Illness as big data problem? The bicameral mind

Supercomputer; Wikimedia

We attended a very interesting discussion of Alzheimer's disease the other day, by an historian of science.  The speaker gave his overview of the history of the disease, from 1906 when it was first described by Dr Alois Alzheimer to today, 107 years and billions of research dollars later.  After much discussion of what we've learned and what we still don't know, it seemed we pretty much all agreed that dementia is a tough problem, predicting who will get it is a tough problem, and while some progress has been made in understanding the early onset form of Alzheimer's, we've got a long way to go in the development of treatment for the disease, whether early or late onset.

And then a physicist in the room spoke up.  He didn't understand why people were so pessimistic about our ability to eventually understand the disease.  Or any disease.  He himself is certain that with the incredible computing power we've got now we'll be able to understand, and predict, them all. A few others in the room signed on to that, none of them physicists, but similarly optimistic.

A piece has just been published at Wired online (18 March 2013) that says much the same.  Richard Barker: "Illness just became another big data problem."  Barker describes the case of an infant born with a rare form of type 1 diabetes for whom the proper treatment is begun once the child is genotyped and his particular mutation identified. 

So diabetes isn't just diabetes: it's a cluster of diseases with different causes and different remedies. This story is just a glimpse of a quiet medical revolution: from defining diseases by the symptoms they cause or the part of the body affected, to the underlying molecular mechanism.

Further, if this child had been sequenced at birth, as our children, or grandchildren, or great-grandchildren will be, his illness would have been identified before he was even ill, and his treatment would have been started immediately.  This day is coming.

An anthropological question:  fad, fact, or cultural bias?
This all sounds very hopeful.  But history shows how at any given era there is a working model of how to do things, and basically everyone except mavericks follow suit.  We want to be in on things, to be doing what seems right, to have support from our fellows, and the comfort all of this brings.  We often stick to this even if there is no real evidence that it is working or evidence that it may not be the best approach.  The long-lasting nature of Galenic (four-humours) medicine is one example.  Armies routinely train for the last war, and pay a price for it.  Religions, though supposedly based on ultimate divinely given truths, form sects and alter their doctrine.

At the same time, it may be--especially in science--that the current way, though imperfect, is the result of centuries of improvement and is the best we can do at any given time.  Certainly we'll not just quit because we know our methods have imperfections!  So, it is fair to ask: is illness now just a data crunching problem?

Well, we can pretty much eliminate infectious diseases right off the bat.  While there may be identifiable genetic susceptibility that explain a small minority of resistance to some infectious diseases, this is by far overwhelmed by other factors that predispose people to infection, like poverty and bad luck.  That makes a lot of illness around the world not reducible to a data crunching, at the individual level.  There's certainly a lot of population-based data crunching that can model risk and explain it in populations, but no amount of sequencing of infants at birth will identify those who will be at highest risk come the next epidemic. 

Then there are complex diseases, like heart disease, or type 2 diabetes or asthma or schizophrenia or autism or hypertension or stroke or most cancers.  Sequencing can't now, and although it's not fashionable to say so, many believe will never be able to predict accurately who's at risk of most of these diseases, for reasons that we write about here all the time.  They're complex, they're polygenic, everyone has a different and unique genome, and a different pathway to disease, environmental factors are causal, and inherently unpredictable.  And so forth.

So now we've pretty much eliminated the big causes of death around the world from the illness as big data problem model.  What's left?

Mendelian diseases, like the form of diabetes Barker described, or the thousands of other primarily very rare and usually pediatric diseases that really are genetic, many of which are now, and will eventually be, identifiable and usually (but not always) predictable with genetic data.  But, many such diseases and disorders are themselves very complex -- cystic fibrosis is a well-studied and well-characterized example, with over 1000 different implicated alleles, all in the same gene, identified to date.

Studies of unexplained genetic disorders, that is where there is familial risk and some cases have an identified gene, have about a 25% success rate for identifying a causal mutation.  Granted, by now it's probably the toughest, rarest disorders that are left to explain -- and/or those without effective enough advocacy groups to have lobbied for funding; but some of these will be explained, while others will not, because there can be numerous pathways to the same phenotype, and what's causal for one individual won't explain it in another.  This is something we know very well already.

Late spring wildflowers; Wikimedia

That complexity isn't always reducible is an idea approached from a completely different angle in a beautiful piece in Aeon Magazine on March 19, by Olivia Laing.  Now a writer, she describes her one time life as an herbalist, trained in the ways of western medicine to understand the molecular properties of the herbs she prescribed for sick patients, and her growing discomfort with the idea that it was all reducible to molecules.

She tells the story of how it had been believed that the Neanderthal buried their dead with flowers, or may even have used flowers medicinally, based on pollen finds in caves in which skeletons were found.  It was a beautiful idea, she writes, except that it was probably wrong.  The pollen was more likely blown in by the wind, or carried in on a rodent's fur. 

I confess to finding this story pleasing, not disappointing. It exposes the depths of our fantasies about people and plants, showing how pattern-driven we are, and how addicted to stories. At the same time, it reveals the baffling complexity of the natural world, its resistance to understanding. No matter what meanings we ascribe to them, plants maintain their mystery. I might not handle them daily anymore, but I like to think of them growing in the fields and waysides of the world: rue and cockspur, nettle and rosemary, rising from the soil year after year to spell out a code we may not ever completely crack.

The problem of the bicameral mind
It has often been said that humans have a 'bicameral' mind: one half is devoted to particular things, with analytic functions, the other to more overall or holistic impressions.  Whether this is literally true or accurate, in science we can trace two similar main kinds of thinking about Nature back through history.

One is the qualitative, enumerative, reductionist particularistic view of causation: causes are individual forces or 'things' and the job of science is to identify them and how they work. To do that, we have to isolate them, and to do that we must reduce our observations to the most rudimentary level--such as molecules, where the causes actually operate. We do this through experimental designs and so on.  We do it because complexity obscures individual causes.  This is the gene mapping approach, the number-crunching idea that we'll just overwhelm Nature with our computers and force it to yield its individual causes.  Mendelian genetics has been an exemplar of this worldview since the turn of the 20th century. It assumes great regularity in Nature, and that the scale of our data and so on are all that prevents us from identifying causes.

The other view is quantitative, and basically holds that Nature works through complex interactions at higher levels than rudimentary forces.  A building cannot be understood by enumerating its bricks, beams, and wires, even if those things are needed and in that rudimentary sense 'cause' or explain the building. But interactions of very complex forms are instead viewed by quantitative minds as the organizing principles, or higher-level 'causes', that we need to understand.  Quantitative genetics as separate from Mendelian genetics has always been a major component of biology, and was basically Darwin's view of evolution.  It treats genetic and evolutionary causation in aggregate, without attempting to enumerate its components.  This view today, though currently held by the vast minority because it's under siege by the reductionist majority, would be that which argues that computer crunching is not what we need: what we need is more innovative thinking about how complex causation works and/or is to be understood and manipulated.

This qualitative/quantitative dichotomization is an oversimplified characterization, and we don't mean to suggest that the world is just a contest between opposites that will ultimate resolve (that's a view of philosophers such as Hagel, and thinkers like Marx).  Still, it reflects widespread differences in world views--of communication between our two brain hemispheres, one might say.

There are attractions and attributes to these different points of view and their intermediaries.  How they will resolve, or if they will, remains to be seen.

Slot machines and thoughts: neural determinism?

Coin flips are probabilistic for all practical purposes (unless you learn how to "predetermine" the outcome, here).  By 'probabilistic' we mean that the outcome of any given flip can only be stated as a probability, such as 50% chance of Heads: we can't say that a Heads will or won't occur.  This is for all practical purposes, since if we knew the exact values of all the variables involved, standard physics can predict the outcome with, with complete certainty.  Machines have been built to show this, as we've posted about before (e.g., here).

Slot machines are (purportedly) random dial-spinners that stop in ultimately random ways (that are adjusted for particular pre-set overall payoff levels, but not individual spins).  In this sense, the slot machine is nearly a random device, but even the computer-based random number generator of modern slot machines is not 100% random and, in a sense, every spin could be predicted at least in principle.

So, as far as anybody can tell in practice, each flip or each jerk of the one-armed bandit, is random.  We still can say much about the results:  We can't predict a given coin flip or slot-pull, but we can predict the overall net result of many pulls, to within some limits based on statistical probability theory--though never perfectly.

On the other hand, a casino is a collection of numerous devices (roulette wheels, poker tables, slot machines, and so on).  Each is of the same probabilistic kind.  Nobody would claim that the take of a casino was not related to these devices, not even those who believe that each one is inherently probabilistic.  To think that would be to argue that something other than physical factors made up a casino.

But the take of a casino on any given day cannot be predicted from an enumeration of its devices! The daily take is the result of how much use was made of each device, of the decision-making behavior of the players, of the particular players that were there that day, of how much they were willing to lose, and so on.  The daily take is an 'emergent' property of the assembled items.  Interestingly, nonetheless, the pattern of daily takes can be predicted at least within some limits.  This is the mysterious connection between full predictability and emergence, and it is a central fact of the life sciences.

Genes exist and they do things.  On average, we can assess what a gene does.  Clearly genes underlie what a person is and does.  But each gene's net impact on some trait depends not just on itself, but on the rest of the genes in the same person's genome, and countless other factors.  A particular individual's particular action is simply not predictable with precision from its genome (or, for that matter, its genome and measured environmental factors).  There are simply too many factors and we can't assess their individual action in individual cases, except within what are usually very broad limits.

Brain games
A common current application of the issues here is to be found in neurosciences.  There is a firm if not fervid belief that if we enumerate everything about genes and brains we'll be able to show that, yes, you're just a chemical automaton.  Forget about the delusion of free will!

Location of the amygdala; Wikipedia

A story last week in the NY Times largely asserts that behavior is going to be predictable from the 'amygdala', a section of the brain.  There is also a story suggesting that psychopaths can be identified early in life.  And there are frequent papers about let's call it 'econogenomics', claiming they will save the day by showing how our genomes determine our economic behavior.

Day after day, in the media and in the science journals themselves, the promise is made of ultimate (often, of imminent) predictability even of complex emergent phenomena, from examination of their parts.  If we just have enough sequencers, fMRI machines, and other kinds of technology, everything will work out.  Not to worry!

So the Human Connectome Project, exploits the 'omics idea that if we mindlessly enumerate every single little thing we can understand every single big thing, is funded and off and enumerating.....every connection between every neuron in the brain (starting, we think, with 'the' mouse, whatever that means).  Mindlessly is the right word, because the investigators of such things often proudly proclaim that they are not testing any hypothesis about Nature: this is pure Baconian empiricism, something we've discussed in earlier posts:  collect all the facts and the theory will emerge automatically.  There seems to be a feeling of imminent triumph that, like the priests of old, we The Scientist will be able to see inside your very soul to see what you are really like, no matter how much you may delude yourself that you are a free agent.

Clear-cut cases of prediction in complex systems from specific identified elements do exist, due to individually very strong factors.  They are usually rare, but they addict us to the idea that all cases--all behaviors or even all thoughts, will be predictable by enumerating all causal factors and their effects.  But this is, at best, not practicable.  Is it an ultimate illusion?

So why the persistent belief to the contrary?
Could it be that really, truly, and ultimately when so many countless probabilistic factors interact to generate a net result, our ability to predict them other than in a few special cases is inherently limited?  Could it be that our claims to do otherwise are, in fact, no more than a current version of Delphic mumbo-jumbo that has always existed in society?  Whether or not that is true, science, like religion, is not likely to agree to that.

Why is there such reluctance to simply accept limits to our knowledge, or perhaps even to our ability to know things by applying current methods?  Is it just arrogance, careerism, profit-chasing?  Is it ignorance of the landscape?

One thing is that of course we cannot apply scientific methods that we haven't yet discovered.  There are programs and even organizations, like the Santa Fe Institute of which Ken is an external faculty member, that are dedicated to working out an understanding of complexity.  We think it's fair to say that they haven't solved the problem!

At present, a nay-sayer may be viewed as someone who is anti-science, or perhaps even being mystical.  After all, either things are material or they aren't!  If they are material, should we not be able to understand them?  If they are numerous or individually small, doesn't the history of science show that instrumentation and technology need to be brought to bear on the problem?

The answer to these questions is certainly 'yes'.  We're not mystics. But physical problems need not be amenable to the kinds of solutions we currently have, any more than astrology solved problems when observing the stars and planets was the technology of the time.   Our society certainly believes in technology and even more so, perhaps, in the idea that technology is for making a profit.  That's the often explicitly stated that the point of science is its application, that we do this for our careers and labs, or for patients, or for society at large.

But it is not defeatism to ask whether the current approaches, based on 400 year-old Enlightenment-derived methods and concepts, are obsolete for the kinds of questions we are now asking (no matter how powerful they were for lesser questions that were successfully answered).  It could potentially help to withdraw resources from business as usual as a way of trying to force more creative thinking--but there's no guarantee that, if, or when, it would work to stimulate the next Darwin or Einstein.

It is similarly not out of line to ask, as regular readers know we ask regularly, whether much of what is being supported in science is on wrong trails, even if good for maintaining funding and other sorts of momentum, by diverting funds from things more likely soluble with traditional approaches, like diseases that really are genetic and for which genetic treatments would be fantastic.

And it is not out of line to ask whether when there are so many really serious human ills in the world, that have nothing to do with genes (or, for that matter, with science), that resources are often wrongly being used to maintain an academic welfare system, the way passing the plate maintains religious establishments on the promise of Things to Come.

As we have often also said often,  triggered by yet more grandiose claims in the news or journals, complexity due to multiple interacting but individually small factors is the challenge of the day.  It is even more challenging to the extent that really, or for all practical purposes, these factors are probabilistic results of large numbers of interacting, individually minor, factors.

If that's the case, we are back in the 1800s, when it was discovered that every year a predictable number of people will commit suicide, and by predictable arrays of methods, but yet this can rarely be predicted for individuals.  That kind of problem was perhaps first recognized more than a century ago, but is still with us.

And it's a no-brainer to recognize that.

Luck of the draw: Evolving flipbooks mimic non-selective processes (a classroom activity)

First the lesson plan, then a look at the peer-review process that provided feedback.

A common ancestor (center) and its descendants.

Introduction and scope

Even if evolution is accepted and natural selection is understood, learners of all ages may mistakenly explain all variation with this single mechanism. That there are myriad resources for, and examples of, natural selection and because it is so powerful, it is not surprising that the concept is dominant even though selection is not the only means by which evolution occurs. Here I suggest that there should be better coverage of non-selective processes at the introductory level of learning evolution. Towards that goal, I offer an engaging activity involving the drawing of flipbooks, which not only marries art and science but symbolically demonstrates evolutionary mechanisms other than selection.

Leads into—biology, genetics, evolution, the art of animating with flipbooks.

Concepts—Mutation, genetic drift, natural selection, common ancestry, diverging lineages, speciation, inheritance, species identification, developmental constraints, complexity, evolutionary progress.

Target age group—All students who are being introduced to the fundamentals of evolution can perform this simple activity and can learn from it. As long as they can trace a line, they can participate. In schools, evolutionary concepts are formally introduced as early as the sixth grade, but basic concepts like change over time, deep time, and common ancestry may be introduced even earlier. Often students are not formally or rigorously introduced to evolution until they reach college or university. Furthermore, many of the more advanced concepts that can be addressed with this activity are only appropriate for secondary and post-secondary courses. It is up to teachers to decide how to integrate this activity into their evolution lessons. I developed this activity, and used it with success, in my introductory biological anthropology course at the University of Rhode Island.

The importance of teaching beyond selection at the introductory level

Natural selection does not explain all of evolution

             Since Darwin’s time we’ve learned that natural selection is just one mechanism of evolution that works in concert with others such as mutation, gene flow, and genetic drift. Mutation, the result of chance, creates the necessary variation for natural selection and drift to take place. Each human inherits an estimated average of 150 mutated nucleotides per person (Ken Weiss, Pennsylvania State University, personal communication[A]). Like mutation, drift is also random, but drift occurs over time as random events accumulate. Because both are due to differential reproduction, the result of drift can look remarkably like that of selection and change away from the ancestral state can occur quickly if the population size is small (1). A classic example of drift occurs in a small culturally isolated population of the Old Order Amish in eastern Pennsylvania; hardly anyone would hypothesize that the relatively high frequency of polydactyly was due to natural selection. For many traits that seem to have no adaptive value, drift is a strong hypothesis. Often drift is considered alongside relaxed selection (2). That is, a trait becomes prevalent through drift in the absence of selective pressures that would otherwise prevent the drift from occurring. The deterioration of human eyesight may be explained this way and so may geographic variation in earwax (3). Many diagnostic characteristics of the Neanderthal face may be explained by drift (4) and so might the fixed loss of tails in our hominoid ancestry.[B]

           

A strict selection perspective creates potential for societal harm

Learning about evolution solely through natural selection is not only inaccurate but may also have negative social consequences.  Wearing adaptation-colored glasses fosters notions that evolution is progressive, that past states were inferior to present ones, and that there is some striving in nature towards perfection (5, 6). From this perspective it is all too easy to assign differential value, worth, or beauty to variation within and between species under the backing assumption that “Mother Nature” has “favored” one trait over another. Judgments like this can lead to human exceptionalism and anti-environmentalism (justifying human superiority over other organisms) or tribal exceptionalism and racism (justifying superiority of some nose shapes or skin colors over others).[C] Presenting a more complete picture of evolution to those in the early phases of learning about it may lower the risk that these dangerous ideological paths will be followed (7).

Flipbooks for teaching evolution

            Seeds, jelly beans, and the like are common stand-ins for alleles or gametes in classroom exercises meant to recreate evolving populations. These exercises demonstrate how new gene pools result from mutation followed by selection or the lack thereof (i.e. drift).  However, these activities are not appropriate for all ages because of the algebra they require for calculating allele frequencies; even at the university level, students can struggle with the math. Furthermore, these engaging hands-on activities do not allow students to witness more than a few generations of evolutionary change. Alternate illustrations of the effects of mutation and genetic drift on evolution are needed. Recently, Gillings (8) provided a pedagogically useful metaphor of these biological processes with language evolution.

Here I offer another sort of instructional device inspired by two films that were recently posted by artist Clement Valla on the Internet. The films show how line drawings, when traced 500 times, can evolve dramatically. And although it is so simple, this is a powerful demonstration of evolution without natural selection.

***

Teacher Resources

Films by Clement Valla (2010)—Inspiration for this flipbook activity

• “A sequence of lines traced by 500 individuals” Also posted here.
• “A sequence of circles traced by 500 individuals” Also posted here.

On-line resources for the art of flipbook animation

• Wired’s How-To “Make a flip book animation”
• National Gallery of Art, Kids. “On the Move”
• “Escape” (flipbook animation)
• “Flip Mania Part 1: Sports” (flipbook animation)
• “Simpsons Fight” (flipbook animation)

On-line resources for teaching and learning about the role of chance in evolution

General evolution:

• NOVA’s “Evolution”
• Berkeley’s “Understanding Evolution for Teachers”

Genetic drift:

• University of Arizona’s “The Biology Project”
• University of Connecticut’s genetic drift simulator

Mutation:

• University of Utah’s “Learn.Genetics”
• NIH’s “Genetics Home Reference”

Misconceptions about evolution:

• AAAS Science Assessment. Topics: Evolution and natural selection
• New Scientist’s “Evolution: 24 myths and misconceptions”

***

Valla’s films are basically digital renderings of classic flipbooks used by cartoon animators and by following the steps in the activity outlined below, teachers can easily recreate the experience of the films with students in the classroom. In addition, they can use this exercise to teach an array of evolutionary principles and concepts.

If learners can trace lines they can perform this activity. As a collaborative endeavor, this activity works with a minimum of two participants and, theoretically, has no maximum group size. With 50 tracings per book, it takes about 50 minutes to complete.[D] At the end, students will have created flipbook animations that “evolved” merely because each of their tracings, no matter how diligently drawn, was slightly different from the previous one.

Materials

·       One pencil or pen for each participant

·       Two blank flipbooks for each participant. There are several ways to fashion flipbooks. They can be small blank notebooks with at least 50 plain white sheets that are slightly transparent for tracing purposes. A much cheaper method is to fasten sheets of copier paper together with a binder clip. The paper should be cut down with a paper cutter to pages with roughly 3 inches (or 8 cm) on each side and not too much larger than that because large books beg for large drawings that slow down the activity. To get seamless animation while flipping through the flipbook, the flipping edges of the pages need to be lined-up, so tap the stack of pages on a table top to settle them all together on one edge before clipping them together and beginning the drawings.  Once the flipbook drawings are underway, the clip cannot be moved or removed.

Procedures

1.     Set the stage. Prior to performing this activity, provide students with background information  on flipbook animation and on concepts of common ancestry, the Tree of Life, evolution, and mechanisms of evolution (natural selection, mutation, and genetic drift). 

***

Questions to gauge knowledge and spark interest before the activity

Teachers will need to choose the questions that are appropriate for their students’ learning level and for the particular evolutionary lessons they want to address.         

Change through time and common descent—What is evolution? What is the evidence for it? How does it occur? What is the concept of common ancestry that is used to build the Tree of Life?

Evolutionary mechanisms—What is natural selection? What are other ways that evolution occurs besides natural selection? What is genetic drift and how is it different from and similar to natural selection? What is a mutation? What causes mutations? How frequent are mutations? What keeps mutations from happening more frequently than they do? Are mutations always bad? How could something that starts as a mutation in an individual end up in more and more individuals in a population over generations and through time?

The nature of evolution—Is evolution progressive? Is there a goal? Does it always result in improvement over earlier forms?

***

2.     Draw the templates.

a.      Have students put their names on the front covers of their books.

b.     Have them open one of their flipbooks to the last page and draw something. Keep it a simple line drawing so that it does not take longer than 10 seconds to trace. The drawing can be an unknown shape, like a doodle or scribble (known here as “unrecognizable”; Figures 1-4). Or the drawing can be a symbol like a number or letter, an amoeba or Mona Lisa (known here as “recognizable”; Figures 5-8). It is important that both types of templates are represented because the “recognizable” templates may experience stabilizing natural selection. That is, tracers of familiar shapes may have stronger expectations about how their tracing should appear. If they have such expectations, they may trace with fewer mistakes and/or correct the mistakes that previous tracers have made. But the “unrecognizable” templates may experience less, if any, of this conservative influence. Do not explain the rationale to the students yet because it will be part of the discussion after the completion of the exercise. The bottom line is that teachers make sure that both unrecognizable and recognizable templates are created. They may also want to encourage some students to draw creatures (see explanation in “concluding remarks”).  

c.      Optional modification: I had several students use identical templates—rather than having each student draw a unique one—so that they could witness several different lineages, not just two, evolving from a common ancestor (Figures 1-8). The only downside to this modification is that students are not given the opportunity to create their own templates. Also, teachers may wish to copy and cut out the templates from Figures 1-8 and glue them in the flipbooks before handing them out to students. This would allow students to compare their results (i.e. descendants) with the ones published here.

d.     Have the students carefully trace their template into their second book. Each of them will now have two flipbooks with identical templates. They may rotate the tracing so that the second template is oriented differently in the book.

3.     Introduce the activity. Briefly describe Step 6—that they’re about to pass the books around and each of them will trace the tracing of the person who went before them until the books are filled up. The result will be flipbooks that contain animated movies of the tracings beginning with the original templates.  

4.     Make predictions. Ask the students: What will your book’s animation be like? What will the last picture in your book look like? Will your two books’ animations be identical? What does the template symbolize in evolutionary terms? What do your two flipbook animations symbolize?

5.     Establish the rules

·       Trace as best as you can, but in a brief amount of time.

·       Joking is fine, but do not give anyone grief for “messing up” a flipbook with their mistakes. Everyone’s tracings are imperfect copies. 

·       You may only look at the page that you are tracing. You may not flip back and look at any previous drawings in the book that build up as this activity goes along.

·       You must pass the book to the next tracer in a way that keeps it open to your drawing (i.e. the drawing that the next person will trace).

6.     Trace in an assembly line to build the flipbooks.

1. Each student will turn one page down over the template and trace it and then pass the book to the right.
2. Each tracing should take a few seconds and, ideally, everyone should take roughly the same amount of time.
3. Trace, pass, trace, pass, and repeat to fill all pages of the book.

7.     Observe, discuss, and explain the evolving animations. When filled-up, make sure each flipbook makes its way back to its owner. Each student will have two flipbook animations of the evolution of their template drawing, starting with the template and ending with the last tracing. Now they are ready to explain the evolution that occurs in their books.

Results

Figures 1-4. “Unrecognizable” template (i.e. ancestor; center circle) and the resulting drawings (i.e. descendents) after 50 tracings carried out in different flipbooks (i.e. divergent evolutionary paths).

Figures 5-8. “Recognizable” template (i.e. ancestor; center circle) and the resulting drawings (i.e. descendents) after 50 tracings carried out in different flipbooks (i.e. divergent evolutionary paths).

***

Questions to gauge understanding and to spark further study after the activity

Teachers will need to choose the questions that are appropriate for their students’ learning level and for the particular evolutionary lessons they want to address. 

Results—What happened to the templates? Were your predictions correct? Were there differences in the outcomes of the identical templates? Describe the differences in size and shape (morphology) between your template and your final drawings: What were the trends, if any, through time? Did any new traits appear? Did any old traits disappear?  Look around at the other flipbooks and distinguish “recognizable” from “unrecognizable” templates (as described in Step 2b):  Were there any differences in the outcomes of their evolution?

Evolutionary mechanisms—How can you explain what happened to your drawings? What caused the evolution in your flipbooks? Explain the evolutionary history of the last drawing in each of your flipbooks.

Speciation and species concepts—Are the final drawings in your two flipbooks different species from your template (i.e. their common ancestor)? Are the two final drawings different species from each other? Can you identify the moment (i.e. the particular tracing) when a new species originated?

Luck, chance, randomness, and non-random constraints—What does luck, chance and randomness have to do with evolution? Is natural selection random? Look at the differences and similarities between any two neighboring pages in a flipbook. Are there many major differences between the two tracings? What does this suggest about phylogenetic and developmental constraints in evolution? Is evolution predictable? Are there any hypothetical evolutionary changes to an organism, like Homo sapiens, that are implausible or highly unlikely?

Scales of variation and modes of inheritance—Are your animations symbolic of the evolution of a strand of DNA, a protein, a cell, a single-celled organism, a tissue, an organ, a multicellular organism, or a population? Are your animations depicting the results of asexual or sexual reproduction through time? What are the differences for each, in terms of how variation gets into the next generation?

Explaining human evolution—List hypotheses for the evolution of variation in human nose shape. Point out which hypothesis most closely mimics the process in your flip book animation. Describe, in as much detail as possible, how the different hypotheses could be tested. Include materials and methods. Then discuss any problems that you can anticipate with confidently supporting one hypothesis over another and suggest some possible workarounds or solutions to those problems.

Complexity, progress, and perfection—Would you describe your final drawings as more complex than your template? What about the reverse? Would you say that your animations depict progress? Progress and perfection are valued in our society, so what’s the trouble with perceiving human evolution to be progressive, or to be striving towards perfection or some ideal form?

***

  

Concluding remarks

            This activity illustrates the impact of luck on evolution—when chance is a factor (mutation and drift) and when it is not (natural selection). Students may also use the flipbooks to learn the principles of common ancestry, divergent evolution, and speciation. More advanced students can explore concepts of inheritance, species identification, developmental constraints, complexity, and evolutionary progress.

Over the course of three trials of this activity, I found that there were observable degrees of evolutionary change in all flipbooks, whether they had unrecognizable or recognizable templates (Figs. 1-8). Even if there seemed to be conservative influences on the recognizable templates as predicted in Step 2b, evolution still occurred simply because human tracers are not perfect. The various degrees of distance between template and results (e.g. Figure 5) nicely demonstrate the various speeds of evolutionary change, with some organisms retaining more ancestral traits than others.

There was another sort of issue with the recognizable templates, specifically the ones that represented creatures. Some of my students who had these templates (Figures 7 & 8) were the only students to ignore chance and instead describe their animations with natural selection. For example one student explained that, “What started as a lizard evolved to a blob maybe because it could survive better without legs.” Another wrote, “Natural selection may have occurred in my animation because of environmental changes that caused the need for certain features on the body.”  These answers reveal common misunderstandings of natural selection (which are due in no small part to our pedagogical language: 9), but they also illuminate a deeper struggle with accepting and identifying randomness in evolutionary scenarios. Because this activity is designed to help overcome these issues, I recommend that teachers encourage some students to draw templates of creatures so that these fundamental problems, if present, are more likely to surface.

Although natural selection is not responsible for the evolution in the flipbook animations, teachers should not forget to discuss how natural selection is involved in this activity: it is the non-random process behind our cells’ ability to copy DNA without making many mistakes and it is mimicked by tracing in the flipbooks. However, like tracing drawings, DNA replication is imperfect and the chance variations that arise are a fundamental component of evolution.

With these flipbooks students can see for themselves, albeit in a symbolic way, how random mutations can contribute to complexity by flipping through the “recognizable” flipbooks backwards (from the last tracing to the template). When viewed in reverse, the animations evolve from (perceived) simplicity to (perceived) complexity. And when students are reminded that all the mistakes in the tracings (i.e. the mutations) are still the same and that it’s just the sequence of these mistakes that differs in the reverse view, a dialogue is opened up about the roles of chance and deep time in the evolution of complex life (10).  Students can reflect on whether chance mutations and drift could have produced a flipbook that started with a blob and ended with a symbol. After gaining this insight, they are better poised to question the relevance of probability-based arguments against evolution and the origin of life (11). 

The roles of luck, chance and randomness too often take a back seat to natural selection and this activity is meant to help introductory students achieve a more complete view of evolution from the start. Although I cannot guarantee that every student will be evolutionarily enlightened or artistically inspired by this activity, it will provide teachers and students with tools for overcoming some of the mistaken assumptions about evolution that we so often inherit and propagate.

Acknowledgments

            Thanks to B. Bailey, N. Bailey, A. Collado, J. Conrad (and the lizard), W. Harcourt-Smith, G. Felda, C. Mesyef, D. Nelson, B. Shearer as well as the students in my two sections of ‘APG 201: Human Origins’ at The University of Rhode Island during the Fall 2011 semester for providing valuable input during the development process.  Thanks also to Anne Buchanan, Norman Johnson, Kevin Stacey, and Ken Weiss for their most helpful comments on the manuscript. Clement Valla’s art was the spark and I’m grateful for it.

References

1.      Helgason A,  et al. (2009) Sequences from first settlers reveal rapid evolution in Icelandic mtDNA pool. PLoS Genet 5(1): e1000343. doi:10.1371/journal.pgen.1000343

2.      Lahti DC, Johnson NA, Ajie BC, Otto SP, Hendry AP, Blumstein DT, Coss RC, Donohue K, Foster SA (2009) Relaxed selection in the wild. Trends in Ecology and Evolution 24: 487-496.

3.      Yoshiura K, et al (2006) A SNP in the ABCC11 gene is the determinant of human earwax type. Nature Genetics 38: 324-330.

4.      Weaver TD, Roseman CC, Stringer CB (2007) Were neandertal and modern human cranial differences produced by natural selection or genetic drift? J Hum Evol 53: 135-145.

5.      Gould SJ, Lewontin RC (1979) The spandrels of San Marco and the Panglossian paradigm: a critique of the adaptationist programme. Proc R Soc Lond B 205: 581-598.

6.      Weiss KM, Dunsworth HM (2011) Dr. Pangloss’s nose: In evolution, cause, correlation, and effect are not always identical. Evolutionary Anthropology 20:3-8. 

7.      Johnson NA, Lahti DC, Blumstein DT (in press) Combating the assumption of evolutionary progress: Lessons from the decay and loss of traits. Evolution: Education and Outreach.

8.      Gillings MR (in press) How evolution generates complexity without design: Language as an instructional metaphor. Evolution.

9.      Nehm RH, Rector M, Ha M (2010) "Force Talk" in evolutionary explanation: Metaphors and misconceptions.  Evo Edu Outreach 3:605–613.

10.   Nilsson DE, Pelger S (1994) A pessimistic estimate of the time required for an eye to evolve. Proc R Soc Lond B 256: 53-58.

11.   Morris HM (2003) The mathematical impossibility of evolution. Back to Genesis, 179. El Cajon, CA: Institute for Creation Research. Available via the Internet. Accessed 2011 December 22.

---

[A] Estimated roughly with the equation 2.5 x 10^-8 mutations per generation, per 6 billion nucleotides based on published rates (e.g. Pelak et al., 2010.PLoS Genetics 6(9): e1001111).

[B] I cannot find a reference containing this hypothesis, but I cannot find one containing a selection-based hypothesis for ape tail loss either.

[C] For just one example of a scholarly treatment of these issues see ‘Race’ is a Four-Letter Word by C. Loring Brace (Oxford University Press, 2005).

[D] This estimate is based on three trials with ten, 25 and 30 students, respectively. However, making 50 tracings takes just as long with 25 students as it does with 125 students. This time estimate of 50 minutes only includes time for instruction and drawing. It does not include the time spent priming the students on evolutionary concepts and discussing the results. For my students, those discussions continued for the rest of the semester because the flipbooks were a useful touchstone for new concepts down the line. 

Behind the article 

It’s tough to get a paper accepted for publication. This one was rejected from an education series in a scientific journal. I chose to submit there because it's open access (and was prepared to pay if the fee wasn't waived) and the series is billed as a forum for classroom activities, not education research. 

I consider the three reviews (below) to be pretty supportive, especially #2, and think that with just a few revisions I could ameliorate the first reviewers' concerns about citing more literature.

But the academic editor’s concerns about assessment, as outlined in the cover letter (also below), which also echo #3's concerns about Intelligent Design (ID) would require much more work to address. Those issues, along with the extremely low-tech methods (just my hunch), is why I think that they rejected my paper rather than ask me to revise it.

Clearly a lot of my article's shortcomings stem from the fact that I am a college professor and not a trained primary-secondary school teacher, who must meet particular standards of evaluation and assessment. I might also have a poor understanding of the minds of students who are learning biology in high school (or younger). My attempt to transcend those things and address common difficulties that we all share with understanding and teaching evolution... at all levels of learning... well, it failed to be seen as that... perhaps because I failed at doing that! 

I chose not to submit elsewhere because I don’t know of many other open access journals that publish lesson plans and, from my personal perspective, I don't see the point of publishing a lesson plan if it’s not open access. I bet you’re thinking that tenure’s the point. Well, if my choices are (a) submit somewhere else and risk burying it in a journal that few will see, or (b) turn my focus to other publications for my tenure portfolio and make this activity available, now, to anyone with Internet access who visits us here on the Mermaid’s Tale...

...then, I’ll take b.

I'm posting the letter and reviewer comments (with my comments in italic red) for a few reasons: (1) if you decide to try this activity, the comments will help you anticipate any issues or problems you may have; (2) you can see the kind of reviews that a paper like this gets and the sorts of things that people require of evolution lesson plans; (3) it's in the spirit of open access which is what this manuscript has been about from the start of my writing it. 

Article submitted on December 28, 2011, Reviews back on February 10, 2012 

So swiftly returned!

Dear Dr. Dunsworth,

Thank you very much for submitting your manuscript "Luck of the draw: Evolving flipbooks mimic non-selective processes" for review by _________. As with all papers reviewed by the journal, yours was assessed and discussed by the editors. In this case, your article was also assessed by an academic editor with relevant expertise and three independent reviewers. Based on the reviews, I regret that we will not be able to accept this manuscript for publication in the journal.

The reviews are attached, and we hope they may help you should you decide to revise the manuscript for submission elsewhere. I am sorry that we cannot be more positive on this occasion.

Overall, the reviewers and the academic editor thought the approach is innovative, though should be more firmly grounded in the prior work dealing with students' understanding of "random" and evolutionary processes.

I honestly thought it was grounded in common knowledge, but I should have cited this and this. (A useful side tip: I perform pre- and post-tests at the beginning and end of each semester with a survey that I built thanks to Cunningham and Wescott's paper. The survey really helps me gauge where students are and where they end up so that each semester I can hopefully help them end up even better. This semester I showed them last semester's stats on day one, tackling some of the issues head-on, like the fact that before taking my course 8% of them think dinosaurs and humans lived at the same time in the past, and 84% think that new traits arise because they need to.)

In addition, the academic editor worried that the activity runs the risk of confusing students by omitting a big piece of the process (selection).  

I assumed that selection would be covered well in other ways and that this activity would complement those efforts.

The reviewers also point out that it is unclear how the activity could be evaluated so that others could determine its efficacy relative to other activities.

If this is how teachers operate, then I’ve got a lot to learn. I didn't have a control group either. Never do!

The evaluation suggestions will be difficult to access, since many rely upon how "different" two drawings are, something that will be difficult to measure accurately and consistently.

It's hard not to jump to this conclusion: If you can’t assess the students’ work easily, then don’t have them do those things or think about those things. Alternatively, it could mean that to publish a lesson plan you must provide teachers with ways to assess the all the things that they ask of their students. Maybe this is one of the big differences between college and everything that comes before it.

For example, because individual viewers may well have different views as to whether or not the flip animations differ from the template, an exercise controlling for or illustrating the bias in viewer perspectives would seem necessary.

This is an exercise that illustrates the subjectivity. I think the issue here is that I should have included explicit instructions for counting, measuring or otherwise evaluating traits and their changes over time, and in deciding whether different drawings should be called separate species or not, rather than suggesting that teachers merely ask students to do all that on their own. But to me setting students free to do those things is a pretty important, and effective, part of the process assuming that the fundamental concepts will be covered in class as follow-up (something I assume teachers would do if speciation and classification were topics that they chose to address with the flipbooks). I think this is, again, my limited experience and college-level bias showing.

Even more problematic, however, is the possibility that students might take away the message that rather than random processes, overlaid by selection, account for increasing complexity in evolution, it is the work of an "intelligent designer." This is obviously not your intent, but something that Reviewer 3 points out may occur.

I had a hunch I’d get pinned for unintentionally promoting ID and I thought I was anticipating some of that in my concluding remarks. If teachers take on those issues (and I hope they do!) there are myriad resources out there to support them starting here and here on the MT and also here: http://ncse.com/.

I hope you appreciate the reasons for this decision and will consider _________ for other submissions in the future. The support of the community is essential if open access publishing is going to succeed, so thanks again for your interest.

Sincerely,
Editor
------------------------------------------------------------------------
Reviewer Notes:

Reviewer #1: While the author has identified a challenging educational issue - differentiating drift and selection as mechanisms of evolution - I found the framing of the problems and the connections to the instructional activity tenuous. There is an extensive literature dealing with students conceptions of "random" event, evolution, and teleological reasoning, none of which were referenced here. The activity was clearly described and sufficient context was supplied to support a teacher interested in adopting it for classroom use. There was, however, no evidence that the activity support the intended learning outcomes or that students enjoyed the lesson. I think we need to have a wide range of strategies for engaging students in evolutionary reasoning and in certain situations this resource may provide a mechanism for raising students awareness about the potential role of drift in evolutionary change. Unfortunately, I don't think this manuscript fits well in this journal and I believe it would be strengthened by connecting it to existing educational research.

Reviewer #2: The paper Luck of the Draw: Evolving flipbooks mimic non-selective processes describes an activity where students create flipbooks by tracing over drawings of either recognizable or unrecognizable templates.  Because tracing is not perfect, and students repeat the tracing effort over many pages, the final outcome provides an example of how small random changes can lead to evolution.  The paper is extremely well written, and the idea of the flipbooks very creative.  The author provides exceptional resources, including links to teaching tools explaining the art of animation, to leading questions for student follow-up and assessment of understanding.  The added figures help the reader visualize the degree of variation that can accumulate over the course of the exercise.  The focus on helping students understand how random events influence evolution is great.  The author correctly identifies a significant problem - too many activities focus on selection, and students, who are already challenged in understanding the concept of random, all too often believe evolution equals natural selection.  Many of the antievolution arguments focus on the perceived impossibility of random events resulting in the evolution of complex structures.  Helping students understand how random events might influence evolutionary change is a very worthwhile educational strategy.

Reviewer #3: This is a very good foundational activity for introducing evolutionary mechanisms.  The chief concern relates to the directionality and complexity issues raised in the concluding remarks, which may be an unavoidable result of the tracing instructions given to students. It seems as though attempts to trace will always result in degradation of initial templates into blobs, which feeds into the 2nd law and mathematical impossibility notions advanced by creationists. So while you may be able to introduce other mechanisms, is one doing so at the risk of demonstrating that the "intelligent designer" of the student themselves is really the take away lesson.  While the point of this exercise may be to raise awareness of the random aspects of evolutionary processes, it may not be clear to students (or pre-college teachers), that they should expect this sort of behavior from such a random process, and that the accumulation of order and complexity results from the overlaying of selection onto random variation.  One suggestion to be considered is to ask if it might be possible to give the students any other instruction that could lead to an accumulation of complexity, without being too Panglossian or feeding into even worse ID notions. Maybe something like "if you see an acute angle, make it into a loop", or something similar that might lead to feature accumulation without having students try to achieve a predetermined target shape. The concern still is that the reason for the variation to be introduced is being produced by the generator, not the system. For more advanced student audiences it seems appropriate to suggest that teachers provide some refutation of the mathematical impossibility argument based on the idea that specifying any specific outcome for a probabilistic system is difficult, but that some outcome has to result.

Part of what  this reviewer is picking up on with the flipbook metaphor/activity is that tracing errors seem to miss parts more than add parts. This would appear to play into Behe's and other ID/creationist arguments that  mutations only chip away at complexity rather than contribute to it. Obviously this activity is only a metaphor and it also cannot go without a companion lesson in selection (which helps a great deal with complexity). One way to avoid giving the impression that mutations only take away complexity would be to stick to unrecognizable templates. But I don't recommend doing that since the recognizables offer great opportunities for teaching the important random mechanisms that are the focus of the lesson. (See 'concluding remarks' where I explain how the recognizables are where students struggle to see the role of chance.) I think that I inadvertently encouraged this reviewer's concern with my wording in that second to last paragraph in the 'concluding remarks.' I should have pointed out how some resulting drawings appear more complex than the templates before going into the trouble with perceiving complexity in the recognizable ones. I think I underestimated how powerful this metaphor could be.


But, overall, regarding #3's issues... I am satisfied with what I laid out in my concluding remarks. Teachers may choose to face the complexity issue explicitly in class and if so they should probably discuss how mutations that cause variation do contribute to the evolution of complexity--even with a mutation that reduced the number of chromosomes in the human lineage, we consider ourselves more complex than chimpanzees who retained one more pair than we did. In the article I cited the famous eye evolution paper for demonstrating the evolution of complexity over time with the accumulation of small mutations. You could also discuss gene duplication's role in complexity. You could talk about hox gene expression in bat wings and bird beaks. You could discuss lactase enzyme production into adulthood and the various known SNPs to allow this in some populations. Even the famous sickle-cell and malaria example illustrates how mutations add to complexity. Ken and Anne have recently listed off a few examples here. Some of these issues raised by ID and anti-evolution folks aren't much more than semantic arguments and differences of perspective...which are issues that stray far from the real biological ones they claim to be about. The same is true, I suspect, for some debates within the evolutionary sciences.


Regarding the suggestion to ask students to deliberately change the drawings in directed ways... I'm uncomfortable with changing the human tracer away from what it is--an imperfect DNA copier--because I worry that would support notions of agency, religious and secular alike! (see my rant here) I also don't think that it's up to an evolution lesson to disprove agency because nobody can do that. What we can do is show how evolution occurs without agency (like we do with this activity). 
------------------------------------------------------------------------

My final thoughts and requests for teachers

These reviews have left me feeling a bit daunted about helping to strengthen evolution education at its earlier stages so that fewer people make it to college and through college so full of misconceptions. If the pre-college rule is that you can't teach something that can't easily be assessed or that you can't teach something that would possibly be fodder for creationists, then I think we risk miring ourselves in the status quo. Religious objections are only one  kind of obstacle to learning and teaching evolution, and letting that one obstacle dominate our pedagogy limits our ability to overcome the rest of them.

Teachers, if you try 'Luck of the draw' please consider the issues raised by the people who put time and effort into reviewing it. 

Take my word for it--students have a lot of fun with it and learn a lot from it. It's a great activity to have students perform if you're away traveling. They can meet somewhere more exciting than the classroom, trace the books together, then bring them back to the next class for discussion when you return.

Trust me, it's not complicated--it's just that there are so many concepts you can choose to run with!

And when you're all done, please leave feedback here. I'd love to know how it goes! I'd love to hear suggestions for improvement!

(c) Holly Dunsworth
Note: I know it's a blog, but this is where I chose to publish. That means, if you use this then find a way to cite it, please. Thanks and welcome to the future!


I'll gladly share a nice printer friendly version of 'Luck of the draw' with anyone who'd like it. Just let me know.

Reducible Complexity: reply to the IDeologs

The gaggle that continue to raid evolutionary biology blogs, patrolling for things that can be naively or intentionally misinterpreted as evidence for their theological views, specifically 'Intelligent Design' (ID), loves to concentrate on complex traits.  They claim such traits cannot have evolved because the independent components won't function on their own and the whole breaks down without them.  They call that Irreducible Complexity:  since you can't take any components of complex traits away and still be viable, such traits could not have arisen gradually by natural selection.  Therefore (the IDeologs say), Intelligent Design is true.  But this is false on several grounds, not all of them even recognized by biologists, who often defend evolution by needlessly agreeing to do it on the IDeologs' turf.

First, it is IDiotic to argue that if an evolutionary claim is false, therefore creationism is true.  That is simply a logical fallacy.  If evolution as biologists see it were being misperceived, that in no way provides evidence for any specific counter explanation.  Only an IDeolog would make such an argument.  It would be just as sensible--that is, as nonsensical--to say that our misperception proved that life came to earth from a parallel universe in a spaceship made of banana peels.  We get things wrong or understand them incompletely in evolutionary biology, which is why it remains an active science, but that is not evidence that evolution didn't happen.

Second, the major IDiotic argument about the need for completeness was one Darwin was aware of and even speculated on in regard to the eye, a favorite irreducible complexity example cited from that time to the present day.  Darwin suggested ways that primitive light sensitivity could have evolved bit by bit.  In what was really striking prescience, his basic speculations have been shown to be about right, because species alive today with 'partial' vision have been found, and genetic components of vision are shared among species with simple as well as complex light reception.  Even saying 'partial' vision is a subtle misnomer, because each species uses what it has: the light sensitivity of a worm or bacterium is not partial for their uses, and to use the adjective suggests the IDiological view that humans are at an intended pinnacle, that our vision is somehow more complete or real than a clam's.  That's an egocentric misperception of evolution.

Complexity is reducible!  It always has been.  It's a central aspect of life.   Right here and now
Thirdly, and perhaps even more important than the first two reasons why the anti-evolutionary IDeology is just plain wrong is that complexity is typically reducible!  The basic IDeologs' premise doesn't have to be refuted because it's not true.

What we know very well is that most traits of organisms are, in fact, the result of multiple interacting factors (gene networks, the  polymeric, cooperative nature of DNA and proteins, signaling and receptors systems, gene regulation, and multipart proteins, etc.).  And, eyes, too.  That is a central fact, and a main point of MT (the blog and the book).  We know from thousands of studies (yes, even the GWAS and other 'omics' studies whose excesses we love to point out) that complex traits really are complex at the gene level.

The same studies also show by their very nature--by the very fact that we are doing so many of them in the first place--that each person will have a different genotype, a different set of variants, involved--even if they have the 'same' trait, like stature, insulin levels, blood pressure, or behavior.  That is why personalized genetic medicine is unlikely to work nearly as well as advertised.  Personalized medicine almost assumes irreducible complexity: enumerate the parts and then any variation in the trait must be due to a broken part that can be identified.  But that isn't how Nature works.

Reducible complexity is true even of vision: Color-blind people are people and they have vision, yet they are missing functional light-sensitive genes (e.g., genes that are used in red or green detection, or overall light sensitivity). Visual acuity varies in all sorts of ways among perfectly viable people.

This is typical of biological traits.  And recent studies have clearly shown that each of us is walking around with numerous completely inactivated genes, whose 'damaged' sequence variants we have inherited--from parents who somehow had managed without them.  One recent paper found that around 165 different genes were completely inactivated (both copies not working) in a typical person.  And there are many others in which one of our two copies is not working normally.  The combination of inactive genes would be different for each person, but the truth is that we do not normally need all the genes in our genome.  That tolerance of variation is exactly the working material that biologists have known is at the basis for evolution from Darwin's own time.

Confirming this in another way, and also very clearly, is that it is routine that a gene experimentally inactivated in a laboratory animal, like a mouse, has serious effects in some strains but little or even no effect in others. A mutation causing a serious disease in humans may do nothing when the same mutation is tested in a mouse, or it may have similarly bad effects only in some strains.  That's one of the notorious problems with mouse models for human traits: mice and people share many traits but we make them differently to various extents. There is more than one way to make the same trait.  Complexity is reducible.

The reducibility of a trait, to put it in terms even an IDeolog could understand, depends on the combination of genes being viable, not on every gene having the most functionally efficient variants.  The importance of component cooperation, a favorite MT word, is in part that various types of cooperation are viable.  That aspect of redundancy and variation is one of the central reasons that complexity could evolve in the first place, exactly in the general fashion argued by Darwin and since.  No biologist suggests that an eye just emerged wholesale from the primeval slime.

But there's more.  Studies of the nature and evolution of genomes shows very clearly that genetic mechanisms arise largely by means that generate redundancy as well as alternative pathways to given outcomes, as cells respond to their local environment.  Gene duplication occasionally leads to individuals with two copies of a gene where in their ancestors there was only one (this happens in species generally, not particular to humans in any way).  That can provide redundancy, so that one of the copies can acquire mutations that alter what the gene does, while the other copy keeps plugging along with the original function.  The new function can be due to mutations in the  protein code of one of the copies, or the DNA sequences that regulate when and where the gene is used.

For these reasons, traits are the result of many different genetic contributions, all varying among individuals, each reaching similarly viable traits with different combinations of that variation.  Those combinations that aren't functional don't survive or reproduce; those that have an advantage may do better.  Over time, the mix of variation, including even the number and set of contributing genes, allow traits to evolve new or altered function.

This is how evolution works, gradually producing new or varied traits.  We understand this because we are aware that complexity is often, or even typically, reducible.  Although it hasn't been put this way before to our knowledge, this is nothing more than a modern understanding of classical evolutionary ideas.

The IDeologs claim that reduced complexity could not have existed in a stepwise, bit by bit, assembly of a new trait from parts that would not work on their own--that evolution couldn't get from there to here. But the deeper truth is that evolution is both there ('incomplete') and here ('complete') today and has been that way at any or even every time in the past.   It isn't just that things have to be assembled over time by different steps, but that they exist at any given time in various steps or stages of 'completeness.'  To a great extent, biological complexity is  inherently reducible at any time as well as over time.

And one more reason:  Of course, we needn't have gone through all of this to convince you that complexity was reducible, after all.  That is because the IDeologs disprove their own irreducibility argument by their very existence:  one can function as a human being even with a brain that allows you intentionally not to use it to recognize the realities of the world--by not using the thinking complexity they were born with!  We would apply this to those who lead the movement, and do or should know better, but not those who they naively lure into adopting its know-nothing IDeology.


Finally, we may make sport of intentionally or willfully self-deluded critics of evolution.  For any of those who are sincere but naive, one can only say that it's too bad, and poignant, too, that science shows the evolutionary nature of life, rather than the comforting existence of a benign divinity who graced the earth with our presence.  How nice if that could be true!  How hard it makes it to understand the injustices and suffering in the world.  But science is about the real world, not the one we might wish for.