On irreconcilable differences between mathematics and Darwinism?

Surprise! There’s no satisfactory mathematical model for macroevolution, at the present time.

In 2006, Professor Allen Macneill acknowledged that macroevolution is not mathematically modelable in the way that microevolution is. He could have meant that macroevolution is not mathematically modelable at all; alternatively, he may have simply meant that macroevolutionary models are not as detailed as microevolutionary models. If he meant the latter, then I would ask: where’s the mathematics that explains macroevolution? Surprisingly, it turns out that there is currently no adequate mathematical model for Darwinian macroevolution. Professor James Tour’s remark that “The Emperor has no clothes” is spot-on.

Evolutionary biology has certainly been the subject of extensive mathematical theorizing. The overall name for this field is population genetics, or the study of allele frequency distribution and change under the influence of the four main evolutionary processes: natural selection, genetic drift, mutation and gene flow. Population genetics attempts to explain speciation within this framework. However, at the present time, there is no mathematical model – not even a “toy model” – showing that Darwin’s theory of macroevolution can even work, much less work within the time available. Darwinist mathematicians themselves have admitted as much.

In 2011, I had the good fortune to listen to a one-hour talk posted on Youtube, entitled, Life as Evolving Software. The talk was given by Professor Gregory Chaitin, a world-famous mathematician and computer scientist, at PPGC UFRGS (Portal do Programa de Pos-Graduacao em Computacao da Universidade Federal do Rio Grande do Sul.Mestrado), in Brazil, on 2 May 2011. I was profoundly impressed by Professor Chaitin’s talk, because he was very honest and up-front about the mathematical shortcomings of the theory of evolution in its current form. As a mathematician who is committed to Darwinism, Chaitin is trying to create a new mathematical version of Darwin’s theory which proves that evolution can really work. He has recently written a book, Proving Darwin: Making Biology Mathematical (Random House, 2012, ISBN: 978-0-375-42314-7), which elaborates on his ideas.

Here are some excerpts from Chaitin’s talk, part of which I transcribed in my post, At last, a Darwinist mathematician tells the truth about evolution (November 6, 2011):

I’m trying to create a new field, and I’d like to invite you all to leap in, join [me] if you feel like it. I think we have a remarkable opportunity to create a kind of a theoretical mathematical biology…

So let me tell you a little bit about this viewpoint … of biology which I think may enable us to create a new … mathematical version of Darwin’s theory, maybe even prove that evolution works for the skeptics who don’t believe it…

I don’t want evolution to stagnate, because as a pure mathematician, if the system evolves and it stops evolving, that’s like it never evolved at all… I want to prove that evolution can go on forever…

OK, so software is everywhere there, and what I want to do is make a theory about randomly evolving, mutating and evolving software – a little toy model of evolution where I can prove theorems, because I love Darwin’s theory, I have nothing against it, but, you know, it’s just an empirical theory. As a pure mathematician, that’s not good enough…

… John Maynard Smith is saying that we define life as something that evolves according to Darwin’s theory of evolution. Now this may seem that it’s totally circular reasoning, but it’s not. It’s not that kind of reasoning, because the whole point, as a pure mathematician, is to prove that there is something in the world of pure math that satisfies this definition – you know, to invent a mathematical life-form in the Pythagorean world that I can prove actually does evolve according to Darwin’s theory, and to prove that there is something which satisfies this definition of being alive. And that will be at least a proof that in some toy model, Darwin’s theory of evolution works – which I regard as the first step in developing this as a theory, this viewpoint of life as evolving software….

…I want to know what is the simplest thing I need mathematically to show that evolution by natural selection works on it? You see, so this will be the simplest possible life form that I can come up with….

The first thing I … want to see is: how fast will this system evolve? How big will the fitness be? How big will the number be that these organisms name? How quickly will they name the really big numbers? So how can we measure the rate of evolutionary progress, or mathematical creativity of my little mathematicians, these programs? Well, the way to measure the rate of progress, or creativity, in this model, is to define a thing called the Busy Beaver function. One way to define it is the largest fitness of any program of N bits in size. It’s the biggest whole number without a sign that can be calculated if you could name it, with a program of N bits in size….

So what happens if we do that, which is sort of cumulative random evolution, the real thing? Well, here’s the result. You’re going to reach Busy Beaver function N in a time that is – you can estimate it to be between order of N squared and order of N cubed. Actually this is an upper bound. I don’t have a lower bound on this. This is a piece of research which I would like to see somebody do – or myself for that matter – but for now it’s just an upper bound. OK, so what does this mean? This means, I will put it this way. I was very pleased initially with this.

Table:
Exhaustive search reaches fitness BB(N) in time 2^N.
Intelligent Design reaches fitness BB(N) in time N. (That’s the fastest possible regime.)
Random evolution reaches fitness BB(N) in time between N^2 and N^3.

This means that picking the mutations at random is almost as good as picking them the best possible way…

But I told a friend of mine … about this result. He doesn’t like Darwinian evolution, and he told me, “Well, you can look at this the other way if you want. This is actually much too slow to justify Darwinian evolution on planet Earth. And if you think about it, he’s right… If you make an estimate, the human genome is something on the order of a gigabyte of bits. So it’s … let’s say a billion bits – actually 6 x 10^9 bits, I think it is, roughly – … so we’re looking at programs up to about that size [here he points to N^2 on the slide] in bits, and N is about of the order of a billion, 10^9, and the time, he said … that’s a very big number, and you would need this to be linear, for this to have happened on planet Earth, because if you take something of the order of 10^9 and you square it or you cube it, well … forget it. There isn’t enough time in the history of the Earth … Even though it’s fast theoretically, it’s too slow to work. He said, “You really need something more or less linear.” And he has a point…

Professor Chaitin’s point here is that if even a process of intelligently guided evolution takes, say, one billion years (1,000,000,000 years) to reach its goal, then an unguided process of cumulative random evolution (i.e. Darwin’s theory) will take one billion times one billion years to reach the same goal, or 1,000,000,000,000,000,000 years. That’s one quintillion years. The problem here should be obvious: the Earth is less than five billion years old, and even the universe is less than 14 billion years old.

May the Mainstream media R.I.P:Pros and cons.

File under "well said" LIII

To suppress free speech is a double wrong. It violates the rights of the hearer as well as those of the speaker. Frederick Douglass

Engineerless engineering?

Nature’s Amazing Machines — Denver Looks at the Marvels of “Natural Engineering”
Steve Laufmann  

The Denver Museum of Nature and Science is running an excellent special exhibition featuring examples of the amazing engineering observed in biology. The DMNS  website  captures the gist of it:

Nature’s Amazing Machines uses real objects, scientific models, and fun activities to show the marvels of natural engineering.

The exhibit focuses on six functional domains observed in living systems (though there are many, many more they could have chosen): Legs and Springs, Wings and Fins, Jaws and Claws, Structures and Materials, Pumps and Pipes, and Insulators and Radiators.

These amazing machines truly are “marvels.” As I pondered the displays, I was struck by just how nearly perfect these natural machines are — from basic design to operational efficiency to various classes of optimizations.

In previous articles (here and here) I’ve tried to make exactly this point. Life requires exquisitely engineered systems. And now DMNS has stepped up to provide dozens of examples. My thanks to them for their timely (and unwitting) support!

The exhibit incorporates many examples of biomimetics, where human engineers have co-opted the designs of living systems. Like Velcro, which was inspired by the burrs of plants. (For the youngsters, note that this kind of co-option is generally patentable, too! … a good way to generate income that you can use to take care of your parents when they get old.)

As you’d expect, the exhibit includes the requisite references to evolution, but these references are descriptive rather than explanatory. Darwinian evolution is simply an assumption underlying the exhibit, with no attempt at further explanations.

They call this natural engineering. This is an interesting term. Presumably they mean that evolution can engineer amazing machines entirely by accident. So it’s possible to get engineering without an engineer — systems engineering performed entirely by natural forces with no intentionality, plan, or purpose. (We should note, as a counterpoint, that the known forces of nature are mainly working to kill every living thing — to achieve equilibrium, aka death — so there must be some as-yet-undiscovered natural force capable of doing these things.)

How does DMNS know that natural engineering can do such things? Nowhere in the exhibit is this question asked, nor is it answered.

Since DMNS doesn’t provide much by way of explanation, you’ll need to add your own. This is a good opportunity to discuss these issues with your kids and your friends. There’s no shortage of questions to be asked, and this is good practice in learning to ask both the obvious and the not-so-obvious questions. For example:

Examine the complexities in the amazing machines featured in the exhibit, not just at the top level, but the underlying mechanisms that must be there to make them work.

How many parts are required, in all the right places, with all the right properties, connected in all the right ways, to achieve the end functions of these machines?

How specifically must they be arranged and interconnected to achieve their function(s)?

How much information is needed to generate all those parts, from base information, to assembly instructions, to the correct parameters for sizing, fit, and capacities?

How precisely must these be fine-tuned in order to successfully operate?

How can natural engineering create such amazing marvels? What natural forces could possibly do all the work required to generate such systems?

How can such finely tuned systems come to exist when so many parts are needed in order to achieve even minimal functionality?

How many tries does it take to get all that stuff right? How many tries does a living organism get when one of its systems doesn’t function effectively?

Is it possible for such systems to arise gradually? If so, how?

Does anything in this exhibit explain how any of this could happen?

If not, why not? Was it omitted simply because the kids might not understand it?

Are these machines more likely to be caused by accident or by design? Through purposelessness or intention?

Why is it that in any other domain of knowledge, the answer would be obvious (design), whereas in biology this answer is simply not allowed?

Each of us is faced with a decision — whether such purposeful outcomes could possibly be purposeless, or whether they are exactly what they look like — the intentional designs of an awesome (and innovative and powerful and detail-oriented) engineer.

Maybe it’s just me, but it seems hard not to see teleology throughout this exhibit.

If you find yourself in the Denver area this fall, make a point of taking in this exhibit. It focuses mainly on high-level designs that will make sense to everyone, including the kids, using hands-on exhibits to make its points. It’s nicely presented, and a great way to spend a couple of hours. It’s free with general admission to DMNS, which includes many other displays that will provide yet more fodder for explaining the mysterious and wonderful design of our world. Organized youth groups get an especially good deal on admission. No reservations are required. Through January 1, 2018.

From healers to hitmen? II

Michael Egnor: How Assisted Suicide Corrupts Medicine and Medical Doctors
David Klinghoffer | @d_klinghoffer  

“A doctor killing a patient is analogous to a pilot deliberately crashing a plane.” So says neurosurgeon and Evolution News contributor Michael Egnor in a conversation with biologist Ray Bohlin.

It’s a brilliant comparison, in both parts of which a trained professional turns his expertise to the exact opposite purpose it was intended to serve. There are huge manuals stacked upon manuals for physicians on how to avoid killing patients, just as pilots are drilled to expose airplane passengers to minimum danger of falling from the sky.

In a new ID the Future episode, Egnor argues that if judges, legislators, or other advocates support killing patients under certain circumstances, then fine, let them do the killing. But don’t corrupt the medical profession on which we all rely.

As Dr. Egnor acutely notes, the point of involving doctors appears to be a non-medical one – putting a pretty, sanitary seal of approval on a heinous deed, in which MDs are really unneeded. It’s not for the patient’s good. It’s for the rest of us, to ease our conscience in something we know is wrong.  Listen to the podcast here, or download it here.

A castle in the clouds?

Information Storage — In the Cloud(s)
Evolution News | @DiscoveryCSC 

In the second-released Star Wars film, The Empire Strikes Back (1980), a “cloud city” of magnificent structures, filled with active intelligent beings, was portrayed floating in the atmosphere of the giant planet Bespin. If we can re-portray it down a few orders of magnitude, something like that exists right here at planet Earth: whole ecosystems of machinery, active structures, and complex ecosystems in the droplets of clouds.

It’s surprising no one ever checked this before in detail. There were hints that microbes could become airborne or “aerosolized” and take flight in the clouds, but how many are there? What types regularly inhabit cloud droplets? How do they survive, and what do they do? A team of nine from CNRS, the National Center for Scientific Research in France, decided to find out. Their results, published in PLOS ONE, could initiate a whole new science of global “cloud ecology,” the results of which can only be imagined.

Within the atmospheric system, clouds are genuine atmospheric interfaces with the ground: they physically connect high altitudes with the surface by being to a large extent at the origin of wet deposition of aerosols, including microorganisms. Cloud water is a complex mixture of soluble gas and particles dissolved into millions of micron-sized water droplets, and forming very reactive and dynamic systems…. As non-soluble biological particles, some microorganisms can physically impact clouds by acting as embryos for the formation of water droplets and ice crystals, with subsequent impacts on hydrological cycles. Observations of microbiological features in fog and clouds raised the possibility that these also represent habitats for microorganisms, where they would actively take part in the chemical reactivity through metabolic activity and nutrient utilization. So far these active inhabitants of clouds remain largely unknown. 

What they found was truly astonishing, calling to remembrance Leeuwenhoek’s first observation in 1665 of a world of microbes in a drop of water. Now, some 350 years later, science has discovered another unseen world of living creatures. In 2013, the team collected three samples from a mountaintop in France in sterile collectors, quickly flash-freezing the material for later analysis. It’s taken a long time to search through the genomes of microbes, because there were so many of them. DNA and RNA sequencing allowed them to make these initial determinations:

Here, microbial communities in cloud water collected at puy de Dôme Mountain’s meteorological station (1465 m altitude, France) were fixed upon sampling and examined by high-throughput sequencing from DNA and RNA extracts, so as to identify active species among community members. Communities consisted of ~103−104 bacteria and archaea mL-1 and ~102−103 eukaryote cells mL-1. They appeared extremely rich, with more than 28,000 distinct species detected in bacteria and 2,600 in eukaryotes. Proteobacteria and Bacteroidetes largely dominated in bacteria, while eukaryotes were essentially distributed among Fungi, Stramenopiles and Alveolata. Within these complex communities, the active members of cloud microbiota were identified as Alpha- (Sphingomonadales, Rhodospirillales and Rhizobiales), Beta- (Burkholderiales) and Gamma-Proteobacteria (Pseudomonadales). These groups of bacteria usually classified as epiphytic are probably the best candidates for interfering with abiotic chemical processes in clouds, and the most prone to successful aerial dispersion.

This could change your cloud viewing forever. Up there in those drifting puffs of white, tens of thousands of complex organisms live in cloud cities! There are a hundred to a thousand eukaryotic cells per milliliter, and a thousand to ten thousand bacteria and archaea. These numbers vastly exceed cell counts from previous observations. “Clouds are extremely rich and diverse mosaics of multiple sources ecosystems,” the researchers say.

What are the microbes doing up there? Well, as the authors indicated, they modify the weather. They can act as embryos for the formation of water droplets (think rain) and ice crystals (think snow and sleet). In a real sense, they are natural cloud seeders that can influence the life of the rest of the organisms on earth. Now there’s a good science project for someone in the tradition of Michael Denton and Privileged Species: To what extent is weather regulated by the presence or absence of microbes in the clouds?

Another thing they do is migrate. Catching the cloud trains in the sky, microbes can distribute themselves around the globe. Since all multicellular organisms (including humans) carry numerous microbes around with them, this could me a means of ensuring beneficial microbes are available in every habitat. Of course, it cannot rule out the spread of pathogens, too, but those represent a small fraction of microbes as a whole.

A survey of this type cannot hope to find all the functions of the cloud-city ecosystem, and the authors admit there’s a lot to learn:

Their identification certainly helps understanding the atmosphere as a habitat; it will also allow focusing researches for evaluating microbial impact on cloud physical and chemical processes, but their actual functioning, the “what do they do?” question remains to be answered.

Nevertheless, the authors suspect that these ecosystems engage in significant functions. They speak of the “global functioning of the community” and describe their interactions as a system:

If an abundant group was to be lost from the community, i.e. a group that is likely to contribute significantly to the structure and global functioning of the system, there would be a high probability to lose or reduce also the functions associated with it. This ecological theory, that functional stability implies even structure, derives from established ecosystems and it is applied here for apprehending the functioning of cloud’s microbial communities in the frame of clouds as microbial habitats hypothesis; it is possible though that this is not applicable to environments acting mainly as transport areas, where microbial establishment is by essence not possible, like clouds.

Transport areas can be places of function. Business meetings are held on cruise ships. People interact (sometimes) on subway trains. As long as the cloud community in a droplet of water has the resources it needs, it could carry on whatever functions it is capable of, the nature and extent of which remain to be discovered.

A big question for design advocates might concern whether microbes are necessary for habitability. Microbes may not be necessary for weather (Cassini scientists, for instance, inferred that cloudbursts occur on Saturn’s moon Titan), but perhaps microbes regulate the climate of a planet in some way. It’s too early to predict exactly what functions of this newly discovered “system” will present to the health of the planet, but it surely looks promising. Maybe astrobiologists should not rush to declare exoplanets habitable till the “global functioning of the community” of microbes is better understood.

For the time being, though, we can certainly marvel at the fact that what appeared to be largely a domain of lifeless dust and water up there turns out to be perfused with huge amounts of complex specified information: the genetic codes of tens of thousands of organisms. It wouldn’t be surprising to learn that all that information is there for a purpose. We encourage design-friendly scientists to take this information and extend our understanding into the next big question: “What do they do?”