The Greatest Show on Earth (Dawkins, 2009)

 Richard Dawkins. The Greatest Show On Earth. (2009) Most of Dawkins’s work has been the attempt to convince people that Creation Science, aka Intelligent Design, is wrong. This book is his marshalling of the evidence that evolution is real, and that we have increasing knowledge and understanding of how it happens. The basic principle is random variation constrained by deterministic laws of physics, chemistry, and biology. It’s because most mutations do not improve the organism’s chances of surviving long enough to breed, or to outbreed siblings and cousins, that the few favourable mutations not only gain a foothold but spread. IOW, while mutations are random, their effects are not, and that is enough to guarantee that most beneficial mutations will usually spread while deleterious ones will not (if they haven’t killed their hosts). One consequence is that the best versions of essential genes are conserved across species. The preservation and spread of favourable genotypes is what “natural selection” actually means.

A well done book, which in the end is the best refutation to the pseudoscience peddled  by the creationists. Recommended. ****

Footnote: It seems to me that one of the motivations for Creationism is a misreading of the Bible. The assumption seems to be that the factual truth is primary. Or Fundamental. Or even the Only Truth. Therefore there is only one legitimate method of interpreting the biblical texts, namely to assume its factual truth. From this point of view, only factual truth can guarantee the truth of whatever moral or theological or other propositions the reader wishes to assert.

But the assumption that factual truth proves moral, theological, and other abstract truths has a fundamental problem for the believer: By making factual truth primary, religious truths are logically contingent. That means that any changes in factual truths may change religious truths. At some level, fundamentalists seem to understand this, hence their insistence that the factual truths they read into the biblical narratives cannot be contradicted. It also means they must find ways of proving the truth of the facts as stated in the Bible.

Evolution 101: What it isn’t, and what it is.

It's taken me quite a few decades to clarify my understanding of evolution.

For example, like many people, I once believed that evolution somehow improves a species. Problem is that we think of improvements from our human point of view. That often makes our notions of improvement irrelevant. And even when our notions of improvement are relevant, they may be mistaken.

A widespread mistaken expectation is that evolutionary theory gives definitive answers. It doesn't. No science does, although some answers are more definitive than others.

Several years ago, a blog I read claimed that the epicanthic fold is “unimportant” if not “useless”, and therefore its existence makes the theory of evolution doubtful. For evolution is all about developing useful traits, right?

Well, no, actually. I'll take up the epicanthic fold.

a) "Unimportant" and "important" aren't what a human might think they are. Just because someone may think something is an unimportant feature doesn't mean that it really is. What’s more, “important” depends on context. "Context" for an organism means its environment.

b) The epicanthic fold may be a consequence of genetic drift. Evolution will not eliminate neutral changes in the genome. Accidents of mating may therefore concentrate some part of a genome and so enhance a particular variation of some trait. The primary accident of mating that affects this is the size of the mating pool. In a small population, genetic drift can show up within half a dozen generations or less, and can disappear just as quickly. In larger populations the effect is slower. However, a trait may become universal.  A secondary cause of genetic drift is aesthetic preferences (for want of a better term), aka as "sexual selection".

c) Actually, the epicanthic fold is helpful in the Arctic in late winter and early spring, when there's still lots of snow around, and the sun is higher in the sky. By shading the pupil of the eye, it reduces the glare from snow and sky. Fact is, the Inuit made sunglasses by cutting narrow slits in flat bones which were fastened in front of the eyes. These are artificial epicanthic folds taken to the extreme, so to speak. It’s also helpful in insulating the eye.

d) The epicanthic fold shows up in several variations. I have a version, but it's not like the one you would see on a Japanese person.

Generally speaking, the phrase "survival of the fittest" has caused much misunderstanding of evolution. It does not mean "survival of the strongest or fastest or etc". It means survival of those who fit their environment best; those which are the best suited to their environment. At the time the phrase was coined, “physically fit” was also becoming common. It meant something like “physically well put together, hence suited to strenuous exercise”, but quickly morphed into “physically superior”.

“Being best suited to their environment”  has a consequence that may seem counterintuitive when evolution is seen as primarily explaining changes. Evolution will preserve traits necessary for life, or that maintain a good adaptation to the environment even when the environment changes. That’s why we share so much of our genome with other animals. The shared bits code for features such as enzymes or hearts, without which survival would be impossible or difficult in any environment.

On the other hand, genetic changes can change the environment, because every organism is part of the environment from the point of view of the other organisms in that environment. If the change confers some survival advantage, there will be new selective pressures on some of the other organisms, and they may change, which may change the selective pressures on still other organisms, including the one that triggered the changes. That means that adaptation is a complicated feedback loop. Or rather a feedback tangle, which means it’s a complex system. As in ecosystem. Unfortunately, our brains are not very good at making sense of simple systems, let alone complicated ones.

As for genetic determinism: People who believe that genes rule are way behind the curve. Genes cannot "determine" anything in the absence of environmental inputs, which includes inputs from other components of the organism itself. In fact many genes will have no effect until some environmental trigger causes them to "express", that is, to start making the proteins they specify. What happens next may eventually trigger other genes. This, in a general way, is how an organism grows and develops.

You are what you are because of your genes _and_ your environment, and your environment includes the environment of your ancestors. Environmental factors can change the DNA by a process called "methylation", which affects gene expression. One consequence of methylation is that a mother's or father's illness can affect their children and grandchildren, and possibly even their great-grandchildren.

Evolution is complicated, but it works because of the interaction of the environment and genetic differences between individuals. If an individual lives long enough to reproduce, its genes and the genes of its mate will survive for another generation. If some variation improves the odds of having more offspring than average, that variation may spread through the following generations until it dominates the population. Cumulative changes may make offspring long separated in time and space so different that they are different species.

But what’s a species? That’s another concept that's not so easy to define. I’m not happy with my concept. I may discuss the results of my attempts at clarification here. Or maybe not.

What is Life? A comment on Viruses

There have been many definitions of “life”. I think the simplest definition of life is this one: Life is a system that acquires the substances and energy needed to continue to exist and to reproduce. If it fails to do this, it ceases to exist. Any such system is an organism.

By that definition, a virus is alive. It’s the simplest form of life: a packet of genetic information that drifts about until it latches onto a cell that it can invade. It then uses the cell to acquire the substance and energy it needs in order to reproduce.

Since a virus needs another organism to survive and reproduce, it is a parasite. Most parasites either do not harm their hosts or provide some benefit. A few (mostly microbes) are necessary for their host’s well-being and even continued existence. A few parasites harm their hosts, and some kill their hosts. A parasite species will survive only as long as its hosts do not die out.

It’s likely that many viruses, like many microbes, are not merely beneficial but necessary for their hosts’ well being. We know enough about bacteria, for example, to know that without them we would have trouble digesting much of our food. We don’t know that much about viruses. But we do know that some of them kill bacteria that are dangerous to us. We also know that viruses can transport bits of DNA between species, and that this sometimes results in beneficial changes to an organism’s genome.

What all this amounts to is that we are woefully ignorant of viruses’ roles in the web of life. The handful that bother us create the impression that we would be better off without them. That is certainly a false impression. We just don’t know enough. Yet.

Footnote: Very early on, some computer programmers wrote small programs with a rather strange property: they would use the computer's operating system to write copies of themselves into every available memory space. Rewriting these programs so that they would send copies of themselves to other computers was the next step. Thus the computer virus. Are they alive? Most of them are not. To be alive, the program would have to also prevent the computer from shutting down, thus maintaining the energy it needs for continued existence.

Do we live in a simulation? (long read)

A comment on David Chalmers’ ideas about virtual reality

Abstract: I argue that the brain’s construction of our experience is in fact a simulation, and consider some of the implications of this view.

David Chalmers has recently been noticed for his ruminations about whether we live in a virtual reality (or simulation), and whether we could tell. In an interview published in New Scientist, he claims that we could not know whether we are living in a simulation. (1) On CBC’s radio program Quirks and Quarks he was one of three people asked this question (2), and Mary Hynes interviewed him on Tapestry. (3) Several of his discussions around this topic are available online: a search on “David Chalmers virtual reality” will present a dozen or more examples.

My answer is, “Of course we live in a simulation. It’s the one created by our brains.” (4) What’s more, the “I” that experiences this simulation is itself part of the simulation. So it would be more accurate to say that “We live as a simulation created by our brains.”

As asked, the question assumes that “I” is somehow distinct from the simulation. That assumption is misleading. Its explicit formulation dates from Descartes, who assumed that mind (or perhaps soul, he’s not very clear on the distinction) and body are separate. He does this because we experience our bodies. But that experience of my body is the “I” that experiences it. There is no separate experience. That is, there is no evidence that “I” can experience anything other than what my body and brain present as reality, which includes the experience of “I”. Thus, the simulation of reality includes “I”. (5)

Elsewhere, Chalmers has claimed that consciousness is the hard problem. Yes it is, if one assumes that “I” is separate from the reality it experiences. However, if “I” and experienced reality are one, then “I” is what is simulated as the experiencer.

Each of us lives as their own simulation. We can compare those simulations by converting them into other simulations. We can talk about our experience, or make pictures, or replicate the situation in the presence of other people, or ask others to do what we did. (6) What’s important about these comparisons is that we can detect differences, and we can detect them reliably. For example, I don’t know whether you see red or green as I do, but we can tell whether or not we see the same or similar differences between red and green. I don’t know how you see Aunt Emily, but we can both recognise that a photo is or is not a picture of her. We can also tell whether we both see that one portrait is a painting and another is a photograph. And that one shows her as a girl, and the other as an old lady. (7)

Science is the attempt to describe whatever it is that the brain simulates. That is, science is an attempt to create a simulation that is the same for everyone. Thus, a scientific theory is an attempt to eliminate the differences between our individual simulations. Suppose I can’t see the same red/green difference that you see, yet by some method we can both detect the same difference between red and green. One method would be to measure the frequency of red and green light, and agree that we observe the same measurements. By this method we have filtered out those idiosyncratic differences caused by the differences in our retinal cells and brains. We have created a simulation (the measurements) that we have in common. We have replaced our individual “subjective” simulations with a common “objective” one. We infer that the shared method of seeing red/green difference must therefore be closer to whatever it is that our simulation simulates. We call that whatever-it-is “reality”. But in fact all we ever do is compare simulations.

Scientists have discovered that aspects that can be mathematised are constant in a way that other aspects are not. This relates to what Wigner called the “The Unreasonable Effectiveness of Mathematics in the Natural Sciences”. (8) I don’t think it’s unreasonable at all. Mathematics is the part of language that translates exactly from one language to another; it’s a lossless translation. For example, no matter how the symbols are pronounced, the algebraic expression (a+b=c) means exactly the same in every language. (9) As every multi-lingual person knows, there is something lost in the translation of every other kind of speech. Each language creates a different simulation; neither their elements nor the relationship between elements map exactly onto each other. Languages are not congruent simulations; they are similar but not identical. The constancy of mathematics across languages preserves what’s constant across simulations. (10)

Mathematics works by abstraction. Moreover, it does not describe content, but structure. A mathematical statement expresses a relationship between two or more entities. The red/green difference can be expressed as a difference in wavelength: red is larger than green. This statement says nothing about the experience of red and green that we may or may not share, nor does it say anything about the quality we label “colour”. It states only that one aspect of our experience of the colours red and green is constant. It also states that we must take care to arrange our experience so that this constancy is revealed.

The consequence is that the closer science gets to a universal simulation, the more abstract that simulation becomes. It is finally pure structure. The most abstract simulation is that created by physics. Einstein’s relativity theories are descriptions of structure. Special relativity describes how the shape of one person’s experience can be precisely transformed into the shape of another person’s experience, given that we know their relative velocities. General relativity goes a step further and describes our experience of reality in terms of its space-time structure. Quantum physics describes interactions, that is, the behaviour of entities that behave differently (for example like waves or particles) depending on context. Hence what we can know about them is context bound. What’s more, context defines events and vice versa. Thus, quantum physics describes reality in terms of event-contexts.

But neither theory describes whatever it is that we label reality. They describe structures, the structure of space-time in the one case, and the structure of event-contexts in the other.    

Both theories are highly abstract. They are highly reliable and precise in predicting how we will experience those abstract aspects. Hence the belief that these more abstract descriptions are truer descriptions of reality than the more concrete subjective simulations of reality that our brains create. I don’t think that belief is justified. What’s more, I think the question of what’s real is an unanswerable one. We know our own experience, because we are that experience. We can know some of what each other’s experiences have in common, because we can talk about them, or make pictures of them, or express aspects of them in music and dance, or describe them using mathematics.

                                     

In the New Scientist interview, Chalmers says “I think, at the very least, virtual worlds [created by virtual reality devices] provide a particularly pure illustration of Descartes’s problem.” Descartes had a problem because he assumed not only that body and mind are separate entities, but that one is physical and the other is not. (11) Chalmers perpetuates Descartes error by asking whether we can know whether we “live in” a simulation. That question makes sense only if “I” and the simulation are ontologically distinct entities. (12) Assuming that distinction begs the question: If “I” is not an essential part of the simulation, then of course we can know “I” is “living in” that simulation. The question is interesting, that is productive, if and only if “I” is an essential part of the simulation.

The brain creates the experience of reality, including “I” as the experiencer of that reality. We can know no other. It is the brain’s creation of our experience that enables “virtual reality” devices. What’s significant about these devices is that they present the “first-person” viewpoint. That is, they present the same structure as the subjective reality that they imitate. They are incomplete, however, because they do not simulate the proprioception necessary to experience the 1st person viewpoint as “I”. (13)

Chalmers ends his New Scientist interview with “A sort of structuralist conception of reality – that the world isn’t intrinsically the way we thought it was, but still has a similar sort of structure – is very strongly suggested by modern science.” I think he’s right. The brain’s simulation of reality is enough like reality, whatever reality “really is”, that we survive quite well. But exactly how much it is like reality can’t be decided. The theories of physics are highly abstract descriptions of some aspects of the structure of our experience of reality, and that is the best we can do.

Notes
(1) Interview with David Chalmers in New Scientist: https://www.newscientist.com/article/mg25333710-900-david-chalmers-interview-virtual-reality-is-as-real-as-real-reality/

(2) Broadcast 2022-03-05. https://www.cbc.ca/listen/live-radio/1-51-quirks-and-quarks/clip/15898721-could-living-computer-simulation-and-were-tell

(3) Broadcast 2022-08-23 https://www.cbc.ca/radio/tapestry/are-we-living-in-a-simulation-look-to-free-guy-not-the-matrix-for-answers-says-david-chalmers-1.6393525

(4) Here’s one explanation of how the brain does this; an online search will garner many more: https://neuroscience.stanford.edu/news/reality-constructed-your-brain-here-s-what-means-and-why-it-matters

(5 ) Every creature with a brain computes some simulation of reality. The bar for accuracy and completeness is rather low. The simulation needs only to be good enough to raise the odds that the creature will survive long enough to reproduce. For example, a frog reacts to a moving fly-size blob, but not to a static one. It will try to catch a raisin tossed past it, but will ignore a dead fly lying near it.

(6) The arts can create simulations of realities that don’t exist, and even of realities that can’t exist. We call these simulations “fictions”. Simulations of reality are called “history”, “physics” “reports”, “portraits”, "descriptions", etc. We have many terms for simulations, because we can make so many different kinds of them.

(7) These comparisons depend on our memories of Aunt Emily. That is, we compare one simulation (the photo of Aunt Emily) with another (our memories of Aunt Emily).

(8) http://www.hep.upenn.edu/~johnda/Papers/wignerUnreasonableEffectiveness.pdf

(9) Wigner writes “My principal aim is to illuminate it from several sides. The first point is that the enormous usefulness of mathematics in the natural sciences is something bordering on the mysterious and that there is no rational explanation for it.” It seems to me that this statement encapsulates Wigner’s puzzlement. I think he fails to notice that mathematics is a component of language. It is not a separate language.
    All known languages include ways of expressing or describing number, size, shape, spatial and temporal relations, collections of things (sets), kinship (classification), rates of change, etc. These terms label mathematical concepts. The number and sophistication of mathematical terms or concepts varies between cultures, but all cultures have mathematical concepts. These concepts are used to communicate individual experience just as the rest of language is used.
    Mathematics begins as an attempt to regularise trade, property, kinship obligations and rights, etc. That is, mathematics is part of the attempt to find those common elements of our individual experience that satisfy our desire for justice, fairness, equity, connection, community, etc.
    Mathematics as a method for enabling and enforcing justice, fairness, equity and so on was formalised in rules of kinship rights and obligations in pre-literate tribal societies, and such rules still make up an essential part of what we experience as our way of life. Literate societies wrote down these rules, and added recipes for calculating the requisite quantities.
    Mathematics as a discipline begins with Euclid’s attempt to organise the concepts into a logical structure. This logical structure translates exactly from one language to another.

(10) Linguists refer to “idiolects”, our idiosyncratic versions of our common language. That idiosyncrasy is in fact the definition of “style”. To understand someone is to translate their idiolect into one’s own, a process we perform almost entirely without conscious awareness. That unconscious translation is one source of mutual misunderstanding. See Steiner (1975).

(11) Another problem generated by the mind-body dichotomy is expressed as “How can the non-physical mind cause physical effects?”

(12) Another version of this problem is whether we would ever know whether we were minds uploaded into a computer.

(13) It’s not clear how a virtual reality systems could provide proprioception. Some kind of body-suit could provide external sensory inputs, but it couldn’t provide internal ones. Perhaps inputs through the brainstem could do it, but experimentation would raise interesting ethical problems. The study of the sensations produced by training simulators is instructive: Our brains can and often will construct more complex sensory experiences than the actual sensory data provide.

Bibliography
Many thinkers have stimulated my ideas. I am grateful to them all. The following represents a small selection of the sources most relevant to this paper.

Damasio, A: Descartes' Error: Emotion, Reason, and the Human Brain (1994; revised 2005)
Damasio, A: The Feeling of What Happens: Body and Emotion in the Making of Consciousness (1999)
Gelernter, David H: The Muse in the Machine: Computerizing the Poetry of Human Thought (1994)
Hawking, Stephen: The Theory of Everything (2002)
Hofstadter Douglas & Dennett, Daniel: The Mind's I: Fantasies and Reflections on Self and Soul (1981)
Hofstadter, Douglas: Gödel, Esher, Bach: an Eternal Golden Braid (1979)
Hofstadter, Douglas: I Am a Strange Loop (2007)
Kraus, Lawrence: A Universe From Nothing (2012)
Norman, Donald A.: The Psychology of Everyday Things (1988)
Rees, Martin: Just Six Numbers (1999)
Rosenfeld, Israel: The Strange, Familiar, and Forgotten. (1991)
Sacks, O: The Man Who Mistook His Wife for a Hat (1985
Sacks, O: The Island of the Colorblind (1997)
Sacks, O: The Mind's Eye (2010)
Steiner, George: After Babel (1975)

2022-04-14

What is Life? A comment on viruses.

There have been many definitions of “life”. I think the simplest definition of life is this one: Life a system that acquires the substances and energy needed to continue to exist and to reproduce. If it fails to do this, it ceases to exist. Any such system is an organism.

By that definition, a virus is alive. It’s the simplest form of life: a packet of genetic information that drifts about until it latches onto a cell that it can invade. It then uses the cell to acquire the substance and energy it needs in order to reproduce.

Since a virus needs another organism to survive and reproduce, it is a parasite. Most parasites either do not harm their hosts or provide some benefit. A few (mostly microbes) are necessary for their host’s well-being and even continued existence. A few parasites harm their hosts, and some kill their hosts. A parasite species will survive only if its hosts do not die out.

It’s likely that many viruses, like many microbes, are not merely beneficial but necessary for their hosts’ well being. We know enough about bacilli, for example, to know that without them, we humans would have trouble digesting much of our food. We don’t know that much about viruses. But we do know that some of them kill bacteria that are dangerous to us. We also know that viruses can transport bits of DNA between species, and that this sometimes results in beneficial changes to an organism’s genome.

What all this amounts to is that we are woefully ignorant of viruses’ roles in the web of life. The handful that bother us create the impression that we would be better off without them. That is certainly false. We just don’t know enough. Yet.

Footnote: Very early on, some programmers wrote small programs with a rather strange property: they would use the computer’s operating system to write copies of themselves into every available memory space. Rewriting these programs so that they would send copies of themselves to other computers was the next step. Thus the computer virus. Are any of them alive? Yes, any virus that can prevent the computer from shutting down, thus maintaining the energy it needs for continued existence. Are there such computer viruses? I don't know. But anything I can imagine, anyone with similar information can imagine. Therefore, someone has imagined such a virus. And when a programmer can imagine a program's functions, creating the program is just a matter of time and effort.

The state of corona virus knowledge as of today (May 3, 2020)

SARS-CoV-2 (the virus) and covid -19 (the illness)

Here’s what “we” know and don’t know as of 2020-05-01. “We” are the people who’ve collected and interpreted the data. “We know” means the data strongly support the conclusion. “We don’t know” means there are insufficient data to draw a conclusion. Compiled from reports in science news magazines, media reports, and Q & A sessions with experts.-WEK

A)    We know: Some people are infected with the virus but don’t get sick.
    We don’t know: how many.

B)    We know that the effects of the virus range from zero to death; and mild to lethal complications.
    We don’t know: Why the virus has such a wide range of effects.

C)    We know: there is a time between infection and symptoms during which a person will be infectious.
    We don’t know: the actual range of both time and severity of this infectious state.

D)    We know: that people who’ve been infected will have anti-bodies in their blood;
    We don’t know: whether the presence of antibodies gives immunity, nor what degree  of immunity, nor how long such immunity might last.

E)    We know: there will be second wave of infection, and probably a third and fourth one,
    We don’t know: how bad these subsequent waves will be.

F)    We know: that some of the economic and social effects will be permanent.
    We don’t know: which effects, nor how these effects might change over time, nor what  the knock-on effects will be.

G)    We know: covid-19 will become another infectious disease that will take its yearly toll.
    We don’t know: when that will happen, nor how common or lethal covid-19 will be.

H)    We know: that some anti-viral treatments show some activity against SARS-CoV-2.
    We don’t know: whether that activity will be good enough for effective tretament.

I)    We know: effective treatments and a vaccine will reduce the danger of covid-19 to that of the flu.
    We don’t know: which treatments will be effective.
    We don’t know: whether a vaccine is possible, and if possible, how well it is likely to work.

J)    We know: the counter-measures have reduced infection rates.
    We don’t know: how effective those counter measures actually were.

K)    We know: that a combination of dry cough and high fever, with some other signs such as difficulty breathing, indicate covid-19. But only a test can confirm the diagnosis.
    We don’t know: what other signs and symptoms may be indicators of covid-19.

Update 2020 05 04: UK doctors have observed covid-19 patients with low and extremely low blood oxygen levels, but without the usual distress. Another puzzle.

Perception: Colours

This is a fragment of a conversation in a newsgroup some years ago. I included parts of three prior posts (in chronological order) in the thread to show the concepts I commented on.

[A]
I was once asked "How many colors are there?". A difficult question, which many people can't answer, they've confused "how many colors" with "how many WORDS for colors". 2^24 (16,777,216) is a better answer than that.

[B]
I agree with 2^24, that seems to be as much as the eye can distinguish.

[C]
Which doesn't mean that reality is so limited. Note that some animals see better than humans, which isn't relevant either.

[Me]
There's a difference between colours as measured by a spectrometer and colours as perceived by a human. Eg, there is no such colour as "brown" in the spectrum. Or "pink". Or "grey". Or etc.

The 2^24 number of colours are the combinations of colour data used to display colours on a screen. Whether there are actually that many colours displayable on a given screen is another issue: screens vary quite a bit in quality, though much less nowadays than they did in the Olden Days. And whether a human can distinguish them all is another issue. And whether they can replicate natural colours in all weathers is another issue again. As anyone who's tried to make a photo "look right" knows.

As for "see better", that's not a clear concept either.

When it comes to perception, the only thing we can objectively measure or observe is what colour (or other sensory) differences the animal can distinguish. While it's true that bees can distinguish ultraviolet wavelengths, that doesn't mean they "see better". They see well enough for their survival, and that's what counts.

Or take frogs. Judging by their behaviour, they can't see fly-sized blobs unless those blobs move. I surmise that's similar to human peripheral vision, which is much better at distinguishing moving blobs of light than still ones.

Bottom line: what's "out there" isn't what we think it is.

David Feldman. When Do Fish Sleep? (1989) Second in Feldman’s series of “imponderables”, which attempt to answer those nagging questions that  our high school classes didn’t cover. Such as the title question. Do fish sleep? Well, they do exhibit episodes of near-zero activity, which I suppose could be seen as sleep. Wrasses cover themselves in a thick blanket of mucus, not to keep warm, but to obliterate their odour, which would attract predators.
     A nicely done potato chip book, with an index, which makes it a useful reference for the times when you can’t be bothered to start up your device and search online. Online searching for fishes’ sleep patterns offers so many hits that deciding which one to open may be more trouble than opening the index in this book and finding the answer on page 161 to 162.
     I like these books (and many others like them, for example the urban legend compendiums), hence ***

ETs as they could be

     Terence Dickinson (text) & Adolf Schaller (original illustrations).  Extraterrestrials (1994). An essay in controlled imagination.  Dickinson and Schaller begin with fictional ETs, then survey the Universe as we know it. Then they discuss evolutionary pressures which (probably) constrain the forms and functions of organisms. Finally, they speculate how ETs may appear if these evolutionary constraints work as expected. The book is handsome, pithy, and inspiring. Recently, SF movies have gone a step or two beyond the bug-eyed variants of human forms of Star Wars and Star Trek. I think this book and similar exercises in speculative imagining have had an good effect.
     The cover shows a half-kilometre long aerial whale swimming through the dense atmosphere of a gas giant like Jupiter. Symbiotic “crabs” living on and in the creature provide the manual dexterity needed to build cities and space-craft. ***

Genetically modified organisms

This is not an easy topic. Most of us misunderstand and very few of us know enough to grasp what genetic modification actually is. This includes the people who do it, who discover repeatedly that they were mistaken about some expected result. Genetics itself has changed enormously in the last couple of decades or so. What most people think of as genetic modification is simply not what it is. In addition, one of the first successful GMOs was designed to improve corporate profits, with improved crop yields as a side effect. This has raised suspicions about the motives the gene modifiers.

I’ll give my current understanding of GMOs, with two warnings: first, the following is inevitably incomplete and certainly wrong or misleading in several places. Second, the news about genetics is changing very rapidly.

Two very basic and fundamental points:
A, The genome (the collection of genes on all the chromosomes) is not like a blueprint. A much better metaphor is “recipe” or “program”. Like any program, different parts of the code are running at any given time. That’s why we have skin cells, and muscle cells, and liver cells, and brain cells, and so on, all of which contain the complete genome. That’s why a scratch or cut heals: the genes that promote skin cell growth and migration to heal the cut are normally inactive. That’s why we are awake or asleep: genes in neurons turn on and off, the neurons function differently, and we sleep or wake up. We say a gene is “expressed” when it’s doing its work.

B, Genetic modification happens all the time. New varieties and species all arise from genetic modification that’s passed on from one generation to the next. However, a large chunk of the genome does not change: natural selection preserves genes that necessary for life and reproduction. That’s why we share about 20% of our genome with snails. Natural selection ignores genes that have no net effect one way or the other; however, “genetic drift” may change the frequency of these genes. That’s a major reason that people from different parts of the world look different.

We humans have used selective breeding to concentrate genetic variations to suit ourselves.. This method gave us wheat, corn, potatoes, tomatoes, and so on. As well as a huge variety of dogs, cows that produce gallons of milk, woolly sheep, gentle buffaloes, and so on. Whenever you breed for some desirable trait, you also breed for other traits, some of which may be undesirable (think tough, bruise-resistant tomatoes with no taste, or roses lacking fragrance). Some selective breeding has resulted in infertile plants (bananas), or plants that need human help to breed (corn).

Selective breeding is possible because of the following mechanisms of genetic modification.

1) Recombination. The prime mode of modification from one generation to the next, and the reason none of us is a clone of our parents. Prime example: Apples. They don’t breed true. All of the delicious varieties we enjoy are the result of recombination. The only way to propagate these varieties is by cloning (grafting from one tree to another). If the chain of cloning breaks, that variety of apple disappears.

2) Hybridisation, also known as crossing. Easy with varieties of the same species, more difficult with related species. Easier with plants than with animals. It happens spontaneously, especially among microbes. Some hybrids between related species are fertile, which raises the question of whether they are new species, and whether the related species are really different species. "Species" is a fuzzy concept.

3) Mutation. Most mutations are repaired as they happen, others kill the cells in which they happen, the rest survive. If a surviving mutation is in an egg or a sperm, it may be passed on to the next generation, in which case it may spread through the species and modify it. Hairless cats are an example.

4) Gene exchange. This happens directly among bacteria, even across species, and is the reason that resistance to antibiotics has spread faster than originally estimated. It’s also the reason bacteria can be used to produce useful materials. It also happens with plants, and occasionally with vertebrates that breed externally, such as fish. Some plants even require “foreign” pollen to reproduce (currants, for example).

5) Polyploidy: more than two sets of chromosomes. Most common among plants (estimates range from 30 to 80% of all plant species). It’s possible to manipulate the process, and so produce new varieties of plants.

6) Methylation: during the organism’s life, methyl groups are attached to the genome, for many different reasons. This affects the gene expression. Methylation happens in all organs, including reproductive organs, which means it can affect gene expression for at least the next generation.

7) Viral or bacterial infections which alter the genome. Prime example: tulips. Viral infection of the bulb affects the colour, shape, etc of the of bloom. It does not affect the seed, which means that the only way to propagate such varieties is by cloning them. Viral infections work by inserting genes into the host DNA, so that the infected cell then produces viruses.

8) Artificial gene modification. Humans have been doing this as long as they’ve been human, through selective breeding. Later, humans discovered cloning (grafting), which led to plants that cannot propagate on their own (seedless watermelons, bananas).
     What’s new is the ability to use some of the natural processes that change DNA. In particular, enzymes that bacteria and viruses use to replace bits of host DNA with the infector’s DNA can be used to insert or replace genes that are useful from our point of view. The most recent method of altering DNA is CRISPR, a method to edit DNA directly, in order add, delete, or replace a gene.

But it’s not easy. Any change to DNA may have unexpected effects. Manipulating the genomes of bacteria is easiest: they are naturally prolific adapters of foreign genes. It’s more difficult with plants, and most difficult with animals. In general, it’s easy to replace a gene, more difficult to insert one. Removing a gene is easy enough: it’s been done with selective breeding of lab mice.

Replacing genes is the basis of gene therapy, which has had some small success. Exchanging genes from the same species is a good way to produce new varieties. Selective breeding is the slow way; CRISPR is quicker.

Inserting genes is difficult because the gene may not even work, let alone work as desired. The success of doing this is highest with bacteria, which do it naturally, and with abandon. For example, there are some bacteria that can eat some plastics. Would be nice to grow a bacterium that needs some specialised environment in a vat, dump in the plastic, and drain off the waste.

Editing the genome, by replacing one version of a gene with another version, turns out to be relatively easy. It’s also hugely successful: after all, a different version of the same gene will usually be expressed just like the one you replaced. The genes for blue eyes and brown eyes are simply different versions of the same genes.

An important fact is that related species share most of their genes. How much do they share? That depends on how closely related they are. We are more closely related to horses than to snails, so we share more genes with horses than with snails. But we are more closely related to snails than to roses, so we share more genes with snails than with roses. Sharing genes with other organisms makes gene exchange possible.

But it’s not really that simple. Just because we share certain genes doesn’t mean that they work exactly the same way. The gene’s environment affects gene expression. Which genes, when, and to what effect, all depend on the gene’s environment. That environment operates over several systems: , first, the cell itself, ie, which other genes are working in that cell. Then the organism itself, ie, which organ the cell is part of. Then the physical environment of the organism, ie, temperature, food, and so on. Finally, other organisms, ie, mates, predators, food sources, and so on. Pretty complicated, really.

And that’s why genetic modification, by any method, is more art than science, and results in more failures than successes.

Nevertheless, we humans have been doing it as much as possible for a long time. The newest insights into how genes work and how to change the genome have merely made the process quicker, and a little more certain.

Revised 2019/03/21

Animal emotions

The problem with anthropomorphising isn't that we ascribe emotions to other animals. It's that too often we imagine those emotions to be the same as ours. They aren't, and they can't be. Animals' sensory apparatus is different from ours, so their experience and their awareness of the world is different from ours.

Their self-awareness is also different, and varies from one lineage to another. Feeling pain isn't the same as knowing you are feeling pain. Even humans can train themselves not to know they are feeling pain. It's one of the methods of controlling pain.

Does that mean that animals lack emotional lives? Of course not. Their emotions are as complex as they can possibly be, and that fact is enough to force an ethical/moral choice on us: do we ignore their sentience, or do we accept and honour it, doing our best to treat them as fellow creatures? Keep in mind that animals kill animals, and that this killing is usually not nearly as humane as that which we inflict on the animals we eat.

Respect for other animals is not the same as treating them as fellow-humans. As far as we can tell, we have a more deliberative morality than other animals do. Since we have that gift, we must exercise it. The fact that we too often don't even deal with humans as we should doesn't diminish that moral imperative.

Nor does it change the inescapable fact that all lives will end. While we enjoy our lives, we should do our best to enrich the lives of all other sentient beings that we encounter.

   
Posted in NYT 2019-02-25 as comment to:

https://www.nytimes.com/2019/02/25/books/review/frans-de-waal-mamas-last-hug.html

The body's afterlife: Stiff by Mary Roach

     Mary Roach. Stiff (2003) Roach writes about the afterlife of cadavers, from providing organs for transplant to testing the effects of bullets to giving medical students understanding of human anatomy to uses you would never have thought of yourself. She writes well, has a nice sense of humour, and demonstrates a good deal less squeamishness than most of her readers. Highly recommended. ****

Accidentals and Essentials: Experience and Reality

Observation and Theory, Experience and

Imagination: What’s Real and What Isn’t

1.0
We experience things and processes, events and spaces, times and moments, extended sequences of events, and so on. We may name (or label) any such experience, and having done so, we tend to think of it as a unified experience, whatever its extent in space and time. Naming is the first step to theory, the precondition of explanation.

2.0
2.1 The things we experience are bundles of sensory inputs. They may be relatively simple bundles, such as the ones that we label “apple”; or complex, hierarchically layered bundles, such as “song”; or more complex networks of experiences such as “fair play”; and so on. But all experiences which we perceive or apprehend as having some kind of unity in space and time can be reduced to a bundle of sensations.

2.2 The “unity in space and time” seems to be a given. Neuro-psychological research indicates that it’s a product of the brain’s processing of sensory inputs. Comparing human and other animals’ perceptions clarifies that insight: a frog responds to a fly-sized object such as a raisin only when it moves. But when it moves, the frog will try to catch and eat it, even when it’s a raisin.

3.0
3.1 We learn in grammar class that nouns name essentials (apple, kitten, rainstorm, triangle) while adjectives name accidentals (red, soft, greasy, warm, loud, sharp, salty, etc). The trick seems to be to recognise what makes an apple an apple and not a kitten; and what features of an apple can vary without destroying its appleness. But these distinctions are illusory, since any description of the essence of an apple is merely a list of accidentals, its so-called properties. Botanical classification makes that quite clear. We may infer that “apple” is a the minimal collection of accidentals that differentiates it from pear, cherry, raspberry, peach, mango, .... Note that the properties overlap: it’s the differences between the lists that differentiate the fruits.

3.2 We can also differentiate objects by abstract qualities, such animate/inanimate, food/non-food, etc. Anthropologists have discovered that there are no universal classification systems. While there is little doubt that we perceive objects as more or less stable collections of sensations, that does not entail that we classify them that way. Apparently humans have a penchant for believing that whatever they name is real. So when we name some aspect of human behaviour as “just”, we start collecting the properties of Justice, and arguing with other people about which of these aspects are accidental or essential. Thus the white wig and black robe of a British judge are accidentals. But is the British Common Law a better system for arriving at just judgments than the European Roman Law? Any argument pro or con will rely on explicit and implict assumptions about the essence of Justice.
 

4.0
4.1 The brain combines sensory inputs into experiences. Some of these combinations are built-in, so much so that the brain organises different sensory inputs into the correct temporal sequence even though the processing time of the inputs varies so much that the results are in not in the correct sequence. When the brain fails to produce the correct image of the reality mediated by senses, its possessor is more or less deluded. If he knows it, he may well be more disturbed by that knowledge than by the failure to parse reality correctly.

4.2 Some of these combinations are inherently incorrect: we call them “illusions”, and the essential (;-)) point is that knowing we perceive an illusion does not cancel it. Nor does the fact that we have acquired  many, perhaps most, of these illusory parsings during the development of the visual cortex after birth.

How the other animals live

 

 Pat Senson. Nasty, Brutish and Short (2010) A compilation of oddball facts about animals as recounted on Quirks and Quarks, CBC radio’s science news show. It demonstrates that no matter how sure we are that we know what’s natural and what isn’t, Mother Nature has a habit of confounding our prejudices. What’s refreshing, compared to TV, is the willingness to admit that just why animals do some of the weird things they do isn’t understood. There are a few attempts at just-so stories, mostly in terms of probable odds of survival, but without more data, most of these remain merely interesting speculation.
     I learned a lot, but very little of it has stuck. A random dive into the book reveals that alligators can move their internal airbag around, which shifts the centre of gravity, and so enables silent, almost ripple-free diving and surfacing. Which is why alligators are more dangerous than crocodiles, who have to use their feet and tails to do that, and so tend to announce their presence in the water. Or maybe alligators’ sneakiness just makes them seem more dangerous.
     A nice potato chip book which should please anybody who wants to know weird stuff about critters. Senson finishes off every mini-essay with a lame joke, which I found somewhat irritating, and costs the book ½ a star. You can find Quirks and Quarks podcasts here.**½

Update 2023-03-20: The painting is The Peaceable Kingdom, by  Edward Hicks.

Smarter than an octopus? Maybe not.

Recent dicussion on a Usenet group about a picture of octopuses "researching" a human diver prompted a search. Cephalopods are smart. See So You Think You're Smarter Than a Cephalopod? from the Smithsonian website.

Food matters

     Seeds of Time (2013) Documentary that follows Cary Fowler as he travels round the world  as part of a world-wide seed-saving project. He was one of the instigators of the Svalbard Seed Vault. His message is simple: industrialised agriculture has brought about a sharp decline in crop diversity just when climate change has raised the need for genetic diversity so that crops can be adapted to changing conditions. Besides Svalbard, a project to preserve potato diversity in Peru gets central billing. There are also scenes of conferences, graphics illustrating the loss of seed banks, and so on. This is one of those slow-moving crises that people will ignore until it’s too late.
      Besides the Peruvian potato saving project, the film includes examples of seed saving by gardeners and other projects designed to preserve and increase diversity. Some of the repetitive bits could have been cut to provide more room for gardening, which in pure energy terms is the most efficient method of growing food.
     Unlike industrialised agriculture, a garden multiplies energy. The efficiency of agribusiness is an illusion limited to money. In terms of resources, it’s highly inefficient, because the externals aren’t priced. Gardening is labour intensive, but we get more food energy out of a garden than we put into it. Good thing too, or our ancestors, couldn’t have survived without preserving garden produce for the long cold winter. We subsidise agri-business by underpricing oil, which means we exchange the future of the planet for the present freedom from labour.
     A film both depressing and hopeful, relentlessly earnest, but necessary. Watch ity, and grow beans in your backyard. ***

Cells are computers, organisms are fractals

     Cells are computers, organisms are fractals

Some notes towards a concept. I’ve long thought that the notion that a neuron as an on-off switch was too simplistic. These notes represent an attempt to produce a better notion. 2016-06-03 & 05. WEK.

The metaphor of DNA as blueprint is misleading. Better: DNA is a program guiding the assembly of proteins. Better yet: It’s the operating system, since it’s RNA that produces the proteins. But if DNA is a program, then the question is, How does it execute? The answer: like any program, at any given time some part is running, the other parts are silent. A program can also trigger other programs. The operating system controls how multiple programs run, it allocates memory and CPU time, access to video and audio subsystems etc. A “call” from one program will stop or start some part of another program. An “interrupt” will cause (re-)allocation of memory, access to subsystems, etc. DNA starts and stops protein synthesis, turns genes on and off, analogous to OS controlling program execution. So the cell is a computer

Recent research shows that inputs to the cell “turn genes on and off”, analogous to calls and interrupts controlling how a program runs. The genes control the functioning of the cell. Exactly how is complicated, but the general pattern is chemical feedback loops. A substance increases, which triggers or stops gene expression, which results in a series of reactions, which cause that substance to decrease, which stops or triggers gene expression, and the cycle repeats.

A neuron responds to the chemical environment outside it by adjusting its internal processes. These processes control gene expression. The feedback loops within the neuron determine the types and quantity of neurotransmitters emitted at the synapse with the next neuron in the circuit. Since both type and quantity of neurotransmitter vary depending on the inputs to the neuron, the neuron is computing the output. The concept of a neuron as simple on-off switch is inadequate.

But a cell is an odd kind of computer. The relation between input and output depends on the internal feedback loops. A given substance may be implicated in two or more feedback loops, which means that the neuron is topologically a net. The computation of the output depends on the topology of the net of chemical reactions, which happen both simultaneously and in sequence. That makes the cell a parallel computer.

More precisely, the cell is a net whose topology varies over time as the chemical feedback loops cycle between limiting states and intersect with each other. Thus, the cell cycles through a series of topologies. It’s a self-modifying net.

The concept of a self-modifying net applies to assemblies of cells (tissues), to organs, and to the organism as whole. The organism too is a complex system of feedback loops. Mathematically it’s a chaotic system: it tends to maintain itself within an envelope of states (the attractors). Illness and disease move the system outside the envelope, and recuperation is a return of the system to the dynamically stable cycles within the envelope.

Conclusion: An organism is a multi-dimensional net of feedback loops. Its topology varies over time at many scales, which implies it’s a fractal system.

Scientific ideas we should forget

 

    John Brockman, ed. This Idea Must Die (2015) A compilation of answers to the question, “What scientific idea is ready for retirement?”, posed on https://www.edge.org/ in 2014. Brockman arranges the answers, starting with general ones, then roughly by topic, such as quantum physics, neurology, evolution, etc, and ending with math and statistics. Often, a short sequence of essays reads like a dialogue.

     Most answers are directed at a general audience, which of course includes scientists in other fields. The writers try to explicate how the target concept causes mistakes or worse, what a better understanding would look like, and sometimes what concept should replace the target. A handful read like part of an ongoing dispute between the writer and the other specialists in the field.

     I was pleased to see that many of my objections, puzzlements, and exasperations were confirmed or clarified in these essays. One of these is the wave-particle duality interpretation of some experiments in quantum physics, which I think is a holdover from the days when observations and models made a nice clean distinction between things that rippled through, and things that bumped into, each other. QM equations show that this distinction isn’t much use. It’s nonsense to say that entities are both waves and particles. It would be like arguing that because people sometimes exhibit fear and at other times exhibit joy, that human beings are somehow both fearful and joyful all at once.

     Another of my annoyances is Schrödinger’s Cat. I’m glad to see that Freeman Dyson notes that the wave function isn’t a thing, so it doesn’t collapse. It’s statement of probabilities in some specific context. (Or conversely, it’s a context defined by a distribution of probabilities). An observation measures one of the probable states. At another time, another state will be observed. To argue that somehow all probable states exist at once is like arguing that because Jack is sometimes angry and sometimes happy when he goes to a baseball game, that therefore Jack is both angry and happy until he goes to the game.

     I found some of the best entertainment in the essays dealing with psychology. One writer attacks a concept, another assumes that same concept in order to attack another one. So what’s an non-expert to do?

     However, the overall effect of reading these essays is the somewhat depressing reminder that we all hold erroneous or misunderstood scientific ideas. They appear in news reports and TV punditry hourly, and many of them have very bad effects on public understanding and thereby on public opinion, which in turn limits politicians’ beliefs about what can and should be done.

     Misunderstanding of basic math is nowhere more obvious than in news about statistics. Case in point: This morning, I heard a report on rising rates of STDs in Alberta, a roughly 40% increase overall in the last ten years, with the highest rate increases among the young and the old, and the lowest among the middle aged. Well, without the actual numbers, rate increases are pretty well meaningless. An increase of, say, from 10 to 20 per 10,000 young would be a 100% increase, while from from 100 to 150 per 10,000 middle-aged people would be only a 50% increase. 50% sounds a lot better than 100%, right? But in this example, 50% is worse, since 50 extra cases will cost five times as much as 10 extra cases.

     The final essay, by Paul Saffo, reminds the reader that the more we know, the more unknowns we encounter. Saffo refers to Teilhard de Chardin’s noosphere, the sphere of knowledge. As it expands into the unknown, its surface increases, the contact between known and unknown increases. I developed this idea on my own many years ago, when I thought of the known as an expanding circle. 2D instead of 3D, but otherwise the same. Either way, there will never be an end to the questions we can ask. Even better, there will always be more questions to ask than have already been answered. But Socrates said as much 2,500 years ago. History echoes.

     Highly recommended, as is the website. ****

Alan Weisman. The World Without Us (2007)

     Alan Weisman. The World Without Us (2007) Suppose every human being would disappear from the face of the Earth? Maybe in a moment, maybe over a few hours or days, but complete disappearance. What would happen to the Earth and the traces of human occupation?
     That’s the thought experiment Weisman runs in this book. He begins by considering how the natural world would take over from us, by rotting and crumbling our homes, our subways, our roads,  and so on. He deals with the effects of our industrial legacy, and considers how the artificial chemicals we’ve dumped into the biosphere might influence future evolution. Finally, he talks about what may remain of our works of the mind the imagination.
     The answers are sobering. Natural processes begin to destroy our artefacts as soon as we stop maintaining them. Subways will flood. Houses will rot away. Bridges will sag and fall. The foundation of skyscrapers will rust, the buildings will lean and then fall. Trees, vines, grasses will grow in and on our works and will crack and split and crumble them. Our corpses will decay, although some of their containers will survive a few hundred years or so. Highly stable molecules will be recycled through the biosphere until some microbes evolve to eat them. Plastics will degrade into flakes, then into nanometre particles, by which time something may have learned how to extract the energy locked up in those molecules. Ceramic tile and pottery will survive thousands of years until geologic processes bury and metamorphose them.
     And Pioneer I and II, and Voyager 1 and 2, and assorted other probes will drift through space and may at some time fetch up in a star system. But the odds that any sentient, intelligent life form will find and decode their significance is vanishingly small.
     Well then, what, if any, traces of our existence will survive us, and for how long? The answer is, lots, but not what you expected. Plastics, ceramics, earthworks and radioactive trash will survive the longest on Earth. The space probes and radio waves will survive longest of all, drifting through space until space dust abrades the probes and radio waves attenuate so much that they can no longer be distinguished from background radiation.
     The subtext of this book is anther question: Can we survive our own successes? Technology is gift that we’ve used to procreate excessively and mine the riches of the planet. Doing that, we’ve changed it, and it will never revert to its pre-human state. In this, we are like all other successful top-level predators. But like any other creature, we will eventually become extinct, either by making our habitat lethal to ourselves, or by evolving into something else. Kurt Vonnegut imagined the latter scenario in Galapagos. Weisman’s book implies that if we don’t do something to at least partly reverse our reconstruction of Earth, a few of us may survive when the inevitable collapse occurs, and those few will become one among many species competing to survive on a planet that begins to reclaim its own. Our continued success is not guaranteed.
     Even if we manage to stumble and muddle our way through the catastrophe that’s already moving through the biosphere, eventually the Sun will destroy us. Weisman doesn’t mention the hope that others have expressed, that homo sapiens terrestris may become homo sapiens stellaris, but even if that remote possibility becomes reality, the Earth and humans as we know them will have ceased to exist.
     An oddly exhilarating book, despite the depressing and gloomy forecasts and implications. Read it. ****

Dan Riskin. Mother Nature is Trying to Kill You (2014)

     Dan Riskin. Mother Nature is Trying to Kill You (2014) One of those popular science books that not only tells you lots of cool stuff, but changes the way you look at the world around you. Riskin takes us back to basics: Nature really is red in tooth and claw, and we’d better not forget it. He demonstrates this thesis under the headings of six of the seven deadly sins, carefully including human examples as well. We are animals, we must eat other living things to survive, and like them we want to maximise the odds that our DNA will be passed on by the next generation. Quoting Dawkins brilliant insight, Riskin reminds us that we are machines whose function is to ensure the survival of the DNA that constructs us.
    So what does it matter that we experience love and kindness and joy, and yearn for justice and truth and beauty? These emotions are merely part of the mechanism that guarantees that we will make babies, along with the other emotions that guarantee that we will try to survive long enough to make sure our babies can make babies too.
     That’s the bleak vision Riskin arrives at when he gets to pride, which is a peculiarly human sin. It makes us oblivious of our connection to and participation in the natural world of competition for every possible scrap of advantage. But turn this pride inside out: Instead of being proud of ability to change other creatures to our advantage, we should be proud of our ability to change ourselves to our advantage. We are capable of doing something that other animals can’t do, which is to plan for the long-range future, and curb and redirect those behaviours that give us immediate, short-term advantages over each other and other animals. That, says Riskin, is something to be proud of. We can refuse to be slaves to our DNA.  Evolution produced us, but it also made us capable of defying its process. Or more humbly, to take advantage of its processes to enable the survival of our DNA not only in the next generation, but in the  generations after that. With luck and savvy, and a huge dollop of rethinking of our purposes, maybe for thousands of generations into the future.
     A book worth reading on many levels. Riskin has a sense of humour, he writes well, and he knows how to present examples that not only teach but also entertain. ***