Friday, March 1, 2024

What Was I Thinking? Remembrances of My Dissertation

In 1987, I submitted my Ph.D. thesis, “Environmental Variability and Phenotypic Flexibility in Plants,” at the University of Illinois. What was I thinking? I was dealing with three variables: plants, the growth flexibility of those plants, and the variability of the environment—in this case, of sunlight intensity. I intended to write about all three of these things in this essay, but it quickly got out of hand, so I will just tell you about how I dealt with the complex problem of measuring environmental variability in three habitats: abandoned agricultural fields, tallgrass prairies, and forest floors.

One of the major problems with measuring environmental variability is construct validity—that is, how valid is a way of measuring something so that it is a believable construct of what you claim to be measuring? I explain this concept in my book Scientifically Thinking. There is no single valid way of measuring environmental variability. What I did instead was to measure it three different ways. If these three ways all gave the same results, then they were probably valid, and I could believe the results.

First, I made instantaneous measurements of light (that is, the colors of light that stimulate photosynthesis) with a “quantum sensor” designed to do exactly this thing. The problem is, this kind of light intensity varies from one moment to the next.

So I used a second method. What I really wanted to know was the spatial patchiness of shade caused by leaves. So I made three-dimensional profiles of leaf area in the three habitat types. To do this, I used nine pieces of wood, a string, and a nail. But neither of these methods could prove that variability of sunlight intensity would actually have an effect on plants.


So I used a third method as well. I used phytometers, that is, actual potted plants. I measured the weight of the plants (plus the soil, or course) in lots of different places in the three habitats in the morning and the afternoon. I measured environmental variability as the differences in how much water the plants transpired.

This was how I tackled the problem of construct validity. I measured what I wanted to know three different ways. I was taking a chance. What if the three ways gave three different answers? But I got lucky. All three methods agreed. Chalk one up for construct validity.

I had expected that weedy fields would be the most variable, the forest floor the least variable, and prairies intermediate between them. And this is what I found. I still marvel that it came out that way.

I announced my results triumphantly: weeds had the most phenotypic flexibility and lived in the most variable environment; forest floor plants had the least flexibility, and lived in the least variable environment; and prairie plants and their environment were intermediate. The results all lined up. Despite all of its limitations, this quixotic quest was successful. I believe the results, largely because I took a risk with construct validity, and it paid off. There is no way I could have gotten these results by sheer luck. Here is the plain English summary of my thesis.

A lot of the scientific method is about validity. You have to measure it, and every time you do, you are taking a risk. But if it works, you are closer to understanding the world.

Friday, February 23, 2024

A Risk of Science

 

I just finished reading a French novel, Cent millions d’annĂ©es et un jour, by Jean-Baptiste Andrea. It was not the best novel I have ever read, but I did learn something interesting from it.

I chose the novel because the protagonist was a paleontologist named Stan, which is my name. He got a team of explorers together to go high into the Alps to look for a cave that was reputed to have a huge skeleton, maybe a dinosaur. After long personal struggles and dangers from the weather, the team gradually abandoned Stan, and he was alone when he actually found the cave. Success?

The author apparently did not understand the process of scientific research very well. Stan started his expedition based on a story. An old man a half century earlier had claimed he knew a cave that hid a big skeleton. Stan asked around in the mountain hamlets, and the rumor was confirmed only by a five-year-old girl. To most scientists, this is not an adequate basis for launching an investigation, especially one that involved a lot of time and personal risk. At least one person died by falling into the chasm that the team painstakingly created to get into what they thought was the right cave.

When Stan entered the cave, winter was advancing on him. The old man who claimed to have found a skeleton was not lying, but was mistaken. It was not a skeleton, but a pile of sticks that looked, at a glance, like a dinosaur skeleton.

It was too late for Stan to hike out of the mountains, so he had to survive in his tent all winter. He may or may not have succeeded, I’m not sure, and he was harassed by wolves that may or may not have existed. It’s just like Life of Pi, where there might have been a tiger on the raft, or maybe not.

My simple point is that, what do you do if your discovery turns out to be worthless? A lot of scientific research ends in failure. The thing to do is to get as many facts, not just rumors, as you can before beginning a big research project, and to not make one project your entire life. Stan was a moderately successful paleontologist—he found a trilobite fossil when he was a kid. With the failure of this one project, his career had failed. True scientists, like any other true explorers, do not take such risks.

Friday, February 16, 2024

The Pleasure of Finding Things Out

This is the phrase that celebrity physicist Richard Feynman used to describe the joy of scientific research. But it also describes the joy of science education. Feynman was as brilliant of a scientist as you could hope to meet, and to him mathematical equations were as obvious as the nose on your face. But he knew very well that science education did not consist of learning piles of facts. He knew it was a matter of joy: professors and students alike should share this joy. This is what I always tried to do as a science educator, even to the extent of trying out what some colleagues thought of as stunts.

This is the reason that Bill Nye the Science Guy is more popular among people in general than any professor could hope to be. Professors try to impress their colleagues; but Bill Nye’s audience is ordinary intelligent people.

 

Jamy Gormaud is France’s answer to Bill Nye. He started off as a reporter, then discovered the joy of science—just as Carl Zimmer and David Quammen started off as fiction writers and found their calling in science writing. Today, with his YouTube channel, Jamy uses humor—a lot of it—to communicate not only science but also history to a large audience. My wife and I started watching his videos in order to learn French, by slowing down the videos and reading subtitles. But I appreciate his joy of science. In one of his books (Mon Tour de France: Des CuriositĂ©s Naturelles et Scientifiques) he has assembled a tour of France to see scientific curiosities. Several dozen videos later, he is still one of our favorite video hosts. Jamy describes the pleasure of learning new things as “la connaissance qui soulève l’esprit” (knowledge that lifts the spirit). He practices “la vulgarisation de la science.” Vulgarization is not a bad word in French, although American professors and writers hate to be accused of vulgarization. It just means making science understandable and interesting to non-specialists.

He takes his readers to old places to see new things. He starts his book in the marshlands of northeastern France mainly because he saw some great sunrises there when he was a kid. This chapter is about why sunrises (and sunsets) are red. Maybe you know why, and maybe you don’t. My answer was mostly right.

Sunlight is intensely white, which results from the mixture of all visible wavelengths of light. But when sunlight encounters atmosphere, it scatters. Blue wavelenths, at one end of the spectrum, scatter more than the others, which is why the sky around the noontime sun on a clear day is blue and the sunlight itself is yellowish: the sunlight is white minus some of the blue color. When sunlight has to travel through more of the atmosphere, as when it comes in at an angle at sunrise or sunset, not only do the blue wavelengths scatter but also the others, except those at the red end of the spectrum. If you did not know this, you might have felt your brain grow a little bit right then. Thanks to Jamy, and maybe to some outstanding science teacher you may have had in the past.

Jamy, and other good science educators, also draws in perspectives from outside of science. It was Isaac Newton who explained that white light is all the rainbow colors mixed together. We do not perceive it as a range of colors, but as bands of color. It turns out, for reasons I explain in my book Scientifically Thinking, that our brains create the illusion of bands of color, which helps our brains make sense of the world. But, Jamy wondered, why did Newton say there were seven bands of color? Clearly there are bands, but can you really see seven bands? Violet, indigo, blue, green, yellow, orange, and red. Long before Newton, Robert Boyle had written that a rainbow has five bands of color. Jamy explained in his book that Newton was very religious—he wrote more pages about religion than about science—and to him seven had great Biblical significance. That is, Newton had a little bit of religious illusion even in his hard scientific observations.

He must be very satisfied in his work. To the extent that my videos fulfill the same role as his, I am satisfied. Even though I have retired, I continue to be a science educator, in the tradition of Jamy Gourmaud.

Friday, February 2, 2024

The End of Creativity

Aldous Huxley wrote a short novel in which he saw a pickup truck speeding out of a Hollywood movie studio, overloaded with unsolicited screenplay manuscripts. The truck veered, and one of the manuscripts fell off. This didn’t really happen, of course. But, almost a hundred years ago, one of history’s great writers complained about how people in power (in this case, movie producers, but this would also include editors and literary agents) would barely if ever look at what they derisively called their “slush pile” of submissions.

Today, little has changed. The term “slush pile” is still standard. I have written a lot, and published very little, fiction. One of my stories ended up in a magazine that was printed and spiral bound at a copy shop. You cannot submit fiction directly to an editor; and very few literary agents, I suspect, even look at the submissions they receive. Out of hundreds of agents to whom I have submitted samples, only about three have responded personally. The others, I suspect, just have unpaid assistants write rejections or, if the submission is online, the software automatically sends out a rejection. I suspect that few of my submissions have even been looked at.

I could say all kinds of bad things about fiction agents. But the purpose of this essay is to defend just one aspect of their refusal to look at submissions. And that is, AI software can write fiction and submit it. How is an agent to know whether a real person wrote the novel? A robot can click on the “I am not a robot” button, I assume.

And they can write them really, really fast. Amazon self-publishing recently had to set a limit on the number of submissions a single source, such as an email, can make: three per hour. One can easily see that an AI program could write ten times that many novels, and keep doing it all night without coffee and without amphetamines. A single computer could write more novels than the whole world’s collection of novels before, say, 1990.

By definition, these novels are formulaic. They follow formulas. That’s what computers do. The resulting novels are very unlikely to have any deep thoughts, and the plot lines will almost certainly be lame. No agent or editor would call them good. By slightly altering the parameters, the AI programmer can produce a great number of very different novels, all bad.

But that doesn’t matter. Most readers cannot tell the difference between good fiction and bad. Maybe a hundred years ago a reader could distinguish them. And today, some readers still can. This probably includes you, intelligent reader. But people who can tell good novels from bad are not as big of a market as those who just want something to distract them. A publisher can pay almost nothing for an AI generated manuscript, and sell a lot of copies. Each such title would be immensely profitable. If good writers complained that a certain major publisher sold books that a computer may have written, a lot of readers would just tell us to stop griping and get with the modern world.

An important reason for this is that, during the twentieth century, the rules of good literature were jettisoned. Plots no longer had to make any sense, especially if they included dream sequences. Fantasy literature is particularly vulnerable to having plots that make no sense; the writer could just change the laws of nature when he or she wanted to. There needs to be no character development or beautiful description. Certainly no meaning-of-life stuff. Poetry is even worse, which is why most poets only read poems by other poets whom they know. Real human writers turned fiction into something that a computer would eventually be able to write. That time has come.

I have spent many hours sending things to fiction agents. Each one has a slightly different set of rules, and they will not read any submission that does not follow these rules. Should you include a summary, or not? A sample of the writing, or not, and if so how much? I’m not sure that it matters, because the submission will almost certainly not be read. Some agents include a list of rules, the last of which is always, I will look at the submission if it looks like something I would like. I doubt that, in the contentment of retirement, I will ever do this again. And the main reason is that neither agents nor publishers could possibly find a good, human novel in the mass of fake AI manuscripts.

I have been moderately successful at publishing nonfiction in those subjects about which I am an expert, even if not the top expert in the world: botany, evolution, ecology, scientific thinking. Check out my books at stanleyrice.com. A computer could write nonfiction, but it would quickly get recognized as fake, because of the unlimited number of errors it would contain. Publishers might even have legal liability if readers followed stupid advice from a random manuscript. For nonfiction, agents and editors want not just a good book but evidence of expertise. This doesn’t prevent fake nonfiction from being published. There are whole “scientific” journals that will publish anything even if it makes no sense at all and since the “journals” are online it costs almost nothing to publish them. Professors have lost their jobs from claiming fake papers as their publications. But it is harder to write fake nonfiction than fake fiction.

Writers in the movie industry have gone on strike over AI taking over their jobs. Most moviegoers would not know the difference between a human writer and a computer. But the stakes are higher, since in a movie you have immense production costs aside from the writing. If moviegoers recognized a movie as “a real stinker,” the producer would quickly be out of business. Maybe.

So my plan is to stop submitting any fiction or poetry. Each submission would go into a pile of mostly computer-generated submissions, potentially numbering in the billions of billions. A needle in a haystack, or a snowflake in hell, would stand a better chance. I will have them printed up for future generations of my family. Someday, in an underground vault, they might get found. And my poems, too. Sorry, Randy, I know you are a good poet but who else can know it? I notice that neither one of us lives off of our fiction or poetry income.

A similar thing is happening in music. A good composer can still outdo a computer. Even when a Huawei program finished Schubert’s unfinished symphony, it required a little human help from composer Lucas Cantor. I listened to it. It simply did not sound like Schubert. But it was competently written and scored. Computers can provide all kinds of sounds that no musical instrument can produce, but composers still need to tell the computers what to do.

But maybe not for long. During much of the twentieth century, composers on university faculties prided themselves on writing music that was distinctly unpleasant to listen to. Their philosophy seemed to be that you are not supposed to actually enjoy music; it is supposed to be a psychological experience, and if you do not connect with the composer’s music, there is something wrong with you. This was the dominant philosophy during the years I took music courses at the university. I heard from two music graduate students about this. I was considering sitting in on a composer’s forum. A graduate student asked me, Do you use notes? I said of course I used notes. Then don’t bother with the forum, she said. Another graduate student told me that the “new music” of the twentieth century created only one emotion in her: terror.

Within a couple of decades, this approach to music was starting to die away. Perhaps they did not know it, but these out-of-touch-with-musical-pleasure composers were sowing the seeds of their own destruction. If a computer could write music that is just as good as the self-proclaimed leaders of musical innovation, then someday they will.

A lot of careers are being replaced by AI. Even some physicians I have consulted stopped to look up my symptoms on WebMD. I got lots of different diagnoses. Some of them would have been funny had they not been intended as serious

Robots have been making cars for decades.

And now they are writing novels. These days, poor Aldous Huxley would have been left mouldering in the dust.

Tuesday, January 23, 2024

Lucky to Be in Tulsa: The Twelfth Message from Fluff the Cottonwood Tree

 

I am happy that Stan has stayed in touch with me after he moved to France. He was glad to leave Tulsa, but I, speaking as a member of the species Populus deltoides, am lucky to be an American.

Almost everywhere in the world, mistletoes are parasitic. In Oklahoma, they grow mostly on elm trees, which are weakened by the Dutch Elm Disease. But in Europe, the elm trees (les ormes, Stan calls them) are stronger, and most of the mistletoes (gui, they are called) grow on black poplar trees (peupliers noirs, or Populus nigra). European black poplars are nearly identical to American cottonwoods, as I noted in my previous essay. If I had been a European cottonwood instead of an American, I would be loaded down with mistletoes. This photo that Stan took in December shows a typical black poplar.

European plant species are similar to, but usually not the same as, American plant species. But the ecological relationships—in this case, parasitism—do not always line up the same way. Evolution has played out along a slightly different path in Europe. Both America and Europe have elms, mistletoes, and cottonwoods, but in Europe it is the cottonwoods, more even than the elms, that are heavy with mistletoes. And in this one case, it has been good luck for me, an American cottonwood.