Why multiverse speculation leaves some cold.

A Cold Spot In Space — “Evidence” of a Multiverse?
David Klinghoffer | @d_klinghoffer

Cosmic fine tuning, with physics and chemistry conspiring to permit the existence of creatures such as ourselves, is one of best-recognized pieces of evidence for intelligent design. To this, the hypothesis of a multiverse is materialism’s only response.

According to this line of reasoning, or imagining, our universe reflects only a lucky roll of the dice. A very, very, very lucky roll, which, however, is just to be expected if reality sports not one but a possibly infinite number of universes. Some universe was bound to get lucky, and it was ours.

It’s the single dreamiest, most unsupported idea in all of science, making Darwinian evolution look like a really solid bet by comparison. What’s wanted is real evidence for the multiverse, any at all, and that seems doomed to go on lacking ad infinitum.

Trumped up evidence is nevertheless a regular feature of popular science journalism. The latest: a headline in The Guardian, “Multiverse: have astronomers found evidence of parallel universes?”  Adding the question mark is prudent, since the answer, to be truthful, is No.

Author Stuart Clark got hold of a press release from the Royal Astronomical Society, which he wheels out after an introduction heavy with jokey references to Brexit, Trump, the alt-right, and cat videos.

It sounds bonkers but the latest piece of evidence that could favour a multiverse comes from the UK’s Royal Astronomical Society. They recently published a study on the so-called ‘cold spot’. This is a particularly cool patch of space seen in the radiation produced by the formation of the Universe more than 13 billion years ago.

The cold spot was first glimpsed by NASA’s WMAP satellite in 2004, and then confirmed by ESA’s Planck mission in 2013. It is supremely puzzling. Most astronomers and cosmologists believe that it is highly unlikely to have been produced by the birth of the universe as it is mathematically difficult for the leading theory — which is called inflation — to explain.

This latest study claims to rule out a last-ditch prosaic explanation: that the cold spot is an optical illusion produced by a lack of intervening galaxies.

One of the study’s authors, Professor Tom Shanks of Durham University, told the RAS, “We can’t entirely rule out that the Spot is caused by an unlikely fluctuation explained by the standard [theory of the Big Bang]. But if that isn’t the answer, then there are more exotic explanations. Perhaps the most exciting of these is that the Cold Spot was caused by a collision between our universe and another bubble universe. If further, more detailed, analysis … proves this to be the case then the Cold Spot might be taken as the first evidence for the multiverse.” [Emphasis added.]
Count the instances of speculative language in those last four sentences. “Can’t entirely rule out…If that isn’t the answers…Perhaps…If further, more detailed, analysis…proves…[M]ight be taken as the first evidence…”

It’s “Heady stuff,” Clark exclaims. That’s one way of putting it. The paper in question, though, says just this (“Evidence against a supervoid causing the CMB Cold Spot”):

If not explained by a ΛCDM ISW effect the Cold Spot could have more exotic primordial origins. If it is a non-Gaussian feature, then explanations would then include either the presence in the early universe of topological defects such as textures (Cruz et al. 2007) or inhomogeneous re-heating associated with non-standard inflation (Bueno Sa ́nchez 2014). Another explanation could be that the Cold Spot is the remnant of a collision between our Universe and another ‘bubble’ universe during an early inflationary phase (Chang et al. 2009, Larjo & Levi 2010). It must be borne in mind that even without a supervoid the Cold Spot may still be caused by an unlikely statistical fluctuation in the standard (Gaussian) ΛCDM cosmology.
In this way, based ultimately on a couple of parenthetically referenced papers from 2009 and 2010, a “cold spot” in space answers one of the ultimate questions that have ever puzzled human beings, tipping the scales toward a universe, or multiverse, without design or purpose. As of the present moment, in the quest to explain away ultra-fine tuning, this is the best kind of stuff that materialism has got to offer.

It’s all the most absurd axe-grinding: building your case against a person or idea you don’t like (intelligent design, in this case) by gathering rumors, dreams, and guesses, disregarding common sense and objective evidence, since the conclusion you wish to reach, that you are bound to reach, is already pre-set.


So materialism goes on its merry way, largely unchallenged, with the media as its bullhorn. If scientists advocating the theory of intelligent design ever went before the public with conjectures as weak as this, they would be flayed alive.

New theory or old theory 2.0?

A “Nachos and Ice Cream” Theory of Evolution
David Klinghoffer | @d_klinghoffer

If the old theory of evolution was so great, why do they keep rolling out new ones? You notice, however, that the “new,” “extended,” “fundamentally revised” theories – with the exception of the theory of intelligent design – always turn out to be more or less repackaged versions of the same old, same old. Without recourse to mind, they fail again and again to solve the main problem.

Case in point: Sarah Zhang in The Atlantic heralds, “A Grand New Theory of Life’s Evolution on Earth.”  At long last, is this the “theory of the generative” we’ve been waiting for?

No. The “new theory” from Olivia Judson of Imperial College London is a neat way of classifying sweeping time frames, “energetic epochs,” where life had energy sources made freshly available, thus making increasingly complex life possible.

The modern world gives us such ready access to nachos and ice cream that it’s easy to forget: Humans bodies require a ridiculous and — for most of Earth’s history — improbable amount of energy to stay alive.

Consider a human dropped into primordial soup 3.8 billion years ago, when life first began. They would have nothing to eat. Earth then had no plants, no animals, no oxygen even. Good luck scrounging up 1600 calories a day drinking pond- or sea water. So how did we get sources of concentrated energy (i.e. food) growing on trees and lumbering through grass? How did we end up with a planet that can support billions of energy-hungry, big-brained, warm-blooded, upright-walking humans?

In“The Energy Expansions of Evolution,”   an extraordinary new essay in Nature Ecology and Evolution, Olivia Judson sets out a theory of successive energy revolutions that purports to explain how our planet came to have such a diversity of environments that support such a rich array of life, from the cyanobacteria to daisies to humans.

Judson divides the history of the life on Earth into five energetic epochs, a novel schema that you will not find in geology or biology textbooks. In order, the energetic epochs are: geochemical energy, sunlight, oxygen, flesh, and fire. Each epoch represents the unlocking of a new source of energy, coinciding with new organisms able to exploit that source and alter their planet. The previous sources of energy stay around, so environments and life on Earth become ever more diverse. Judson calls it a “step-wise construction of a life-planet system.” [Emphasis added.]
The key word in that passage may be “coincide.” Energy – delivered in the form of “nachos and ice cream,” or whatever the case might be — is necessary but not sufficient in explaining how complex life arises. Merely “coinciding” with great leaps forward in biological complexity doesn’t cut it. The really grand mystery remains the origin of biological information. See our short video, “The Information Enigma.”  Positing “energetic epochs” does nothing to resolve that enigma.

She mentions oxygen. In the context of explaining the Cambrian explosion, a classic fallacy is the “oxygen theory,”  holding that new body plans arose thanks newly available oxygen. As we’ve noted many times before, oxygen has no ability to compose coded information, generating the software on which life runs.

The point about fire is interesting, and should ring a bell. Zhang summarizes:

Then one particular type of animal — those of the genus Homo — figure out fire. Fire lets us cook, which may have allowed us to get more nutrition out of the same food. It lets us forge labor-saving metal tools. It lets us create fertilizer through the Haber-Bosch process to grow food on industrial scales. It lets us burn fossil fuels for energy.

True enough. But this brief treatment falls well short of Michael Denton’s research and writing on the same subject. Fire does more than harness fuel to provide energy. It reveals how nature has been specially fitted for a creature like man, and vice versa. See, “Fire-Maker: How Humans Were Designed to Harness Fire & Transform Our Planet.”

When plants attack?

Ladybug v. Darwin.

Ladybug, Living Origami, Lends a Hand with Umbrella and Other Designs
David Klinghoffer | @d_klinghoffer

Delicate and delightful, ladybug beetles are the insect everyone loves. Having one unexpectedly land on your hand is a reminder of how gentle and beautiful nature can be.

Their ability to alternate nimbly between walking and flying is also a marvel of design. Japanese scientists have been working on clarifying the secret of how they fold and unfold their wings, an effortless gesture of living origami. They published their findings in PNAS.

From USA Today:

Japanese scientists were curious to learn how ladybugs folded their wings inside their shells, so they surgically removed several ladybugs’ outer shells (technically called elytra) and replaced them with glued-on, artificial clear silicone shells to peer at the wings’ underlying folding mechanism.

Why bother with such seemingly frivolous research? It turns out that how the bugs naturally fold their wings can provide design hints for a wide range of practical uses for humans. This includes satellite antennas, microscopic medical instruments, and even everyday items like umbrellas and fans.

“The ladybugs’ technique for achieving complex folding is quite fascinating and novel, particularly for researchers in the fields of robotics, mechanics, aerospace and mechanical engineering,” said lead author Kazuya Saito of the University of Tokyo. [Emphasis added.]

That is astonishingly wide array of “design hints” from the humble bug, which are also called ladybirds. See the design in action:The Telegraph echoes:

Ladybird wings could help change design of umbrellas for first time in 1,000 years
The New York Times:

Ladybugs Pack Wings and Engineering Secrets in Tidy Origami Packages

[…]

To the naked eye, this elegant transformation is a mystery. But scientists in Japan created a window into the process in a study published Monday in Proceedings of the National Academy of Sciences. Just how the ladybug manages to cram these rigid structures into tiny spaces is a valuable lesson for engineers designing deployable structures like umbrellas and satellites.

A ladybug’s hind wings are sturdy enough to keep it in the air for up to two hours and enable it to reach speeds up to 37 miles an hour and altitudes as high as three vertically stacked Empire State Buildings. Yet they fold away with ease. These seemingly contradictory attributes perplexed Kazuya Saito, an aerospace engineer at the University of Tokyo and the lead author of the study.

Working on creating deployable structures like large sails and solar power systems for spacecrafts, he turned to the ladybug for design inspiration.
Notice how, in discussing them, it’s as if we are forced to use the language of design. Regarding ladybugs and their “engineering secrets,” as the NY Times candidly puts it, molecular biologist Douglas Axe tweets:“Like a DeLorean, only cooler!” Here is a DeLorean:In his book Undeniable: How Biology Confirms Our Intuition That Life Is Designed, Dr. Axe uses the illustration of an origami crane. With good reason behind this universal intuition, our minds rebel at the idea that any origami creation could arise through a combination of chance and law, without purpose or design. Yet Darwinian theory demands that we believe a real crane arose that way, or a real ladybug.

The fall of Rome.:The reboot

How to Protect Medical Conscience
Wesley J. Smith

Over at First Things, I have a piece up about the ongoing and accelerating campaign — most recently furthered by  Ezekiel Emanuel  — to drive pro-life and orthodox religious believers out of medicine by forcing their participation or complicity in acts in the medical sphere with which they have strong moral or religious objections.

There are currently some conscience protections in the law, but as the piece notes, they are under assault here and are already collapsing in other countries. From“Pro-Lifers Get Out of Medicine”:

The government of Ontario, Canada is on the verge of requiring doctors either to euthanize or to refer all legally qualified patients. In Victoria, Australia, all physicians must either perform an abortion when asked or find an abortionist for the patient.

One doctor has been disciplined under the law for refusing to refer for a sex-selective abortion. In Washington, a small pharmacy chain owned by a Christian family failed in its attempt to be excused from a regulation requiring all legal prescriptions to be dispensed, with a specific provision precluding conscience exemptions. The chain now faces a requirement to fill prescriptions for the morning-after pill, against the owners’ religious beliefs.

In Vermont, a regulation obligates all doctors to discuss assisted suicide with their terminally ill patients as an end-of-life option, even if they are morally opposed. Litigation to stay this forced speech has, so far, been unavailing.

The ACLU recently commenced a campaign of litigation against Catholic hospitals that adhere to the Church’s moral teaching.

Here, I would like to share some ideas about how to shore up existing protections to best protect medical professionals from being forced into committing what they consider sinful or immoral acts. I suggest that the following general principles apply in crafting such ­protections:

Conscience protections should be legally binding.

The rights of conscience should apply to medical facilities such as hospitals and nursing homes as well as to individuals.

Except in the very rare and compelling circumstance in which a patient’s life is at stake, no medical professional should be compelled to perform or participate in procedures or treatments that take human life. 

The rights of conscience should apply most strongly in elective procedures, that is, medical treatments not required to extend the life of, or prevent serious harm to, the patient.

It should be the procedure that is objectionable, not the patient. In this way, for example, physicians could not refuse to treat a lung-cancer patient because the patient smoked or to maintain the life of a patient in a vegetative state because the physician believed that people with profound impairments do not have a life worth living.

No medical professional should ever be forced to participate in a medical procedure intended primarily to facilitate the patient’s lifestyle preferences or desires (in contrast to maintaining life or treating a disease or injury).

To avoid conflicts and respect patient autonomy, patients should be advised, whenever feasible, in advance of a professional’s or facility’s conscientious objection to performing or participating in legal medical procedures or treatments.

The rights of conscience should be limited to bona fide medical facilities such as hospitals, skilled nursing centers, and hospices and to licensed medical professionals such as physicians, nurses, and pharmacists.

I am interested in other ideas on this subject, which I predict will become a firestorm issue in coming years.

And still yet more on Venezuela's meltdown.

Chinese propaganda american style?

Manifest destiny past its shelf life?:Pros and cons.

On our latter day frankensteins and the end of science.

Swarm" Science: Why the Myth of Artificial Intelligence Threatens Scientific Discovery

Erik J. Larson 

 

 

In the last year, two major well-funded efforts have launched in Europe and in the U.S. aimed at understanding the human brain using powerful and novel computational methods: advanced supercomputing platforms, analyzing peta- and even exabyte datasets, using machine learning methods like convolutional neural networks (CNNs), or "Deep Learning."

At the Swiss Federal Institute of Technology in Lausanne (EPFL), for instance, the Human Brain Project is now underway, a ten-year effort funded by the European Commission to construct a complete computer simulation of the human brain. In the U.S., the Obama Administration has provided an initial $100 million in funding for the newly launched Brain Research Through Advanced Neurotechnologies (BRAIN) Initiative, with funding projected to reach $3 billion in the next ten years. Both projects are billed as major leaps forward in our quest to gain a deeper understanding of the brain -- one of the last frontiers of scientific discovery.

Predictably, given today's intellectual climate, both projects are premised on major confusions and fictions about the role of science and the powers of technology.

The myth of evolving Artificial Intelligence, for one, lies at the center of these confusions. While the U.S. BRAIN Initiative is committed more to the development of measurement technologies aimed at mapping the so-called human connectome -- the wiring diagram of the brain viewed as an intricate network of neurons and neuron circuits -- the Human Brain Project more explicitly seeks to engineer an actual, working simulation of a human brain.

The AI myth drives the HBP vision explicitly, then, even as ideas about Artificial Intelligence and the powers of data-driven methods (aka "Big Data") undergird both projects. The issues raised today in neuroscience are large, significant, and profoundly troubling for science. In what follows, I'll discuss Artificial Intelligence and its role in science today, focusing on how it plays out so unfortunately in neuroscience, and in particular in the high-visibility Human Brain Project in Switzerland.

AI and Science

AI is the idea that computers are becoming intelligent in the same sense as humans, and eventually to even a greater degree. The idea is typically cast by AI enthusiasts and technologists as forward-thinking and visionary, but in fact it has profoundly negative affects on certain very central and important features of our culture and intellectual climate. Its eventual effects are to distract us from using our own minds.

The connection here is obvious, once you see it. If we believe that the burden of human thinking (and here I mean, particularly, explaining the world around us) will be lessened because machines are rapidly gaining intelligence, the consequence to science if this view is fictitious can only be to diminish and ultimately to imperil it.

At the very least, we should expect scientific discovery not to accelerate, but to remain in a confused and stagnant state with this set of ideas. These ideas dominate today.

Look at the history of science. Scientists have grand visions and believe they can explain the world by contact of the rational mind with nature. One thinks of Einstein, but many others as well: Copernicus, Galileo, Newton, Maxwell, Hamilton, Heisenberg, even Watson and Crick.

Copernicus, for instance, became convinced that the entire Ptolemaic model of the solar system stemmed from false theory. His heliocentric model is a case study in the triumph of the human mind not to analyze data but effectively to ignore it -- seeking a more fundamental explanation of observation in a rational vision that is not data-driven but prior to and more fundamental than what we collect and view (the "data"). Were computers around back then, one feels that Copernicus would have ignored their results too, so long as they were directed at analyzing geocentric models. Scientific insight here is key, yesterday and today.

Yet the current worldview is committed, incessantly and obsessively, to reducing scientific insight to "swarms" of scientists working on problems, by each making little contributions to a framework that is already in place. The Human Brain Project here is paradigmatic: the "swarm" language is directly from a key HBP contributor Sean Hill (in the recent compilation The Future of the Brain edited by Gary Marcus, whom I like).

The swarm metaphor evokes thoughts of insects buzzing around, fulfilling pre-ordained roles. So if we're convinced that in a Human-Technology System the "technology" is actually becoming humanly intelligent (the AI myth), the set of social and cultural beliefs begin to change to accommodate a technology-centered worldview. This, however, provides very little impetus for discovery.

To the extent that individual minds aren't central to the technology-driven model of science, then "progress" based on "swarm science" further reinforces the belief that computers are increasingly responsible for advances. It's a self-fulfilling vision; the only problem is that fundamental insights, not being the focus anyway, are also the casualties of this view. If we're living in a geocentric universe with respect to, say, neuroscience still, the model of "swarm" science and data-driven analysis from AI algorithms isn't going to correct us. That's up to us: in the history of science, today, and in our future.

An example. Neuroscientists are collecting massive datasets from neural imaging technologies (not itself a bad thing), believing that machine-learning algorithms will find interesting patterns in the data. When the problem is well defined, this makes sense.

But reading the literature, it's clear that the more starry-eyed among the neuroscientists (like Human Brain Project director Henry Markram) also think that such an approach will obviate the need for individual theory in favor of a model where explanation "emerges" from a deluge of data.

This is not a good idea. For one thing, science doesn't work that way. The "swarm-and-emerge" model of science would seem ridiculous were it not for the belief that such massive quantities of data run on such powerful computing resources ("massive" and "powerful" is part of the emotional component of this worldview) could somehow replace traditional means of discovery, where scientists propose hypotheses and design specific experiments to generate particular datasets to test those hypotheses.

Now, computation is supposed to replace all that human-centered scientific exploration -- Markram himself has said publicly that the thousands of individual experiments are too much for humans to understand. It may be true that the volume of research is daunting, but the antidote can hardly be to force thousands of labs to input data into a set of APIs that presuppose a certain, particular theory of the brain! (This is essentially what the Human Brain Project does.) We don't have the necessary insights, yet, in the first place.

Even more pernicious, the belief that technology is "evolving" and getting closer and closer to human intelligence gives less and less an impetus to people to fight for traditional scientific practice, centered on discovery. If human thought is not the focus anymore, why empower all those individual thinkers? Let them "swarm," instead, around a problem that has been pre-defined.

This too is an example of how the AI myth also encourages a kind of non-egalitarian view of things, where a few people are actually telling everyone else what to do, even as the model is supposed to be communitarian in spirit. This gets us a little too far off topic presently, but is a fascinating case study in how false narratives are self-serving in subtle ways.

Back to science. In fact the single best worldview for scientific discovery is simple: human minds explain data with theory. Now, but only after we have this belief, we can and should insert: and our technology can help us. Computation is a tool -- a very powerful one, but as it isn't becoming intelligent in the sense of providing theory for us, we can't then jettison our model of science, and begin downplaying or disregarding the theoretical insights that scientists (with minds) provide.

This is a terrible idea. It's just terrible. It's no wonder that any major scientific successes in the last decade have been largely engineering-based, like the Human Genome Project. No one has the patience, or even the faith, to fund smaller-scale and more discovery-based efforts.

The idea, once again, is that the computational resources will somehow replace traditional scientific practice, or "revolutionize it" -- but as I've been at pains to argue, computation isn't "smart" in the way people are, and so the entire AI Myth is not positive, or even neutral, but positively threatening to real progress.

The End of Theory? Maybe So

Hence when Chris Andersen wrote in 2007 that Big Data and super computing (and machine learning or i.e., induction) meant the "End of Theory," he echoed the popular Silicon Valley worldview that machines are evolving a human -- and eventually a superhuman -- intelligence, and he simultaneously imperiled scientific discovery. Why? Because (a) machines aren't gaining abductive inference powers, and so aren't getting smart in the relevant manner to underwrite "end of theory" arguments, and (b) ignoring the necessity of scientists to use their minds to understand and explain "data" is essentially gutting the central driving force of scientific change.

To put this yet again on more practical footing, over five hundred neuroscientists petitioned the EU last year because a huge portion of funding for fundamental neuroscience research (over a billion euro) went to the Human Brain Project, which is an engineering effort that presupposes that fundamental pieces of theory about the brain are in place. The only way a reasonable person could believe that, is if he were convinced that the Big Data/AI model would yield those theoretical fruits somehow along the way. When pressed, however, the silence as to how exactly that will happen is deafening.

The answer Markram and others want to provide -- if only sci-fi arguments worked on EU officials or practicing neuroscientists -- is that the computers will keep getting "smarter." And so that myth is really at the root of a lot of current confusion. Make no mistake, the dream of AI is one thing, but the belief that AI is around the corner and inevitable is just a fiction, and potentially a harmful one at that.

To chance and necessity be the glory?

Moths Defy the Possible

Evolution News & Views 

How do you make choices in a data-poor environment? Imagine being in a dark room in total silence. Every few seconds, a tiny flash of light appears. You might keep your eyes open as long as possible to avoid missing any of them. You might watch the flashes over time to see if there's a pattern. If you see a pattern, you might deduce it will lead to further information.

The ability to navigate this way in a dim world is called a summation strategy. "This slowing visual response is consistent with temporal summation, a visual strategy whereby the visual integration time (or 'shutter time') is lengthened to increase visual reliability in dim light," Eric Warrant explains in Science. He's discussing how hawkmoths perform "Visual tracking in the dead of night," and he's clearly impressed by how amazingly well insects "defy the possible" as they move through the world:

Nocturnal insects live in a dim world. They have brains smaller than a grain of rice, and eyes that are even smaller. Yet, they have remarkable visual abilities, many of which seem to defy what is physically possible. On page 1245 of this issue, Sponberget al. reveal how one species, the hawkmoth Manduca sexta, isable to accurately track wind-tossed flowers in near darknessand remain stationary while hovering and feeding. [Emphasis added.]

The hawkmoth has some peers on the Olympic award platform:

Examples of remarkable visual abilities include the nocturnal central American sweat bee Megalopta genalis, which can use learned visual landmarks to navigate from its nest -- aninconspicuous hollowed-out twig hanging in the tangled undergrowth -- through a dark and complex rainforest to a distant source of nocturnal flowers, and then return. The nocturnalAustralian bull ant Myrmecia pyriformis manages similar navigational feats on foot. Nocturnal South African dung beetles can use the dim celestial pattern of polarized light around the moon or the bright band of light in the Milky Way as a visual compass to trace out a beeline when rolling dung balls. Some nocturnal insects, like the elephant hawkmoth Deilephila elpenor, even have trichromatic color vision.

These insects pack a lot of computing power in brains the size of a grain of rice. How do they do it? Part of the answer lies in the fine-tuning between object and sensor:

It turns out that even though the hawkmoths must compromise tracking accuracy to meet the demands of visual motiondetection in dim light, the tracking error remains small exactly over the range of frequencies with which wind-tossed flowers move in the wild. The results reveal a remarkable match between the sensorimotor performance of an animal and the dynamics of the sensory stimulus that it most needs to detect.

A tiny brain imposes real-world constraints on processing speed. The hawkmoth, so equipped, faces limits on sensorimotor performance: how sensitive its eyes are in dim light, how quickly it can perceive motion in the flower, and how fast it can move its muscles to stay in sync. The moth inserts its proboscis into the flower, and if a breeze moves the flower about, the moth has to be able to keep up with it to get its food. To meet the challenge, its brain software includes the "remarkable" ability to perform data summation and path integration fast enough to move with the flower while it feeds.

In their experiments, Sponberg et al. observed hawkmoths in a specially designed chamber. They were able to control light levels and move artificial flowers containing a sugar solution at different speeds. "During experiments, this flower was attached to a motorized arm that moved the flower from side to side in a complex trajectory," Warrant says.

The component movement frequencies of this trajectory varied over two orders of magnitude and encompassed the narrower range of frequencies typical of wind-tossed flowers. A hovering moth fed from the flower by extending its proboscis into the reservoir, rapidly flying from side to side to maintain feeding bystabilizing the moving flower in the center of its visual field.

The experiment allowed the researchers to cross the line from possible to impossible, showing at what point the moth could not keep up. Dimmer light requires longer integration time, while faster motion requires quicker muscle response. Still, these little flyers "tracked the flower remarkably well" by using the temporal summation strategy.

Hummingbirds feed on moving flowers, too, but usually in broad daylight. To find this ability to track a moving food source in a tinier creature possessing a much smaller brain is truly amazing -- especially considering that it has less light to see by.

This strategy has recently been demonstrated in bumblebeesflying in dim light and has been predicted for nocturnalhawkmoths. Although temporal summation sacrifices the perception of faster objects, it strengthens the perception of slower ones, like the slower movement frequencies (below ~2 Hz) of the robotic flower.

... and that just happens to be the maximum speed of the natural flowers in the moth's environment. How did this perfect match arise? Why, natural selection, of course. Here comes the narrative gloss:

By carefully analyzing the movements of several species of flowers tossed by natural winds -- including those favored by hawkmoths -- Sponberg et al. discovered that their movements were confined to frequencies below ~2 Hz. Thus, despite visual limitations in dim light, the flight dynamics and visual summation strategies of hovering hawkmoths have evolved to perfectly match the movement characteristics of flowers, their only food source.

The implications of the study go far beyond this particular species. It shows how in small animals like hawkmoths, withlimited nervous system capacities and stretched energy budgets, the forces of natural selection have matched sensory and motorprocessing to the most pressing ecological tasks that animals must perform in order to survive. This is done not by maximizing performance in every possible aspect of behavior, but bystripping away everything but the absolutely necessary andhoning what remains to perform tasks as accurately and efficiently as possible.

Do the experimenters agree with this narrative? They actually have little to say about evolution. Near the end of the paper, they speculate a little:

The frequencies with which a moth can maneuver could provide a selective pressure on the biomechanics of flowers to avoidproducing floral movements faster than those that the moth can track in low light. The converse interaction -- flower motions selecting on the moth -- could also be important, suggesting acoevolutionary relationship between pollinator and plant thatextends beyond color, odor, and spatial features to include motion dynamics.

The evolutionary narrative, though, is unsatisfying. It is only conceptual, not empirical (nobody saw the flower and moth co-evolve). Additionally, flowers could just as well thrive with other pollinators that operate during the daytime. Or, the moth could simply adjust its biological clock to feed in better light, too. The theory, "It is, therefore it evolved" could explain anything.

Warrant also mischaracterizes natural selection as a force. Natural selection is more like a bumper than a force; it's the hub in the pinball game, not the flipper that an intelligent agent uses. It's far easier for a moth to drop the ball in the hole (i.e., go extinct) than to decide what capacities it must stretch to match the hubs in its game. The hub, certainly, cares nothing about whether the player wins or not. It's not going to tell the moth, "Pssst ... strip away everything that's not absolutely necessary, and hone what remains, and you might win!" Personifying natural selection in this way does not foster scientific understanding.

Worst of all, the evolutionary explanation presupposes the existence of highly complex traits that are available to be stripped or honed: flight, a brain, muscles -- the works. You can't hone what isn't there.

What we observe is a tightly adapted relationship between flower and moth that reaches to the limits of the possible. Any stripping or honing comes not from the environment, but from internal information encoded in the organism. Intelligent causes know how to code for robustness, so that a program can work in a variety of circumstances. Seeing this kind of software packed into a computer the size of a grain of rice makes the design inference even more compelling.

Illustra Media's documentary Metamorphosis showed in vibrant color the remarkable continent-spanning migration of the Monarch butterfly. Their new documentary, Living Waters (coming out this summer), shows dramatic examples of long-distance migration and targeting in the oceans and rivers of the earth, where the lack of visual cues makes finding the target even more demanding. The film makes powerful arguments against the abilities of natural selection, and for the explanatory fruitfulness of intelligent design

Why so little evolving across the history of life?

A Good Question from Michael Denton About the Fixity of Animal Body Plans
David Klinghoffer September 9, 2011 6:00 AM


Biochemist Michael Denton (Evolution: A Theory in Crisis, Nature's Destiny: How the Laws of Biology Reveal Purpose in the Universe) was in our offices this week and he casually posed a question that I, for one, had never considered. Hundreds of millions of years ago, all these animal body plans became fixed. They stayed as they were and still are so today.

Before that -- I'm putting this my way, so if I get anything wrong blame me -- of course they had been, under Darwinian assumptions, morphing step-by-step, with painful gradualness. Then they just stopped and froze in their tracks.

The class Insecta with its distinctive segmentation, for example, goes back more than 400 million years to the Silurian period. It gives the impression of a creative personality at work in a lab. He hits on a design he likes and sticks with it. It does not keep morphing.

This is exactly the way I am about recipes. I experiment with dinner plans, discover something I like, and then repeat it endlessly with minor variations from there onward.

Why does the designer or the cook like it that way? Well, he just does. There's no reason that can be expressed in traditional Darwinian adaptive terms. There is no adaptive advantage in this fixity of body plans. Why not keep experimenting and morphing as an unguided, purposeless process would be expected to do? But nature doesn't work that way. It finds a good plan and holds on to it fast, for dear life. This suggests purpose, intelligence, thought, design. Or is there something I'm missing?

No such thing as bad publicity?

How Curiosity Overcomes the Yuck Factor: A Positive Take on Negative Reviews
Douglas Axe | @DougAxe

I’ve been arguing that intelligent design explains life better than Darwin’s theory for long enough to be familiar with reactions that amount to little more than disgust — the yuck response. Usually I take that response as a sign that I need to move on to more receptive listeners, but I was recently reminded that the yuck response doesn’t always end the discussion. A colleague of mine — a former Darwinist who now sees life as designed — told me how he came to change his view several years ago. It was curiosity that bumped him out of the Darwinian rut, by compelling him to give a few of the best books on intelligent design a serious read.Kriti Sharma’s yuck reaction to my book, Undeniable: How Biology Confirms our Intuition That Life Is Designed, in her recent  review suggests she might be stuck in that same rut. She read the book, but not very seriously.

Sharma, a PhD biology student at the University of North Carolina at Chapel Hill, describes giving lectures to other students on the evolutionary divergence between clams and snails. According to the evolutionary story, something quite different from modern clams or snails had descendants that became modern clams and snails in all their great variety. Anyone with an appreciation of all the distinct biological marvels represented by that variety should be struck by the magnitude of this claim. Add just a dash of curiosity to that awe, and you start to wonder how a blind evolutionary process could actually pull it off. How can something utterly devoid of insight possibly appear so insightful?

Sharma’s vagueness on this point is the familiar sign that curiosity hasn’t yet kicked in. She says evolution gets lots of trials with lots of feedback, each small step depending on the prior step. She seems satisfied with that. The staggering variety of stunning living things that populate our planet is adequately explained by those rather unimpressive factors — time and natural selection — she thinks. In her case, my attempts to expose the inadequacy of those factors seem to have fallen on deaf ears.

Much of my book is devoted to developing an argument around everyday experience and common sense, a combination I refer to as common science. It seems to me that Darwin’s thinking is quite vulnerable to refutation by common science. After all, selection doesn’t really make anything. It merely chooses among things that have already been made. That’s what the word means. The only kind of selection that gives you clams or snails is the kind you do while ordering dinner at a French restaurant.

Sharma dismisses such thoughts as childish “pre-theoretical” thinking.

One of my book’s themes is that we adults shy away from common-science deductions like that for the wrong reasons. Fearing that smart people couldn’t possibly have overlooked such obvious facts for so long, we tend to assume they must know something the rest of us don’t. But in making that assumption, we overlook something equally obvious, which is that smart people take great pride in their smarts. Wanting to be revered for their intellects, they’re very reluctant to say anything that might cause their status to take a hit. Ironically, the end result of all this fretting about appearances is that the “smart” explanation of biological origins has the same amount of substance to it as the emperor’s new clothes — worn with just as much pride.

Another theme of my book is that because common science gives us the right conclusion about our origin, deeper digging consistently affirms that conclusion. No matter how deeply we dig, if we keep curiosity at the forefront we find our intuitive rejection of the inventive power of natural selection to be absolutely correct.

Half-a-minute’s worth of digging might convince you of this.

Consider, for example, Graham Bell, the James McGill Professor of Biology at McGill University and a recently elected Fellow of the Royal Society. He’s an accomplished evolutionary biologist, author of a book titled Selection: The Mechanism of Evolution, where he argues that “Living complexity cannot be explained except through selection, and does not require any other category of explanation whatsoever.” According to Bell, then, selection most certainly is evolution’s engine of invention.

Now consider Andreas Wagner of the Department of Evolutionary Biology and Environmental Studies at the University of Zurich, who is also an accomplished evolutionary biologist. His book,  Arrival of the Fittest: Solving Evolution’s Greatest Puzzle, confirms common science by declaring that “natural selection is not a creative force. It does not innovate, but merely selects what is already there.”

Notice that Wagner’s assessment, contrary to Bell’s, leaves a rather large and conspicuous hole right in the middle of evolutionary theory. “To appreciate the magnitude of the problem,” says Wagner, “consider that every one of the differences between humans and the first life forms on earth was once an innovation: an adaptive solution to some unique challenge faced by a living being.” According to Wagner, then, selection most certainly is not evolution’s engine of invention.

Don’t miss the significance of this. Two highly regarded experts at the very center of today’s evolutionary thinking have completely opposite opinions about how evolution is supposed to work! What this really means, of course, is that the community of evolutionary biologists has no clue how evolution would work! Again, add just a pinch of curiosity to that startling realization and you start to wonder whether evolution really can work.

That’s what drove me to test Darwin’s idea in the lab for the last twenty years. As I explain in Undeniable, his theory has failed this testing consistently and spectacularly.

Now, I’m very willing to hear from anyone who thinks otherwise, as long as they show genuine curiosity of the kind that rises above academic peer pressure by refusing to settle for stock explanations that are obviously inadequate. Kriti Sharma seems content to leave her worldview undisturbed for the moment, which is understandable.

That was my colleague before curiosity got the better of him.

Why enzymes are undeniably designed.

Don’t Be Intimidated by Keith Fox on Intelligent Design
Douglas Axe | @DougAxe


Darwin believed that once simple bacteria appeared on Earth (however that happened), natural selection took over from there — creating every living thing from that humble beginning. And this continues to be the official view of the science establishment to this day.

Being skeptical of that view, my colleagues and I have spent twenty-some years putting Darwin’s idea to one test after another in the lab. As described in a stack of peer-reviewed technical papers, it has failed every one of these tests. I’m convinced, however, that you don’t need a PhD to see why it had to fail. That’s why I based my recent book — Undeniable: Undeniable: How Biology Confirms Our Intuition That Life Is Designed — on commonsense reasoning instead of technical argument.

Biochemist Keith Fox at the University of Southampton didn’t like the book, so he wrote a short critique claiming I got it all wrong. The things I’ve studied for all these years are called enzymes — sophisticated catalysts that handle all the chemical processes inside cells. Based on my work and the work of many others, I claim that these remarkable little factories can’t have come about by any ordinary physical process. I say they’re molecular masterpieces — works of genius. Fox disagrees, and while he doesn’t seem to have done any work in the field, his critique of Undeniable includes his own rough-and-ready theory of enzyme origins.

As I recently recounted, Fox thinks working enzymes started out much smaller than they are today, growing to their present size through the refining work of natural selection. Years ago, I explained in technical detail why this can’t be true — why enzymes must be full-sized and exquisitely shaped to do their jobs. But, again, a major theme of my book is that you don’t have to take my word for this. You can see for yourself that life is designed all the way down to the molecular level.

Here’s one visual example to make the point.




That green thing is a large molecule called tRNA, and the little yellow things are amino acids. For life to work, these amino acids, which come in 20 different kinds, must be connected in special sequences to make chain-like molecules called proteins (enzymes being one class of proteins). If these long molecules were nothing but floppy chains, they would be useless. Instead, their special sequences cause them to fold up into distinct and highly useful shapes, each as well suited to its specific function as any human-made machine.

The crucial instructions for the sequences that cause these machine-like shapes to form are preserved in the form of genes, used in every living cell and carefully passed to successive generations. A set of tRNA molecules like that green one is crucial for reading these genes to make proteins. The tRNA molecules work like clever adapters: their underside recognizes (by perfect fit) a specific short piece of genetic sequence — a genetic word, if you will — while their top part holds the amino acid that, in the language of genes, is referred to by that word.

In order for this to work, something has to make sure each different green thing gets the right amino acid attached at the top — meaning the one corresponding to the genetic “word” recognized down below. As if that weren’t challenging enough, those little yellow amino acids are attached to the green things only with difficulty. They must be forced into position and then locked in place with a chemical bond.

Life’s ingenious solution to these compound challenges is a set of enzymes like the one shown here in blue.



Each of these enzymes recognizes its own type of tRNA molecule, checking the bottom part to make sure it will read the right genetic word and simultaneously recognizing the amino acid corresponding to this genetic word. In power-tool fashion, these enzymes “burn” ATP to forcibly attach the correct amino acid into position on the tRNA (in the above picture you can see the red ATP in place, ready for the correct amino acid to enter the opening and be forced into place).

Sophisticated power tools don’t appear out of thin air, though. So, wanting to think otherwise, Keith Fox imagined much simpler things that could come out of thin air, proposing that these can do crudely what today’s enzymes do so elegantly. Specifically, the little blue blob below is what Fox imagined.



Now, imagination can be useful in science, but only by connecting in a compelling way to reality. As anyone can plainly see, that isn’t the case here. In fact, the absence of evidence to back Fox’s claim up, while significant, isn’t nearly as significant as the fact that we can all see why his claim simply can’t work. Little blobs like that (nothing but two amino acids joined together) can’t possibly verify the bottom of the tRNA…much less do so while recognizing the corresponding amino acid…much less hold the needed ATP in position to power the attachment of that amino acid. And while the comical inadequacy of the size of that little blob is what jumps out at us, this isn’t just about size. Rather, it’s about the necessity of matching shape to function.

Other examples could be given by the thousands (literally) — each showing how woefully inadequate Fox’s little blobs are. But you get the point.

The only thing Keith Fox’s theory of enzyme origins has going for it is that it came from Keith Fox — a fully credentialed and highly competent biochemist at a major research university. In other words, his claim borrows any status it has from his professional standing. But when a scientist, however accomplished, stubbornly wants to see things one way, this borrowed status just isn’t enough.

Surprised? On the one hand, you shouldn’t be…but on the other, you’re in good company if you are. Many people are so persuaded by the stereotypical view of scientists that they can’t imagine how these supposedly uber-rational thinkers could allow their desires to interfere with their reasoning.


Rest assured that they can. Scientist are, after all, just as human as everyone else.