The not-so-silent seas

 kw: book reviews, nonfiction, science, oceanography, acoustics, bioacoustics, sound, noise pollution

A number of years ago at the beach at Cape Henlopen, Delaware, a pod of porpoises came by, a hundred yards or so offshore, as they usually do in the afternoon. This particular day a couple of busloads of Amish people from the Lancaster, PA area had been brought for a day at the beach, and I was standing about chest-deep in the water among a dozen or so Amish teenagers. As I like to do when the porpoises swim by, I ducked my head under water to listen to them whistle and chirp. It is a sound I love. I liken it to the social honking of a V of geese flying overhead.

I said to the nearest Amish boy, "Try putting your head under water. You'll hear the porpoises." He tried it, and then shouted something in German to the other kids. Soon they all were bobbing up and down and chattering among themselves about this novel experience.

As a teen I often watched the Flipper TV show, centered on a bottlenose dolphin (the "poster child" of porpoises). I was familiar with the chatty noises the animal could make. A few years later I was enthralled to listen to the album Songs of the Humpback Whale. As an avid reader of science articles and books, I've kept up in a general way with the findings of bioacoustics about the whole range of animals that make sounds under water, from snapping shrimp and mantis shrimp to the fish called Grunts—and many others that do more than grunt—to the mammals, particularly whales (I count porpoises as small whales).

The title Sing Like a Fish: How Sound Rules Life Under Water was a slam-dunk for me. The reading was as enjoyable as I'd anticipated. The author, Amorina Kingdon, muses in the Epilog whether it was worthwhile to devote two years of her life to the book and its research. She concludes a resounding Yes, and I agree. Who else could do this? Another might write on the same subject, but Ms Kingdon's voice is unique: heartfelt, lyrical and eloquent.

Early in the book we learn why we've ignored the underwater soundscape for so long. Our ears don't hear that well under water. In the age of sail, many sounds were heard by sailors trying to sleep below decks. When there is little wind, a sailing ship is so silent, the sounds of the sea that make their way through the wooden hull are quite evident. These days, professional sailors would be hard pressed to hear anything coming through the hull of a noisy, engine-driven ship. Those who never go to sea, who experience it only from above, have no idea how sound-filled it is. Early SCUBA divers, with Jacques Cousteau in the lead, hampered by air-adapted ears and the noisy SCUBA apparatus, heard so little that they produced a documentary film about the ocean titled The Silent World, about ten years before the first episode of Flipper aired. As I recall, the main sound heard under water in that film is the noise of the SCUBA. I wonder if Cousteau ever learned that fish have songs.

Although I wanted to learn SCUBA diving, I wasn't willing to pony up for expensive diving lessons and equipment. I snorkeled instead; I could surface dive to 40 feet without much trouble, and once went 60 feet. Snorkeling can also be noisy if you never leave the surface; we breathe rather loudly. But if you pop a surface dive down even 10 feet and just hang there, gradually the sounds will become evident. In my case, though, I dove offshore of tide pools, to see what animals were on the rocks. Most of the sound was wave noise, but I did hear a little of the fishy chorus around me: clicks, squeaks, and mournful groans. Better equipment has helped us realize that fish sing! Not just whales.

Once the hydrophone was invented, the soundscapes of the seas came into sharper focus (Hmm, bit of a mixed metaphor there; I guess you can figure it out anyway). Much of the book is devoted to surveying the breadth of underwater animal species that detect sound, hear sound (different senses), and communicate using sound. In one place it is stated that a catalog of fish sounds contained around 900 species. Compare that to the 94 species of cetaceans (whales of all varieties), all of which can vocalize. Though there are about 34,000 species of fish, the 900 "cataloged" to be vocal simply reflects the very early stage of "auditioning" the world's census of fish. I don't recall reading about any fish that were tested, that they were unconditionally silent, so perhaps I can fairly conclude that most, or nearly all, fish will be found to not just receive sound but to use it.

Certain invertebrates also make sounds intentionally. Snapping shrimp and mantis shrimp make noises loud enough to be weapons, though a mantis shrimp mainly relies on the fastest punch in the animal kingdom as its primary weapon. Considering the wide range of insects that make noises to communicate and court, it's reasonable to assume that many of the active invertebrates also use sound. I immediately thought of scallops, which make a clapping sound when fleeing danger, but in their case I think the sound is incidental to the "jet propulsion" their clapping produces.

Sadly, there is a new player on the soundscape. Us. Ship engines are noisy. The propellers ("screws") are noisier. Sonar is noisy. Seismic surveying is incredibly noisy. The racket of pile driving to install offshore wind turbines drives whales and fish crazy and can kill them. The low rumble of the turbines once they are operating is a chronic noise that drives migrating animals to change migration routes, and hinders the feeding activities of many animals that need to hear their prey. So does the persistent growl of ships' propellers and the hammering of depth-finding Sonar. A couple of chapters are devoted to describing all the problems that sea animals are having with the sounds we make while we use the oceans for commerce and entertainment.

The book ends on a hopeful note regarding the confluence of regulation and public attitudes that can result from wise use of scientific data being collected right now. We know we can't protect everything, but if we know certain areas that are most sensitive—such as a special bay where certain whales raise their calves—we can focus our efforts where they are more effective.

Just in case you're wondering: This sonogram illustrates why we call the sounds made by humpback whales "songs":

For reference, middle C on a piano has a frequency of 261 Hz. 200 on these diagrams would then be near the G below middle C, and it happens to be the natural frequency of my speaking voice. To sing along with this whale, just follow the lowest, darkest line of each group. The highest blip on the second track (~700 Hz) is almost an octave higher than the highest note I can sing, which is an A with a frequency of 440 Hz. Most women can just reach the next A at 880 Hz, so a woman can sing with this whale, but not even a low-voiced man can reach the low tones near 50 Hz seen in much of the second track. This whale has a very wide vocal range!

But why are these a song rather than tuneless noises such as some people make when concentrating on whittling or something similar? In a word, structure. Phrases and shorter elements (words?) repeat and are sometimes repeated with variations. There is something intentional going on. One verse of a typical popular (human) song lasts from half a minute to a minute. Most song tracks on your playlist are 3-4 minutes in length. A typical section (verse?) of a humpback song lasts a couple of minutes, and such verses are grouped into soliloquies lasting on average 8 minutes, but the whale may sing the song, over and over again, with variations, for an hour, or even a day. Maybe a whale is a philosopher, and this is his way (only males sing) of thinking out loud. Or maybe these are courting songs, which the whale will repeat until a female responds, perhaps from miles away, and joins him.

A book like this reminds us of what we don't know, and hints at the level of effort we'll need to exert to find out what the natural world contains, while it is still there. That's the author's aim. The fish are singing, for their own reasons. But now we are able to hear. Will we value their songs enough to preserve them, not just as recordings, but by preserving the singers?

More Octo-fun

 kw: book reviews, nonfiction, zoology, cephalopods, octopus, octopuses

Almost a year ago I reviewed Soul of an Octopus by Sy Montgomery. She has followed up with a delightful, small book Secrets of the Octopus. Even more than the prior book, this one is replete with amazing pictures of these astounding creatures. The core of Soul is the relationship Dr. Montgomery had with four Giant Pacific Octopus individuals, during the short time (just a few years) that each resided in the aquarium at Monterey Bay. In Secrets we find a number of newer discoveries about octopuses.

At present we know of about 300 species of octopus. The largest is the Giant Pacific Octopus, Enteroctopus dofleini, which can reach twice the size of a man and weigh between 100-250 pounds. The first octopus I saw was one of these, at Marineland of the Pacific, when it was still open. I was about ten years old. The large female was plastered to the glass, and I had to look in from the side to see her mantle (which many people mistake for the head; it is behind the head).

I remember at the time being told that red color for an octopus meant anger, but that is wrong. It means interest or excitement. An angry octopus will instead blacken, particularly when it rises up to intimidate an opponent. The animal in this photo is excited from interacting with the diver. Many species of octopus quickly learn to enjoy human company.

Octopuses are cephalopods, the "brainy" order of mollusks, which also includes squids, cuttlefish, argonauts (which produce lovely, featherweight shells), nautiluses (with coiled, heavier shells), and sepiolids (often called "dumbo octopuses"). All cephalopods have arms, which most people call "tentacles", but to a biologist, the tentacles are the two long, extensible members that shoot out to capture prey, and only have suckers at their ends, the part often called a club. Arms typically have suckers all long their length. Also, all cephalopods have color-shifting skin, and many have skin that can dramatically change shape. Almost any octopus can mimic a rock or patch of seaweed in both color and shape.

The smallest octopus is the Hairy Octopus, which was discovered only a couple of years ago. It is so new a scientific binomial name hasn't been chosen yet. These lovely little critters, only 5 cm long (2 inches, or the size of a large paper clip), exhibit the shape-shifting skill almost all the time, looking mostly like drifting bits of seaweed. Depending on the screen you are using, this picture is probably twice as large as the actual animal.

It was once thought that octopuses are strictly solitary, only meeting to mate or fight or eat one another. This is also out of date. A lot depends on the density or scarcity of food. In abundant circumstances, some (perhaps many) species can be quite social, as seen with a few "octo-cities" such as Octopolis near Australia. While no large settlements of Giant Pacific Octopuses are known, their apparent enjoyment of human association indicates that they also can be quite sociable.

Some octopuses use tools. The Coconut Octopus, Amphioctopus marginatus, is just the right size to fit into a coconut shell. When an individual finds either a coconut shell portion (or two), or a similarly-sized shell of a clam or scallop, it will typically begin to carry it around to use as an impromptu shelter. This is a good strategy for an orange-sized, tasty morsel in an ocean full of predators.

This species is also one that "walks". Holding a shell with up to six arms, it uses two to stride along the ocean floor like a bellhop with a heavy suitcase. This image is two clips from a video of an octopus that wraps six arms around its body while walking on the other two. Starting about 10 seconds into this video, we see another species "stand up and walk away" from the photographer.

This is the video link, in case the one above doesn't work right: https://www.youtube.com/watch?v=kHwUW1inDCs.

These are just a few of the recent learnings about various species of octopus. The last part of the book, "Octoprofiles" by Warren K. Carlyle IV, presents brief descriptions of sixteen cephalopod species to give us a taste of their variety. Reading this book and gazing at the terrific pictures is pure enjoyment.

If the AI can't see you, do you exist?

 kw: book reviews, nonfiction, artificial intelligence, artificial vision, face recognition systems, activism, memoirs

One could say it all started with a Halloween mask. One could also say it started with a vision system that couldn't see. Graduate student Joy Buolamwini was coding a project she calls Aspire Mirror, using some off-the-shelf face recognition software, but it couldn't detect her face. She had recently bought a white costume mask for a Halloween event; on a whim she put it on. Lo and behold! The system detected the mask as a face, right away.

Dr. Buolamwini's parents are from Ghana, so she isn't just "Black", she's darker skinned than many Afro-Americans. The software she used for the Aspire Mirror prototype isn't the only one that is blind to her face. Most such software is "Black blind", and many vision systems make many more recognition errors with Black faces than with White ones. Later in her career, when she and colleagues tested major vision systems, they showed an almost perfect correlation between accuracy and paleness of skin. 

As she describes in her book Unmasking AI: My Mission to Protect What is Human in a World of Machines, one major company's software achieved 100% accuracy of both recognition (distinguishing persons who look similar) and verification (admitting only the correct person to their phone, for example) for White male faces only. Other major brands achieved accuracy exceeding 85% or 90%, again for White faces only, and also, better accuracy for men than women. For all of them, the darker the skin, the lower the accuracy of both kinds, and the lowest accuracy is for Black women.

As Big Data has morphed into Large Language Models and Large Image Models (LLM and LIM, respectively), their identification as AI has been cemented in the popular (and press) imagination. Personally, I dislike the term "Artificial Intelligence" when used for such systems. I prefer SI, "Simulated Intelligence". Weaselly terms such as ANI (Artificial Narrow Intelligence) still don't go far enough to distance SI software from natural (i.e., evolved) intelligence. Genuine AGI (Artificial General Intelligence), if it is possible, would be deserving of the raw moniker without the qualifier: AI.

Face recognition is something all animals with vision can accomplish. Of course, various species do better at recognizing their own species. Even insects, with a very different vision system than our own, can recognize one human from another, favoring a familiar face (if it belongs to someone who didn't try to kill them on sight). I saw this when we had a large (basketball size) nest of hornets on a corner of our house. Even in late summer, when hornets get more aggressive, they ignored my wife and me, but would threaten unfamiliar persons; the mail carriers, who change from day to day, were cautioned to avoid that corner of the house. We can conclude that it doesn't take a huge brain to recognize faces reliably.

Machine vision systems have to be trained. So far, it takes a huge "neural network", whether hardware or software based, that has been trained with at least thousands of images of people's faces, to do their job. With millions they do better. The bias problem is with the training data. Dr. Buolamwini found that the standard facial image databases all had more male than female faces, and many more White faces than all others combined. I don't recall much in the way of numbers, but I get the impression that the proportions were "whiter" than the demographics of the American populace. Consider that the major cities of America all have either majority Black populations, or are near-majority Black. That means that automated surveillance systems—for which which most large machine vision systems are obtained—have been trained on a population that they seldom encounter, and have seen too few of their actual "clientele" to be able to reliably recognize them.

The ramifications of this are grave indeed. Scenario: You arrive home to find police or FBI waiting to arrest you. You have been picked out by an AI system as "strongly resembling" a wanted suspect, and a system that was monitoring the several cameras you passed by on your way alerted the authorities of your presence. This has happened to a number of people, not all of them Black, and a few spent hours or days in custody before their actual identity was verified. 

Another scenario: Your company wants to reduce the number of security guards at the gate (I've worked at such secure installations), so they announce that you'll need to look into a camera to get access. If the system being used is no more capable than the one behind Aspire Mirror, and you happen to be Black, it may not even recognize that a face has been presented to it!

Another issue that the author presents, several times: Training images are typically frontal and partial profile photos with good lighting and a neutral background. Nothing like pictures taken "in the wild", such as from a camera at the top of a 20-foot pole on a street corner.

This reminds me of something I'll have to describe, because I can't ethically show the photo here. After a baptism in my back yard, we took a group photo of about 35 of us. We were a good mix of races including two Black families and a few Chinese families; five Caucasians were present (I am in a very multi-ethnic church). It is under a tree, so the lighting is dappled. I did brightness tests of several faces. One White boy's face in a shadowy part of the image is darker than the face of a Black boy in the sunshine. A Black man in the shadow is practically invisible. However, shifting the photo's brightness a little makes that particular Black man easy to see, while washing out all the sunlit faces. Interestingly, Google Photos seems to be pretty good at isolating faces and recognizing them; it recognized every face in the photo, even though it had to ask me to verify some of the identifications. Other face recognition software that I've used don't do quite so well.

This example emphasizes that even a posed group photo can have lighting variations that stretch a vision system (including our own!) to its limits. With such matters as the prime example, the author expands the arena to include automated systems of decision support: Résumés scanned and prioritized before the hiring manager even sees them; street surveillance with automated flagging of "suspicious" persons or behavior; neighborhood analyses that set store prices based on demographics, and similarly for real estate appraisals. All these are actually extensions of things that humans were doing already. The machines just do them faster and more cheaply...and some have been banned as a human activity (real estate redlining, for example), but AI systems are being allowed to slip under the radar.

Only a portion of the book is devoted to such technical matters. Much more involves Dr. Buolamwini's increasing involvement in policy. As she relates, it is not enough to point out the deficiencies of systems that lie behind automated decision making. Their weaknesses reflect and even amplify the weaknesses of the people who create them. Biased people cannot produce unbiased systems (A side thought: Get together several people who each recognize their own bias, and ensure that multiple viewpoints are included, and they have a better chance of reducing the biases of a system they all have a hand in developing and training; this is hard! But it is analogous to the way TCP/IP protocols can transmit data with extraordinary perfection through a noisy network; the Internet would be impossible without it).

Over a rather short span of time, much of it while she was still in graduate school, the author has become a more and more visible presence to policy makers, in her capacity as a founding member of the Algorithmic Justice League and the Poet of Code. In her epilogue she describes a meeting with the President of the U.S., at which he asked, "What should I do?" 

Since this occurred quite recently, it will be left to the next President (and maybe several "nexts") to deal with these matters. Make no mistake: they must be dealt with. This is a bipartisan matter. "Algorithmic harms" know no political party, and oxen all along the political spectrum have been gored. I find it abundantly clear that long before AGI arrives to become just "AI", making all prior systems obsolete, governance systems are required to rein in the big money behind overuse of such tools. We still have a grip on the tail of this tiger, but it is quite capable of spinning 'round for a bite!

The Einstein paradox

 kw: book reviews, nonfiction, biographies, social media, celebrities, albert einstein

I am presently 76 years old, just three months shy of age 77. That is eight months beyond the age at which Albert Einstein died. He passed away 69 years ago, and it seems that he is more famous now than he was during his life. He was not an entertainer, nor a politician, nor anything else we associate with being a celebrity. Celebrities come and go, and most of those who were utterly idolized just a few years ago have been forgotten.

He was famous in Germany for years before he became hated by the Nazis and had to flee to America. He spent his years in America trying to extend his General Theory of Relativity into a Unified Field Theory, or Theory of Everything. He was working on that the day he died. The brightest minds in Physics have been trying the same thing ever since, so far without success. The only one of them who still holds, somewhat, a place in the popular mind is Stephen Hawking. Sadly, he also passed away without reaching that theoretical Holy Grail.

On an airplane ride a few years ago I sat near a youngish cosmologist. I told him I had a question I'd been just itching to ask a cosmologist; he agreed to hear it. He had already said—in agreement with things I have read—that a Unified Field Theory depends on discovering a quantum of gravity, a "graviton". By analogy with the photon, a graviton is thought to be a boson (a force-carrying particle). So I asked, "If not even photons can escape the gravity of a black hole, and all of a black hole's mass is found inside its event horizon, how do gravitons get out to reach other bodies and attract them toward the black hole? What is the 'emitting surface' of a black hole?" He was silent for half an hour, thinking. Then he said, "I have the beginning of an answer. The emitting surface of an accelerated electron is much larger than the electron, which emits photons with wavelengths thousands of times greater than the size of the atoms about which electrons orbit. By analogy, gravitons must be emitted over an area larger than the event horizon of a black hole." I agreed that it is a good beginning. I hope he has continued to think about it. Such a principle may not be the key to producing a Theory of Everything, but perhaps it is a start.

Einstein's General Relativity theory, that gravity describes the shape of spacetime, rather than being a field (or boson), is quite incompatible with the notion of a graviton! Time will tell. Einstein surpassed Newton. Some future physicist may surpass Einstein.

In the meantime, we have the real Einstein, and the legendary Einstein, to content with. Little did I realize that there is a social media presence in his name. The social media accounts for Albert Einstein are mediated by an interesting fellow named Benyamin Cohen, who has written The Einstein Effect: How the World's Favorite Genius Got into Our Cars, Our Bathrooms, and Our Minds.

Mr. Cohen states that he is not a scientist, and that he doesn't try to impersonate Einstein (unlike some fool I've heard of who impersonates Jesus online and on radio). He posts new and interesting factoids about Einstein, both from others' efforts or from bits of research unearthed at the Hebrew University of Jerusalem, where the Einstein archives are.

Cohen did a bit of traveling to connect with various facets of the Einstein legend and history. Along the way, he got to see some of the remnants of Albert Einstein's brain, which was originally stolen by the pathologist who did the autopsy; he interviewed friends and fellow scientists; he visited a warehouse where Einstein memorabilia are made and sold; he tracked down a few relatives.

In many ways, Einstein was a kind of miracle. As one descendant put it, he got all the good bits and all other Einsteins get genetic leftovers. His fame began, and largely rested, on the astonishing series of articles he published in 1905, his annus mirabilis, on four subjects:

1. Photoelectric Effect
2. Brownian Motion
3. Special Theory of Relativity
4. Mass-Energy Equivalence

It is necessary to dig into each of these very briefly, more briefly than the book does:

1. Photoelectric Effect – When light shines on any material, only the light "bluer" than a characteristic wavelength will eject electrons from it. This proved that light is carried by particles that we now call photons. The color of light we see depends on the energy of the photons. We see only a very narrow range of photon energies, with red being lower energy and blue being higher (about twice as much) energy per photon. Einstein explained how it worked, for which he received a Nobel Prize. 
2. Brownian Motion – Tiny particles such as pollen grains in water jitter continually, as described by a scientist named Robert Brown in 1827. Anyone can see this with a microscope. Later scientists developed the statistical understanding of the particles' motions. Einstein showed that the motions were caused by thermal motions of molecules of water, thus proving that such molecules existed.
3. Special Theory of Relativity – Earlier scientists had worked out some elementary math of the consequences that result if light's speed is constant, relative to anyone observing the light. Einstein formalized the theory, which showed how relative velocity between one frame of reference and another, causes the perceived length of a moving object to change, the rate of time passing to change, and the mass to change. For example, mu mesons (muons) produced in a particle accelerator go farther than one might expect: At rest the half-life of a muon is 1.52 microseconds. But if a muon beam is zipping along at 99% of the speed of light, the half life is seven times as long, about 10.8 microseconds. Without "time dilation" the muon beam would be reduced to ½ strength after 200 meters, and to ¼ strength after another 200 meters. But instead, the ½-strength distance, at 0.99c, is 1,400 meters. Much closer approaches to light speed allow muons to persist much longer.
4. Mass-Energy Equivalence – The famous equation E=mc² encapsulates the idea. Where it becomes practical is with nuclear energy (or nuclear bombs). The "atomic bomb" works by the release of energy of nuclei of uranium or plutonium: when the nucleus is split, the products weigh just a bit less than the original nucleus, and this tiny difference in mass yields a huge amount of energy. This is because c² is a very large number. The "hydrogen bomb" is even more energetic because the percent of the mass of hydrogen released by fusing it to helium is about 100x as great as that from splitting uranium.

This leads us to a paradox in Einstein. He was a determined pacifist. But, once E=mc² became known to scientists, he and others realized that Hitler's scientists could produce a devastating weapon. Thus, he sent a letter to President Roosevelt urging him to begin a project to produce that weapon first. The President did two things: he started the Manhattan Project, and he ordered his generals in Europe to intensify the war against Germany, to forestall their chances of developing an atomic weapon.

Einstein was reserved, disturbed by the limelight, the incessant publicity. He was also subject to a lot of harassment because of his fame. He might be rather bemused by his current popularity. I think he would appreciate that someone like Mr. Cohen is taking care of the social media accounts (none of which existed until about 40 years after he died!).

Here is one way Einstein's work affects us daily. Wayfinding depends on both theories of Relativity. GPS navigation depends on satellites that constantly emit precisely timed signals giving their present location in orbit. Because the satellites are moving, relative to Earth's surface, at about 2.4 miles per second (3.9 km/s), their clocks run slow by a few microseconds per day. The actual velocity of the surface depends on latitude, but ranges from zero at the poles to 0.46 km/s at the equator. All this is corrected for using the math of Special Relativity. Also, the satellite orbits are a 12,500 miles (20,200 km) above the surface, and the lower gravity field causes their clocks to run fast by a few microseconds per day. Correcting for this requires the math of General Relativity. These effects don't quite cancel out. Wouldn't that be convenient! Einstein in the sky!

By the way, I have to correct an error. On page 42 I read, "Let's say your car is moving at sixty miles per hour and headed west. Your phone sends those coordinates to the satellite, which in turn, sends back information on where you need to go…" Not even close! Here's what actually happens:

• There are 32 satellites in orbit (more are planned), in groups of orbits designed to keep three or more satellites in view from any place on Earth, all the time.
• Each carries a hyper-accurate atomic clock.
• They continually broadcast their location and the accurate (to the billionth of a second) time the signal was transmitted.

That is what the satellites do. They do not receive signals from GPS receivers in our cars or phones, nor do they calculate our driving directions. They would need to be huge supercomputers to handle the traffic of billions of devices on a continuous basis.

Your receiver, whether it's a phone or stand-alone, receives signals from satellites it can hear. This is a view from a diagnostic screen in a GPS receiver, showing ten satellites in view, and five being "listened to". Then,

• The receiver calculates the distance to each satellite based on the time signals they send compared to its own clock.
• Each distance implies a sphere in space centered on the satellite's position.
• The receiver does the math to find where the spheres all intersect. That is the position of the receiver. Three satellites can pinpoint one location on Earth; four can pinpoint that location and its elevation; five can refine the position more accurately.
• The receiver updates the screen to show its (your) current position on the map.

When you begin navigating, you tell the receiver where you want to go, and perhaps where you want to start from, or allow it to find out where it is by checking the satellite signals. It then calculates one or more routes from start to finish. Once you choose the route you want, it displays the tracking screen, updating it as you go.

The satellites don't know where you are, or anything else. They just know where they are. Your GPS receiver does all the work.

OK, back to the book. On his various trips, Cohen learned more and more aspects of Einstein's life and the ongoing hype surrounding him and his legend. A lot is there! One company still sells a warehouse full of bobblehead Einstein dolls about yearly. Hats, T-shirts, posters; Einstein look-alike contests. An Einstein exhibit near "Area 51", which is still considered by many to hold a crashed flying saucer. One celebrity attendee told Cohen, "I'm celebrated because people understand me. Einstein is celebrated because nobody could understand him."

That's the bottom line. Nobody understands what Einstein really did, except for a very few physicists who are trying to extend his theories into a Theory of Everything. Perhaps someday somebody will do it, or more likely it will be a collection of scientists. Modern science is too big for solitary geniuses to grasp it all. In the meantime, we have Albert Einstein to look up to, as someone who transcended the bounds that restrain the rest of us, at least a little. Recently, now that most light bulbs have been replaced with LED bulbs, the last patent of Thomas Edison became obsolete; of the thousand patents he was awarded, none are currently in use. Of the four articles Einstein published in 1905, and the General Relativity article he published a dozen years later, all are still in use. Whether we know it or not, we touch the results of his work daily.

Before Greek was Greek

 kw: book reviews, nonfiction, archaeology, decipherment, linear b, greek language, minoan script, biographies

The decipherment of Linear B was the greatest triumph of applied linguistics in history. The story of Jean-François Champollion and Egyptian Hieroglyphics is better known, but Champollion had the Rosetta Stone to provide what is effectively a trilingual dictionary. The persons who "cracked" Linear B had to manufacture their own "Rosetta stone" almost out of thin air.

Gentleman archaeologist Arthur Evans and his crew began to unearth clay tablets at Knossos, Crete in 1900. He soon determined that a small number of them were older than the rest, and seemed to be linguistically ancestral. Both scripts were drawn in clay with a pointed stylus, scribing glyphs formed of straight and curved lines, and thus they were dubbed Linear A and Linear B. This tablet of Linear B writing is better preserved than most. It is housed in the Ashmolean Museum in Oxford. 

The tablets themselves were preserved because Knossos was invaded, destroyed and burned. The tablets, destined to be dissolved and the clay re-used after a year or so, were baked, effectively fired into hard ceramic.

Evans found about 200 tablets with Linear A inscriptions. To date, just over 1,400 Linear A inscriptions are known, but with ten or fewer glyphs on most of them, the total corpus is too small to succumb to statistical analysis. By contrast, by 1952 when the decipherment of Linear B was mostly complete, 2,000 tablets were known, and at present, more than 6,000 inscribed artifacts have been found, many of them substantially longer than the typical Linear A inscription.

The story of that decipherment and the back story of the excavation of Knossos in the early 1900's are presented in The Riddle of the Labyrinth: The Quest to Crack an Ancient Code by Margalit Fox. To us, an unknown script is a kind of code. To the Minoans of 1400 BC, however, it was their language, just as this page is written in English, my language. Maybe in 3,000 years or so English will be as little known as is the language represented by Linear B or, even more so, Linear A.

Long ago I learned that Linear B was deciphered by Michael Ventris, a British architect and amateur linguist. His story is told, with only a little hype, in the documentary film A Very English Genius. However, his work relied on the statistical analyses of a very American genius, Alice Kober. This book brings her out of the shadows to which a century of male bias had consigned her. The work of both of them was, not so much depending upon, but impeded by, the attempts at decipherment by the discoverer of the tablets, Arthur Evans.

Sir Arthur Evans (knighted subsequent to his discoveries) was an excellent archaeologist, but as a scholar he was a real jerk, and kept 90% of the tablets away from others during his long lifetime. When he finally died at age 90 in 1941, the work which Ms Kober had been doing with the limited body of text available to her got a real boost. 

Not that there was an immediate breakthrough: just copying the texts in pre-computer times required hand transcription (even a photo is hard to interpret, as this example shows). Ignore the blue tinting; it is an artifact of boosting the contrast of the photo.

It had been evident to Evans that most of the tablets recorded economic transactions. This one is evidently a descriptive list of items, noting whether there one or two of each. The circle with dots inside is a logogram for some commercial object, I don't know what.

Knowing the general subject of the texts helped. Statistical work, which took years and years, gradually ferreted out the information needed for Alice Kober to discern a few crucial facts (Note: "language" is spoken; "script" is written; a "glyph" is a written symbol):

1. The language was inflected. Inflections are used in most Indo-European languages. English has only a few inflections, such as "-s" to indicate plural nouns (dog → dogs) and third-person verbs (I swim → she swims), and "-d" or "-ed" for the past tense of many verbs (work → worked), for example. Other languages have many more kinds of inflections, while Chinese, for example, has hardly any.
2. The script is logo-syllabic, meaning that most of the meaning is carried by glyphs that represent syllables, but a few glyphs represent whole words (our "&" for "and" is an example). Chinese is logographic: tens of thousands of core words are represented by a single glyph each, while other words are composed from two or three glyphs. English and most European languages are alphabetic, with a very small (26 for English) number of glyphs that each represent a single "atom" of sound. Amharic (Ethiopian) script is a syllabary with 231 glyphs, which are comprised of seven variations of 33 basic forms. The most familiar logo-syllabic scripts are Egyptian Hieroglyphs and Japanese. Japanese script uses a few thousand logograms derived from Chinese, and 72 syllabic glyphs used for inflection, foreign words, and words not expressed by the Chinese glyphs. Linear B has about 90 syllable-glyphs and perhaps 100 logographs.
3. Inflection and syllabaries don't work too well together. For instance, for "worker" and "working" it isn't hard to extract the inflections "-er" and "-ing". But suppose one has what is called a CV syllabary (such as Linear B), where CV means Consonant-Vowel. The symbol for "ke" and the one for "ki" will be different, perhaps quite different (dealing with the terminal "r" and "ng" sounds is another issue…). Alice Kober determined many of the "bridging" glyphs needed for Linear B to work with an inflected language.
4. A grid of syllabic relationships, a kind of matrix. A significant number of the glyphs could be arranged thus, making it possible to take a stab at certain meanings, without knowing how any of them were pronounced.

All this had been worked out and published by the time Alice Kober died in 1950 at age 43, probably of cancer. Her filing and sorting system depended on cards she sorted into cigarette carton boxes! She had been greatly helped during her last few years of life by the release of 80-90% of the tablets for her to view and transcribe, after the death of Arthur Evans. Now the torch had to pass to another, and that was Michael Ventris.

Michael Ventris had a few stellar qualities that made him well suited for decipherment. All three, Evans, Kober and Ventris, had a facility for learning languages. Ventris, in particular, never lost a child's ability to learn a language very quickly.

A side note on that: Many years ago my wife, a Japanese, was hired by a school district on a military base to teach one class daily in Japanese to the children of soldiers who had children born in Japan, who had not learned English yet. Classes were also held in German and Spanish for kids born into those languages. By three months into the program, it wasn't needed; the children learned English from their classmates so fast they achieved near-native fluency by Christmastime. Thus, the three teachers in the program were re-directed to teach a language class in Japanese, German or Spanish to any child in the school who wanted it, or whose parents wanted it for them.

Having already studied Linear B for half his life (he was not quite 30), Ventris now set aside his architecture career to dive into decipherment full time. From the beginning he had felt certain that the language behind Linear B was Etruscan. In about a year, greatly aided by Kober's results, particularly the grid/matrix, and having made the inspired assumption that words unique to tablets found at Knossos and words unique to tablets found in Greece were place names, gained the ability to assign sound values to a few signs. The grid then "solved itself", much like solving a Sudoku puzzle. He was forced by the decipherment itself to realize that the language was Greek, not Etruscan. He had the intellectual honesty to accept this. He announced the decipherment in 1952.

Fame swallowed up much of his time. Accolades devoured him. He was sometimes dogged with a case of imposter syndrome, embarrassed by the success. Plus, once one has climbed the highest mountain, what's next? He was still puzzling over that when he died in a car crash at the age of 34.

The Linear B inscriptions do not record sagas, hero stories, or kingly decrees. They are mostly lists and receipts of a commercial nature. In an era before money was common, a barter economy, keeping track of "stuff" was a critical requirement for a civilization to function. We may think we have a lot of paperwork now, but imagine if we had to record all transactions "in kind"?! "This chariot is worth so many sheep," and "That chair is worth about as much as a side table." How does one even figure his own net worth (the opening chapter of the Biblical book of Job gives us a hint)? The very banality of the inscriptions is their value. They record people's daily lives. We learn many day-to-day things about life in Knossos and nearby places.

Ms Fox's writing carried me right along. Riddle is a detective story, with three generations of detective, who solved a riddle that Sherlock Holmes would find baffling. In "The Adventure of the Dancing Men" Holmes solved a cipher. Those of us who like puzzles enjoy the newspaper cipher puzzles, which are about on the same level of difficulty. Solving Linear B was a half-century effort, though I think it is fair to argue that the solution process made little headway until 1941, after Arthur Evans died. Alice Kober laid the groundwork for solution in eight or nine years, working with 10% of the material. Then, once "the rubber hit the road" the American genius and the English genius solved Linear B in about twelve years.

Insects — worthy of more respect

 kw: book reviews, nonfiction, science, insects, ecology, entomology

To a first approximation, the average animal on Earth seems to be an ant of medium size, a little smaller than a rice grain. According to Steve Nicholls, as he writes in Alien Worlds: How Insects Conquered the Earth & Why Their Fate Will Determine Our Future, ants make up one-third of the total biomass of all insects (p. 439). The total biomass of insects, around one billion tons, equals the total mass of all humans plus all domestic animals.

As these leafcutter ants illustrate, insects were farming millions of years before humans began doing so. Leafcutter ants chew up leaves to grow nutritious fungi. Other insects carry out similar kinds of agriculture. 

Insects, again illustrated by ants, also took up ranching long, long ago. As we see here, these ants guard and "pasture" aphids and drink the honeydew they provide (others care for mealybugs).

Alien Worlds is a heavy book; the paper is supercalendered, meaning it is loaded with clay to make photographs look better. It is also more dense. This 500-page book, which doesn't look much larger than a typical novel, weighs almost three pounds; the novel would weigh a pound and a half. The quality of the images makes it all worth it.

About a third of the "real estate" of the pages consists of eye-popping photos. Mr. Nicholls is a documentarist who has traveled the world preparing programs, and he has a wealth of material on which to rely. I'll resist the temptation to scan a bunch of the pictures, and just tantalize you with one, this Hummingbird Clearwing moth, Hemaris thysbe, feeding. It is a type of hawk moth, and is about this size. This image is cropped from one page of a two-page spread showing two of these moths feeding.

The obligatory historical review in the first few chapters presents the place of insects in the arthropod phylum, a basic history of their development, and discusses some of the reasons that they became the most successful class of animals (basically: extreme flexibility of foods and conditions they can endure).

Those who are familiar with biological classification can skip a few paragraphs to the arrow below. Biological entities are named with two Latin or Latinized words, such as Tyrannosaurus rex or Homo sapiens, and the words are (or ought to be) italicized whenever possible. The first word of the scientific name, the capitalized word, is the Genus, and the second, uncapitalized word is the Species. Homo is a genus of primates that presently includes only the species sapiens, but in the past there were other species such as neanderthalensis and ergaster. A scientific name, the genus and species, must be unique, to avoid confusion.

The plural of genus is genera and the plural of species is species (no inflection); they are Latin plurals. The hierarchy of major groupings is, from top down:

• Kingdom – There are 5 or 6; here we are interested in Animalia, the kingdom of animals.
• Phylum – There are about 40 phyla of animals. Most of the creatures people call "animals" are in the phylum Vertebrata, animals with backbones. Earthworms are in the phylum Annelida. Insects and related creatures are in the phylum Arthropoda.
• Class – In the Arthropoda there are five classes. More on that below. Insect species make up about 70% of the total.
• Order – The class Insecta includes 29 orders. For example, Lepidoptera includes the moths and butterflies, and Hymenoptera includes wasps, bees, and ants.
• Family – Too many to count, and the number changes almost weekly as naturalists find new species and taxonomists (systematists) regroup existing ones.
• Genus 
• Species

The phylum Arthropoda has these groups:

These are not exactly the classes. Chelicerata, Crustacea and Insecta are classes. The myriapods are made up of two primary classes, Diplopoda (millipedes) and Chilopoda (centipedes), plus a few very minor but very distinct classes. The extinct class Trilobitomorpha  rounds out the bunch. All the living classes include members that live on land; the little "pillbugs" or wood lice, for example are crustaceans, related more to crabs than to insects.

→OK. The author, having brought the evolution of insects and their arthropod kin up to date, dwells for a chapter on the co-development of insects (and some other arthropods such as ants) and flowers. The rest of the book works its way up the ladder of social organization, finishing with bees, wasps and termites. A major aim of the author is to show how insects are integrated into every aspect of life, and how much of our "civilized" lifestyle depends on them. A few tidbits:

• Do you like almonds, a trendy superfood? Honeybees pollinate them, and the almond groves of central California need to have millions of beehives trucked in to provide a sufficient number of bees. Although other species of bee are good pollinators—sometimes working five times as hard—only honeybees exist in numbers sufficient to pollinate the almond crop. About half our plant foods require pollination by bees.
• Dung beetles and related beetles and other insects keep us from being awash in cow poop.
• Burying beetles (sexton beetles) and other members of the "cleanup squad" dispose of the bodies of little animals that die "out there", and the remains of larger animals after vultures and coyotes have picked their skeletons almost clean.
• In many cultures insects or their larvae are a necessary food item.

Another couple of interesting items: Firstly, tool use. Some insects use pebbles or bits of twig, though these behavior probably evolved and don't seem to be learned as cultural attainments the way tools are used and learned by various birds and mammals. Secondly, language. I think most of us know about "waggle dancing", a communication method among bees, to indicate the direction and distance to a productive patch of flowers. Many insects also communicate by sound, although none have a humanlike vocal apparatus. Most insect sounds are stridulation, the rubbing of legs or wings against other body parts, which makes sounds that are often amplified by resonance. Apparently, bess beetles in particular use different sounds for different purposes. These beetles are 1-1.5 inch (25-40 mm) in size, usually shiny and black, but they are seldom seen because they tunnel in rotting wood. One North American species, Odontotaenius disjunctus, makes seven distinct sounds, combined into as many as 13 utterances for different contexts (such as "food here" or "danger"). The beginnings of language? The author doesn't mention if these "words" are learned, but does tell us that each species has its own dialect.

Many have noticed that taking a drive in the countryside can now be done without the need to clean your car's windshield every 50 miles or so. When I was a child this was not so. This is often decried as an indicator that insects are in steep decline. They probably are, but I wonder to what extent we killed off all the low-flying ones, and if cars were 20 feet taller, maybe there are still plenty of critters in fight to run into. However, cars and their windshields aren't much of a culprit. Habitat destruction and overuse of pesticides take a much greater toll. I find it quite distressing to see farm after farm and orchard after orchard being sold to developers, who build housing developments or even mini-towns complete with apartments and retail outlets and office plazas. In my view, turning agricultural land into hardscape is criminal. Mr. Nicholls probably believes this also, though he doesn't state it the same way.

Besides the visual appeal of hundreds of photos, the discussions and explanations are enjoyable and impel one right along through this briefest of summaries of the vast subject of insect lore.

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If you don't care about errata, you can stop already. I am a compulsive proofreader, so I noticed a few things, a few more than I find normal:

First and foremost, discussing insect sizes, which range from 0.129 mm for a species of fairyfly (a tiny wasp) to 110 mm for the largest species of goliath beetle (stick insects can get 2-3 times this long, but they weigh much less), he states in page 45, "The size range of insects covers only three orders of magnitude, small compared to fish, for example, whose size range covers eight orders of magnitude." This is just nuts. Eight orders of magnitude is a range of 100 million to one. If the smallest fish is 1 mm in size (it's larger than that), then is the largest fish 100 km in length? He seems to have used the lengths of insects, but the weights of fishes. Let's investigate.

• Fairyfly length and weight: 0.129 mm and 25 micrograms (0.000025 g).
• Goliath beetle length and weight: 110 mm and 100 g (larva) or 60 g (adult).
• Dwarf goby length and weight: 7.9 mm and 60 g.
• Whale shark length and weight: 18 m and 20,000 kg (18,000 mm and 20 million g)
• Orders of magnitude for these insects: log(110/0.129) = 2.93, which is close to 3 for length; log(100/0.000025) = 6.6, so between 6 and 7 orders of magnitude for weight.
• Orders of magnitude for fishes: log(18,000/7.9) = 3.4, or something over 3 for length; log(20,000,000/60) = 5.5, so between 5 and 6 orders of magnitude for weight.

All this indicates that the extrema for length are in the range of three orders of magnitude for both fish and insects, and the extrema for weight are in the range of six orders of magnitude for both, with the insects having a greater range of weights! I have no idea where "eight" came from. This is worse than a simple cross-category error.

Lesser items that ought to have been caught by a copy editor:

• p125: The word for a gripping tool is "vise". The word "vice" was used, an error I see frequently, but "vice" is a sinful tendency such as over-drinking.
• pp200 and 305: At the beginning of a sentence, the starting letter was not capitalized.
• pp211 and 432: The footnote is a copy of the one on the prior page.
• p422-3: The phrase in parentheses "(soccer against)" should be "(soccer again)", as he'd made a comment about soccer a few sentences earlier.