H+ Summit @ Harvard — The Rise Of The Citizen Scientist
June 12–13, Harvard University
Cambridge, MA

You can register at http://www.eventbrite.com/event/648806598/friendsofhplus/4141206940.

An obvious next step in the effort to dramatically lower the cost of access to low Earth orbit is to explore non-rocket options. A wide variety of ideas have been proposed, but it’s difficult to meaningfully compare them and to get a sense of what’s actually on the technology horizon. The best way to quantitatively assess these technologies is by using Technology Readiness Levels (TRLs). TRLs are used by NASA, the United States military, and many other agencies and companies worldwide. Typically there are nine levels, ranging from speculations on basic principles to full flight-tested status.

The system NASA uses can be summed up as follows:

TRL 1 Basic principles observed and reported
TRL 2 Technology concept and/or application formulated
TRL 3 Analytical and experimental critical function and/or characteristic proof-of concept
TRL 4 Component and/or breadboard validation in laboratory environment
TRL 5 Component and/or breadboard validation in relevant environment
TRL 6 System/subsystem model or prototype demonstration in a relevant environment (ground or space)
TRL 7 System prototype demonstration in a space environment
TRL 8 Actual system completed and “flight qualified” through test and demonstration (ground or space)
TRL 9 Actual system “flight proven” through successful mission operations.

Progress towards achieving a non-rocket space launch will be facilitated by popular understanding of each of these proposed technologies and their readiness level. This can serve to coordinate more work into those methods that are the most promising. I think it is important to distinguish between options with acceleration levels within the range human safety and those that would be useful only for cargo. Below I have listed some non-rocket space launch methods and my assessment of their technology readiness levels.

Spacegun: 6. The US Navy’s HARP Project launched a projectile to 180 km. With some level of rocket-powered assistance in reaching stable orbit, this method may be feasible for shipments of certain forms of freight.

Spaceplane: 6. Though a spaceplane prototype has been flown, this is not equivalent to an orbital flight. A spaceplane will need significantly more delta-v to reach orbit than a suborbital trajectory requires.

Orbital airship: 2. Though many subsystems have been flown, the problem of atmospheric drag on a full scale orbital airship appears to prevent this kind of architecture from reaching space.

Space Elevator: 3. The concept may be possible, albeit with major technological hurdles at the present time. A counterweight, such as an asteroid, needs to be positioned above geostationary orbit. The material of the elevator cable needs to have a very high tensile strength/mass ratio; no satisfactory material currently exists for this application. The problem of orbital collisions with the elevator has also not been resolved.

Electromagnetic catapult: 4. This structure could be built up the slope of a tall mountain to avoid much of the Earth’s atmosphere. Assuming a small amount of rocket power would be used after a vehicle exits the catapult, no insurmountable technological obstacles stand in the way of this method. The sheer scale of the project makes it difficult to develop the technology past level 4.

Are there any ideas we’re missing here?

Lee Smolin is said to believe (according to personal communication from Danila Medvedev who was told about it by John Smart. I tried to reach Smolin for comments, but failed) that global catastrophe is impossible, based on the following reasoning: the multiverse is dominated by those universes that are able to replicate. This Self-replication occurs in black holes, and in especially in those black holes, which are created civilizations. Thus, the parameters of the universe are selected so that civilization cannot self-destruct before they create black holes. As a result, all physical processes, in which civilization may self-destruct, are closed or highly unlikely. Early version of Smolin’s argument is here: http://en.wikipedia.org/wiki/Lee_Smolin but this early version was refuted in 2004, and so he (probably) added existence of civilization as another condition for cosmic natural selection. Anyway, even if it is not Smolin’s real line of thoughts, it is quite possible line of thoughts.

I think this argument is not persuasive, since the selection can operate both in the direction of universes with more viable civilizations, and in the direction of universes with a larger number of civilizations, just as biological evolution works to more robust offspring in some species (mammals) and in the larger number of offspring with lower viability (plants, for example, dandelion). Since some parameters for the development of civilizations is extremely difficult to adjust by the basic laws of nature (for example, the chances of nuclear war or a hostile AI), but it is easy to adjust the number of emerging civilizations, it seems to me that the universes, if they replicated with the help of civilizations, will use the strategy of dandelions, but not the strategy of mammals. So it will create many unstable civilization and we are most likely one of them (self indication assumption also help us to think so – see recent post of Katja Grace http://meteuphoric.wordpress.com/2010/03/23/sia-doomsday-the-filter-is-ahead/)

But still some pressure can exist for the preservation of civilization. Namely, if an atomic bomb would be as easy to create as a dynamite – much easier then on Earth (which depends on the quantity of uranium and its chemical and nuclear properties, ie, is determined by the original basic laws of the universe), then the chances of the average survival of civilization would be lower. If Smolin’s hypothesis is correct, then we should encounter insurmountable difficulties in creating nano-robots, microelectronics, needed for strong AI, harmful experiments on accelerators with strangelet (except those that lead to the creation of black holes and new universes), and in several other potentially dangerous technology trends that depend on their success from the basic properties of the universe, which may manifest itself in the peculiarities of its chemistry.

In addition, the evolution of universes by Smolin leads to the fact that civilization should create a black hole as early as possible in the course of its history, leading to replication of universes, because the later it happens, the greater the chances that the civilization will self-destruct before it can create black holes. In addition, the civilization is not required to survive after the moment of “replication” (though survival may be useful for the replication, if civilization creates a lot of black holes during its long existence.) From these two points, it follows that we may underestimate the risks from Hadron Collider in the creation of black holes.

I would repeat: early creation of a black hole suggested by Smolin and destroying the parent civilization, is very consistent with the situation with the Hadron Collider. Collider is a very early opportunity for us to create a black hole, as compared with another opportunity — to become a super-civilization and learn how to connect stars, so that they collapse into black holes. It will take millions of years and the chances to live up to this stage is much smaller. Also collider created black holes may be special, which is requirement for civilization driven replication of universes. However, the creation of black holes in collider with a high probability means the death of our civilization (but not necessarily: black hole could grow extremely slowly in the bowels of the Earth, for example, millions of years, and we have time to leave the Earth, and it depends on the unknown physical conditions.) In doing so, black hole must have some feature that distinguishes it from other holes that arise in our universe, for example, a powerful magnetic field (which exist in collider) or a unique initial mass (also exist in LHC: they will collide ions of gold).

So Smolin’s logic is sound but not proving that our civilization is safe, but in fact proving quiet opposite: that the chances of extinction in near future is high. We are not obliged to participate in the replication of universes suggested by Smolin, if it ever happens, especially if it is tantamount to the death of the parent civilization. If we continue our lives without black holes, it does not change the total number of universes have arisen, as it is infinite.

8th European conference on Computing And Philosophy — ECAP 2010
Technische Universität München
4–6 October 2010

Submission deadline of extended abstracts: 7 May 2010
Submission form

Theme

Historical analysis of a broad range of paradigm shifts in science, biology, history, technology, and in particular in computing technology, suggests an accelerating rate of evolution, however measured. John von Neumann projected that the consequence of this trend may be an “essential singularity in the history of the race beyond which human affairs as we know them could not continue”. This notion of singularity coincides in time and nature with Alan Turing (1950) and Stephen Hawking’s (1998) expectation of machines to exhibit intelligence on a par with to the average human no later than 2050. Irving John Good (1965) and Vernor Vinge (1993) expect the singularity to take the form of an ‘intelligence explosion’, a process in which intelligent machines design ever more intelligent machines. Transhumanists suggest a parallel or alternative, explosive process of improvements in human intelligence. And Alvin Toffler’s Third Wave (1980) forecasts “a collision point in human destiny” the scale of which, in the course of history, is on the par only with the agricultural revolution and the industrial revolution.

We invite submissions describing systematic attempts at understanding the likelihood and nature of these projections. In particular, we welcome papers critically analyzing the following issues from a philosophical, computational, mathematical, scientific and ethical standpoints:

  • Claims and evidence to acceleration
  • Technological predictions (critical analysis of past and future)
  • The nature of an intelligence explosion and its possible outcomes
  • The nature of the Technological Singularity and its outcome
  • Safe and unsafe artificial general intelligence and preventative measures
  • Technological forecasts of computing phenomena and their projected impact
  • Beyond the ‘event horizon’ of the Technological Singularity
  • The prospects of transhuman breakthroughs and likely timeframes

Amnon H. Eden, School of Computer Science & Electronic Engineering, University of Essex, UK and Center For Inquiry, Amherst NY

Experts regard safety report on Big Bang Machine as insufficient and one-dimensional

International critics of the high energy experiments planned to start soon at the particle accelerator LHC at CERN in Geneva have submitted a request to the Ministers of Science of the CERN member states and to the delegates to the CERN Council, the supreme controlling body of CERN.

The paper states that several risk scenarios (that have to be described as global or existential risks) cannot currently be excluded. Under present conditions, the critics have to speak out against an operation of the LHC.

The submission includes assessments from expertises in the fields markedly missing from the physicist-only LSAG safety report — those of risk assessment, law, ethics and statistics. Further weight is added because these experts are all university-level experts – from Griffith University, the University of North Dakota and Oxford University respectively. In particular, it is criticised that CERN’s official safety report lacks independence – all its authors have a prior interest in the LHC running and that the report uses physicist-only authors, when modern risk-assessment guidelines recommend risk experts and ethicists as well.

As a precondition of safety, the request calls for a neutral and multi-disciplinary risk assessment and additional astrophysical experiments – Earth based and in the atmosphere – for a better empirical verification of the alleged comparability of particle collisions under the extreme artificial conditions of the LHC experiment and relatively rare natural high energy particle collisions: “Far from copying nature, the LHC focuses on rare and extreme events in a physical set up which has never occurred before in the history of the planet. Nature does not set up LHC experiments.”

Even under greatly improved circumstances concerning safety as proposed above, big jumps in energy increase, as presently planned by a factor of three compared to present records, without carefully analyzing previous results before each increase of energy, should principally be avoided.

The concise “Request to CERN Council and Member States on LHC Risks” (Pdf with hyperlinks to the described studies) by several critical groups, supported by well known critics of the planned experiments:

http://lhc-concern.info/wp-content/uploads/2010/03/request-t…5;2010.pdf

The answer received by now does not consider these arguments and studies but only repeats again that from the side of the operators everything appears sufficient, agreed by a Nobel Price winner in physics. LHC restart and record collisions by factor 3 are presently scheduled for March 30, 2010.

Official detailed and well understandable paper and communication with many scientific sources by ‘ConCERNed International’ and ‘LHC Kritik’:

http://lhc-concern.info/wp-content/uploads/2010/03/critical-…ed-int.pdf

More info:
http://lhc-concern.info/

A few months ago, my friend Benjamin Jakobus and I created an online “risk intelligence” test at http://www.projectionpoint.com/. It consists of fifty statements about science, history, geography, and so on, and your task is to say how likely you think it is that each of these statements is true. We calculate your risk intelligence quotient (RQ) on the basis of your estimates. So far, over 30,000 people have taken our test, and we’re currently writing up the results for some peer-reviewed journals.

Now we want to take things a step further, and see whether our measure correlates with the ability to make accurate estimates of future events. To this end we’ve created a “prediction game” at http://www.projectionpoint.com/prediction_game.php. The basic idea is the same; we provide you with a bunch of statements, and your task is to say how likely you think it is that each one is true. The difference is that these statements refer not to known facts, but to future events. Unlike the first test, nobody knows whether these statements are true or false yet. For most of them, we won’t know until the end of the year 2010.

For example, how likely do you think it is that this year will be the hottest on record? If you think this is very unlikely you might select the 10% category. If you think it is quite likely, but not very likely, you might put the chances at 60% or 70%. Selecting the 50% category would mean that you had no idea how likely it is.

This is ongoing research, so please feel free to comment, criticise or make suggestions.

Another risk is loss of human rationality, while preserving human life. In a society there are always so many people with limited cognitive abilities, and most of the achievements are made by a small number of talented people. Genetic and social degradation, reducing the level of education, loss of skills of logic can lead to a temporary decrease in intelligence of individual groups of people. But as long as humanity is very large in population, it is not so bad, because there will always be enough intelligent people. Significant drop in population after nonglobal disaster may exacerbate this problem. And the low intelligence of the remaining people will reduce their chances of survival. Of course, one can imagine such an absurd situation that people are so degraded that by the evolutionary path new species arise from us, which is not having a full-fledged intelligence — and that back then this kind of evolving reasonable, developed a new intelligence.
More dangerous is decline of intelligence because of the spread of technological contaminants (or use of a certain weapon). For example, I should mention constantly growing global arsenic contamination, which is used in various technological processes. Sergio Dani wrote about this in his article “Gold, coal and oil.” http://sosarsenic.blogspot.com/2009/11/gold-coal-and-oil-reg…is-of.html, http://www.medical-hypotheses.com/article/S0306-9877 (09) 00666–5/abstract
Disengaged during the extraction of gold mines in the arsenic remains in the biosphere for millennia. Dani binds arsenic with Alzheimer’s disease. In his another paper is demonstrated that increasing concentrations of arsenic leads to an exponential increase in incidence of Alzheimer’s disease. He believes that people are particularly vulnerable to arsenic poisoning, as they have large brains and longevity. If, however, according to Denis, in the course of evolution, people will adapt to high levels of arsenic, it will lead to a decline in the brain and life expectancy, resulting in the intellect of people will be lost.
In addition to arsenic contamination occurs among many other neurotoxic substances — CO, CO2, methane, benzene, dioxin, mercury, lead, etc. Although the level of pollution by each of them separately is below health standards, the sum of the impacts may be larger. One reason for the fall of the Roman Empire was called the total poisoning of its citizens (though not barbarians) of lead from water pipes. Of course, they could not have knowledge about these remote and unforeseen consequences — but we also may not know about the many consequences of our affairs.
In addition to dementia is alcohol and most drugs, many drugs (eg, side effect in the accompanying sheets of mixtures of heartburn called dementia). Also rigid ideological system, or memes.
Number of infections, particularly prion, also leads to dementia.
Despite this, the average IQ of people is growing as life expectancy.