Humans were the network long before software and hardware ever existed. In the human network, each person is a node, of course, and each connection with other people is a link. The links are not just what make us a network, they are what make us human.
You might deem those links as threads. Of course, sometimes they are literally like threads, the wires and the cables that make up our astonishing, often befuddling communication networks.
Other times, the threads are invisible (to us) radio waves and microwaves and what-not. But the most important invisible threads are those forged by love between family members and friends and lovers. Love is invisible but indisputably real.
This multitude of threads make up a much larger, ever-changing tapestry. A tapestry reflecting who we are, collectively, globally. A tapestry woven into the world’s far more expansive ecosystem, one we should be bent on not just preserving but sustaining and growing.
Amid all this, keep in mind you are not alone. We are not alone. Far from it.
Reticula, or networks, are not necessarily intelligent, of course. In fact, most aren’t. But all forms of intelligence require neworks, as far as I can tell.
Why?
There are lots of articles and books about how networks are the basis for natural and machine intelligence. But for the purpose of this post, I want to avoid those and see if I can get down to first priciples based on what I already know.
Define Intelligence
To me, intelligence is the ability to understand one’s environment well enough to achieve one’s goals, either through influencing that environment or knowing when not to.
Networks Are Efficient Forms of Complexity
Let’s specify that intelligence requires complexity. I have some thoughts about why that is, but let’s just assume it for now.
If you need complexity for intelligence, then networks are a good way to go. After all, networks are groups of nodes and links. Each node has two or more links…sometimes a lot more. In this post, I’m referring to larger networks.
In such networks, there are many possible routes to take to get from one part of the network to another. All these different routes will tend to have different lengths.
Why is that important? First, each length will have a nonstandard characteristic, both in terms of time and space.
Second, depending on the size and variability of the network, the patterns of that route may be as unique as a fingerprint or snowflake.
Third, this complexity is efficiently created using a relatively small amount of matter. That is, it just requires stringy links rather than large blocks of matter into which are carved intricate pathways. This efficiency is useful for animals designed to carry around intelligence in a relatively small package like the brain.
Something Must Move Within the Network
Intelligence does not only require a complex physical or virtual network of some sort, it also requires something that moves within that network. In the case of biological and machine intelligence, what moves is electricity.
I don’t know if electricity is the only possible means or agency of movement. For example, maybe one could build an intelligence made up of a complex array of tubes and nodes powered by moving water. Maybe any sufficiently complex adaptive system has the potential for intelligence if it has enough energy (of some sort) to carry out its functionality.
But electricity does seem like a very useful medium. It works at the atomic level, and it depends on the movement of electrons. Electrons are a component of all atoms, and therefore they are a natural means of transformation at the atomic scale.
In the end, though, this may be less a matter of energy than of information.
Information Is Key to Reticular Intelligence
One way or another, information is exchanged between neurons in the brain. They seem to be much more complex than simple logic gates, but the idea is similar. Some unique pathway is followed as an electrical pulses flashes through a specific part of the network. Maybe it forms some kind of value or string of chemical interactions.
Assuming they exist, I don’t know how such values would be determined, though we can imagine a lot of possible variables such as length of the pathways, strength of the pulse, shape of the neurons, etc. Regardless, I can envision that the values or interactions would be based on the unique nature of each circuit in the network.
These somehow allow us to experience “reality.” We don’t know if this reality has any objective nature. But, somehow the perception of this reality allows us to continue to operate, so these interpretations are useful to our continued existence.
Maybe what we experience is more like a GUI interface on a computer. We aren’t sure what is happening in the background of the computer (that is, in objective reality, assuming there is one), but we know what we see on the screen of our minds. And, although that screen may bear little resemblance to true reality, it does help us interface with it in useful ways.
Our Experience of a Red Tomato
I don’t know if my experience of the color red is the same as your experience. But however my mind interprets it, the color serves as useful signal in nature (and in human society).
So let’s imagine that I am looking at tomatoes on a vine. I pick the red ones because I deem those as ripe. Ripe ones taste best and may have the highest degree of nutritional value. The signal of red comes from a particular pattern in the network of my brain. Other parts of the network give me things like shape and texture. All these things are stored in a different part of the network.
When I see the requisite colors and shapes on a vine, all of these network patterns light up at once, giving me a specific value that is interpreted by my brain as a ripe tomato.
Influencing My Environment
When my neural network discerns what it interprets as a ripe tomato, other parts of network are brought into the picture. They tell me to reach out to the tomato and pick it. If it is small enough, maybe I pop it in my mouth. If it is larger, maybe I put it into a bag and bring it into the house.
These actions demonstrate some form of intelligence on my part. That is, I am able to influence my environment in order to meet my goal of pleasure and allievating hunger (which helps survival).
The Variability of the Network
I think the complexity of the network is necessary because of the complexity of the environment around me. My particular path to survival is a higher (or, at least different) intelligence than that of many other beings on the planet.
That doesn’t mean that another animal could not survive with a much more limited neural network. There are many animals that make do with much less complex ones and, I assume, less intelligence. But they have found a niche in which a more limited intelligence serves them very well in the survival game.
Plants do not seem to require a neural network at all, though it is clear they still have things like memory and perhaps agency. The network of their bodies contains some type of intelligence, even if it is what we would consider a low level.
But if your main survival tactic is being more intelligent than the other beings on the planet, then a substantial neural net is required. The neural net somehow reflects a larger number of ways to influence and interpret the environment. The more complex the network, the better it is at establishing a wide range of values that can be interpreted to enhance survival.
Summing Up
There’s so much I don’t know. I need to read more of the literature on neural nets. But even there I know I’ll bump up against a great many unknowns, such as how our experience of reality–our qualia, if you like–emerges from the bumps, grinds and transformations of the “dumb” matter in our brains.
Still, this exercise has helped me refine my intuition on why intelligence is linked to networks, though there’s still a lot that I can’t explain short of referencing the magic and miraculous.
Networks have a lot of virtues. Your personal neural net allows you to think. The Internet allows you to enjoy an astonishing array services and communications. Networks of fabric clothe you. Networks of roads and airports enable fast, cheap travel.
I could go on but you get the idea.
On the other hand, networks can also cause problems: sometimes fatal ones. In fact, they are largely responsible for the “culture wars” (which I think are more accurately defined as “reality wars”) causing widespread social conflict to the point of weakening or even destroying democracies.
The Problem with Intelligence
When the network of your brain meets the Internet, we get some terrific things… and some downright dangerous ones.
Jeff Hawkins, the author of A Thousand Brains, explains why this happens. It boils down to language, especially written language.
Our brains can believe stuff that isn’t true. This is especially the case when we’re talking about things that we haven’t directly experienced. After all, mammals’ brains were originally evolved to make sense of their own experiences. Only via language are we humans able to communicate the details of our experience to others.
This is a powerful tool for survival. Imagine our ancestors being able to tell one another in detail about where the tree with the ripest fruit is, about which times of day they could avoid the lions stalking prey at the river bank, or about the best ways to craft a bow and arrows.
No doubt humans have always used language to lie, as well. But lying to others when in a small nomadic tribe will typically be a limited affair, affecting small groups of people who know one another well and have shared most of the same experiences.
These days it’s a different story. Lies can be quickly shared with millions of people who have little ability to verify the facts as presented. This can lead to widespread belief in fabrications, flawed understandings, and convoluted conspiracy theories.
The Truth of Pocket Pink Pachyderms
Let’s say you’ve read on some blog that there is a species of salmon-colored elephants you can hold in the palm of your hand. “Really?” you think. “Too weird!”
The blog goes into detail about how some elephant experts spliced the DNA from Borneo pygmy elephants with the modified RNA of pot-bellied pigs, and how there are rich women in Indonesia who keep them in jewel-adorned bird cages as status symbols.
“Huh,” you think. “That seems way too detailed to be bogus.”
So you Google it and sure enough there’s a YouTube personality telling you they have a good friend who owns one of the tiny elephants and just adores it.
Yes, there’s a fact-checking website that says the tiny elephants are a hoax, but you don’t believe such websites because they’re all controlled by the mainstream media. You never believe anything from the MSM. You believe in real people on the Internet.
Speaking of which, you found another YouTuber who shares your views on many issues and says he personally saw one of the tiny pink elephants. He even shows a video of one of them (though another YouTube watcher claims the creature is just a newly born aardvark, a claim that sounds like sheer sour grapes to you).
Pretty soon you’re part of a private social media channel where people discuss the nefarious black market trade in these adorable creatures. Yet governments are doing nothing to stop this trade. Why not? There must be an international cover up!
You have not personally seen the exquisite but vulnerable salmon-colored elephants in the flesh, but some people you know strongly believe in “pocket pachyderm” rights and are lobbying to make them legal service animals they can bring on airplanes.
This Is Your Brain on Memes
The pocket pink elephant is just an example of how memes get started and spread. Memes are ideas that spread from from brain to brain much as viruses spread from body to body. That is, they spread quickly, sometimes even exponentially, in groups that are susceptible to them.
Memes carry cultural ideas, but sometimes these ideas are based on false premises. That’s where the trouble lies. Hawkins writes, “On its own, a brain will inexorably move toward more and more accurate models of the world. But this process is thwarted, on a global scale, by viral false beliefs.”
Dangerously Different Realities
We’ve already witnessed some of the dangers this brings. The events of January 6th were largely the result of passionate people believing that there was massive fraud during the 2020 presidential election despite an absence of evidence of the sort that could convince judges that those claims were legitimate enough to be worth investigating.
Although most Americans didn’t believe in the so-called Big Lie, millions did. This conflict of beliefs among people–who have no personal experiences of events and yet form strong opinions on whether or not those events occurred–is a danger to civil society. And, it allows politicians to play on those beliefs in order to maintain and strengthen political power, even if they themselves don’t truly hold those beliefs.
After all, pols can use the strategy of false beliefs to garner more votes, more campaign funding, and greater support for their agendas. This becomes a negative feedback loop in which false beliefs provide support for politicians and other stakeholders (for example, media outlets that sell advertising), who in turn reinforce those beliefs.
Then these beliefs become so widely shared that certain voters demand their leaders express those beliefs. And on it goes, a vicious cycle of belief in things that never happened and yet must be voiced if one wishes to continue to be viewed as a loyal member of a given group.
Networks and New Technologies
This problem is built into the nature of human language and cognition. But it is magnified by the Internet and other networks (e.g., television and radio).
Unless we address this dynamic, things are only going to get worse thanks to generative AI. Those technologies will make it ever easier to for people to mislead others as AI-fabricated photos, videos and audio to become pervasive.
We are, after all, designed to believe our eyes and ears. When we get ever more high quality video and audio fabrications spread over the global network, our reality wars may further intensify.
So, What Are You Gonna Do?
How do we avoid these reality wars? That’s among the most important questions of our age. Although I don’t hold the answers, here are some ideas to think about:
Ensure that all fact-checking organizations cite their sources, that assessments are reviewed by balanced editorial committees, and that the public can easily review methodologies and, where possible, sources. These systems can’t and won’t appease every fact-denier that comes along, but they help demonstrate the legitimacy of their analyses.
Use technologies such as blockchain to corroborate the authenticity of media sources. This remains difficult to do well, and associations between blockchain technologies and the vagaries of cryptocurrencies do not endear blockchains to the public at large. But over time, blockchains may serve useful role here.
Require that all products of generative AI technologies contain impossible or very difficult to remove identifiers that they are fabrications. And develop fake-spotting technologies that are easily used by anyone.
Require social media companies to ensure everyone gets at least a chance at a balanced perspective by modifying their link recommendation engines.
Require that this topic of how the mind works amid networks to be covered in schools as one major component of digital literacy.
Continue to use popular media to educate people about the dangers involved. Movies and documentaries can ultimately make people more aware of how false narratives and fake news works.
Seeing Things Differently
I’m not suggesting that everyone can or should hold the same positions on political or social issues. To a large degree, people can share most of the same realities and yet hold contrary opinions about them.
In fact, competing points of view are essential to the health of a working democracy.
But we need to at least agree on the fundamental facts themselves when it comes to major issues. From there, we can debate the significance of those facts and how they should addressed.
We also need to forge updated cultural attitudes toward politicians. Yes, it’s a trope that politicians lie. But in our current age, lies are more dangerous than ever before. We need to hold them to a higher standard of honesty than in the past. In fact, the 2022 mid-term elections in the United States suggests that this may be happening.
Networks are a fundamental reality, and the Internet is going nowhere barring some global catastrophe. We’ve got to figure out how to use it more wisely. Otherwise, it’ll tear us apart rather than knit us together.
Featured image from Grandjean, Martin (2014). "La connaissance est un réseau". Les Cahiers du Numérique 10 (3): 37-54. DOI:10.3166/LCN.10.3.37-54. Graph representing the metadata of thousands of archive documents. Wikipedia.
The other day, I was playing with Stable Diffusion and found myself thinking hard about the ethics of AI-generated images. Indeed, I found myself in an ethical quandary. Or maybe quandaries.
More specifically, I was playing with putting famous haiku poems into the “Generate Image” box and seeing what kinds of images the Stable Diffusion generator would concoct.
It was pretty uninspiring stuff until I started adding the names of specific illustrators in front of the haiku. Things got more interesting artistically but, from my perspective, murkier ethically. And, it made me wonder if society has yet formulated way to approach the ethics of AI-generated images today.
The Old Pond Meets the New AIs
The first famous haiku I used was “The Old Pond” by Matsuo Bashō. Here’s how it goes in the translation I found:
An old silent pond
A frog jumps into the pond—
Splash! Silence again.
At first, I got a bunch of photo-like but highly weird and often grotesque images of frogs. You’ve got to play with Stable Diffusion a while to see what I mean, but here are a a few examples:
Okay, so far, so bad. A failed experiment. But that’s when I had the bright idea of adding certain illustrators’ names to the search so the generator would be able to focus on specific portions of the reticulum to find higher quality images. For reasons that will become apparent, I’m not going to mention their names. But here are some of the images I found interesting:
Better, right? I mean, each one appeals to different tastes, but they aren’t demented and inappropriate. There was considerable trial and error, and I was a bit proud of what I eventually kept as the better ones.
“Lighting One Candle” Meets the AI Prometheus
The next haiku I decided to use was “Lighting One Candle” by Yosa Buson. Here’s how that one goes:
The light of a candle
Is transferred to another candle—
Spring twilight
This time I got some fairly shmaltzy images that you might find in the more pious sections of the local greeting card aisle. That’s not a dig at religion, by the way, but that aesthetic has never appealed to me. It seems too trite and predictable for something as grand as God. Anyway, the two images of candles below are examples of what I mean:
I like the two trees, though. I think it’s an inspired interpretation of the poem, one that I didn’t expect. It raised my opinion of what’s currently possible for these AIs. It’d make for a fine greeting card in the right section of the store.
But, still not finding much worth preserving, I went back to putting illustrators’ names in with the haiku. I thought the following images were worth keeping.
In each of these cases, I used an illustrator’s name. Some of these illustrators are deceased but some are still creating art. And this is where the ethical concerns arise.
Where Are the New Legal Lines in Generative AI?
I don’t think the legalities relating to generative AI have been completely worked out yet. Still, it looks like does appear that artists are going to have a tough time battling the against huge tech firms with deep pockets, even in nations like Japan with strong copyright laws. Here’s one quote from the article “AI-generated Art Sparks Furious Backlash from Japan’s Anime Community”:
[W]ith art generated by AI, legal issues only arise if the output is exactly the same, or very close to, the images on which the model is trained. “If the images generated are identical … then publishing [those images] may infringe on copyright,” Taichi Kakinuma, an AI-focused partner at the law firm Storia and a member of the economy ministry’s committee on contract guidelines for AI and data, told Rest of World….But successful legal cases against AI firms are unlikely, said Kazuyasu Shiraishi, a partner at the Tokyo-headquartered law firm TMI Associates, to Rest of World. In 2018, the National Diet, Japan’s legislative body, amended the national copyright law to allow machine-learning models to scrape copyrighted data from the internet without permission, which offers up a liability shield for services like NovelAI.
How About Generative AI’s Ethical Lines?
Even if the AI generators have relatively solid legal lines defining how they can work, the ethical lines are harder to draw. With the images I generated, I didn’t pay too much attention to whether the illustrators were living or dead. I was, after all, just “playing around.”
But once I had the images, I came to think that asking the generative AI to ape someone’s artistic style is pretty sleazy if that artist is still alive and earning their livelihood through their art. That’s why I don’t want to mention any names in this post. It might encourage others to add the names of those artists into image generators. (Of course, if you’re truly knowledgeable about illustrators, you’ll figure it out anyway, but in that case, you don’t need any help from a knucklehead like me.)
It’s one thing to ask an AI to use a Picasso-esque style for an image. Picasso died back in 1973. His family may get annoyed, but I very much doubt that any of his works will become less valuable due to some (still) crummy imitations.
But it’s a different story with living artists. If a publisher wants the style of a certain artist for a book cover, for example, then the publisher should damn well hire the artist, not ask a free AI to crank out a cheap and inferior imitation. Even if the copyright system ultimately can’t protect those artists legally, we can at least apply social pressure to the AI generator companies as customers.
I think AI generator firms should have policies that allow artists to opt out of having their works used to “train” the algorithms. That is, they can request to be put on the equivalent of a “don’t imitate” list. I don’t even know if that’s doable in the long run, but it might be one step in the direction of establishing proper ethics of AI-generated images.
The Soft Colonialism of Probability and Prediction?
First is the exploitation of cultural capital. These models exploit enormous datasets of images scraped from the web without authors’ consent, and many of those images are original artworks by both dead and living artists….The second concern is the propagation of the idea that creativity can be isolated from embodiment, relations, and socio-cultural contexts so as to be statistically modeled. In fact, far from being “creative,” AI-generated images are probabilistic approximations of features of existing artworks….AI art is, in my view, soft propaganda for the ideology of prediction.
To an extent, his first concern about cultural capital is related to my previous discussion about artists’ legal and moral rights, a topic that will remain salient as these technologies evolve.
His second concern is more abstract and, I think, debatable. Probabilistic and predictive algorithms may have begun in the “Global North,” but probability is leveraged in software wherever it is developed these days. It’s like calling semiconductors part of the “West” even as a nation like Taiwan innovates the tech and dominates the space.
Some of his argument rests on the idea that generative AI is not “creative,” but that term depends entirely on how we define it. Wikipedia, for example, states, “Creativity is a phenomenon whereby something new and valuable is formed.”
Are the images created by these technologies new and valuable? Well, let’s start by asking whether they represent something new. By one definition, they absolutely do, which is why they are not infringing on copyright. On the other hand, for now they are unlikely to create truly new artistic expressions in the larger sense, as the Impressionists did in the 19th century.
As for “valuable,” well, take a look at the millions if not billions of dollars investors are throwing their way. (But, sure, there are other ways to define value as well.)
My Own Rules for Now
As I use and write about these technologies, I’ll continue to leverage the names deceased artists. But for now I’ll refrain from using images based on the styles of those stilling living. Maybe that’s too simplistic and binary. Or maybe it’s just stupid of me not to take advantage of current artistic styles and innovations. After all, artists borrow approaches from one another all the time. That’s how art advances.
I don’t know how it’s all going to work out, but it’s certainly going to require more thought from all of us. There will never be a single viewpoint, but in time let’s hope we form some semblance of consensus about what are principled and unprincipled usages of these technologies.
Featured image is from Stable Diffusion. I think I used a phrase like "medieval saint looking at a cellphone." Presto.
To a large extent, you are the culmination of activity in your neocortex. That’s the part of your brain that drives sensory perception, logic, spatial reasoning, and language, among other things. Without it, you’re pretty much an inarticulate lizard person (which I’m afraid is my disposition all too often in the mornings as I read recent newspaper headlines). You neocortex is complex, highly networked place. In short, your mind is a matrix.
Or, at least neuroscientist Jeff Hawkins conceives the neocortex as a matrix of thousands of smaller brains. Amid this reticulum, each minibrain (my word, not his) stores many different models of the world. Somewhere in there there’s a mental model for your car, your house, your pets, your significant other, whatever politician you love to hate, that sweaty dude who walks that barky dog in the neighborhood every morning, and, well, everything else in your personal universe.
The minibrains are cortical columns, each quite intelligent on its own. Hawkins writes,
A cortical column occupies about one square millimeter. It extends through the entire 2.5 mm thickness, giving it a volume of 2.5 cubic millimeters. By this definition, there are roughly 150,000 cortical columns stacked side by side in a human neocortex. You can imagine a cortical column like a little piece of thin spaghetti. A human neocortex is like 150,000 short pieces of spaghetti stacked vertically next to each other.
Have Spaghetti, Will Reference
Okay, so you are largely the sum total of lots of cortical columns. But what does a cortical column actually do?
One of its primary purposes is to store and activate reference frames: oodles and oodles of reference frames.
A reference frame is where we access the information about what an object (or even an abstract concept) is and where it’s located in the world. For example, you have a reference frame for a coffee cup in various cortical columns. You know such a cup when you see it, and feel it, and sip from it. You also know where it is and how it moves. When you turn the cup upside down (hopefully sans coffee), the reference frame in your head also moves.
Reference frames have essential virtues such as:
allowing the brain to learn the structure and components of an object
allowing the brain to mentally manipulate the object as a whole (which is why you can envision an upside down coffee cup)
allowing your brain to plan and create movements, even conceptual ones
Thanks to reference frames, just one cortical column can “learn the three-dimensional shape of objects by sensing and moving and sensing and moving.” As you walk through a strange house, for example, you are mentally building a model of the house using reference frames. This includes your judgments about it. (“Hate that mushy chair in the living room, love that painting in the study, what were they thinking with that creepy bureau in the bedroom!?”)
I Think, Therefore I Predict
You’re a futurist. We all are. Because we’re subconsciously predicting stuff every moment of our conscious day.
Let’s say, for example, that you pick up your cup of coffee without even thinking about it. Your brain predicts the feel of the familiar, smooth, warm ceramic. That’s what you get most mornings. If instead your brain gets something different, it registers surprise and draws your attention to the cup.
Maybe it’s a minor surprise, like a small crack in the cup. Maybe it’s a bigger one, as when one of your fingers unexpectedly brush a cockroach that then quickly crawls up your arm. Argh!
Either way, you didn’t get what you subconsciously predicted based on your reference frame. These tiny predictions happen all the time. Your whole life is spent predicting what comes next, even of you’re not fully aware of it. If something happens that doesn’t match your mental model, your brain gets busy trying to figure out what went wrong with your expectation/prediction and what to do next.
(“Roach! Need to swat it! Where did I put that crappy news magazine? Come on, cortical-column-based reference frames, help me find it! Fast!)
You Are Your Reticulum
In short, most of your brain (the neocortex is about 70% of its total volume) is a highly complex reticulum made up of cortical columns, which themselves are made up of dense networks of neurons that are in a constant state of anticipation, even when you’re feeling pretty relaxed.
Your consciousness doesn’t exist in any one place. Your singular identity is, rather, a clever pastiche fabricated by that squishy matrix in your noggin.
So, why does it feel as if you’re you, the real mental “decider” (as George W. Bush’s neocortex once put it)? Hawkins thinks that all your various cortical columns are essentially “voting” about what you should perceive and how you should act. When you can’t make up your mind, it’s because the vote is too close to call.
So, you’re not just a matrix. You’re a democracy! Which is great. Even if our increasingly shaky U.S. government descends into tyranny, at least our brains will keep voting.
The human brain does ambiguity well. Most of us are strangely drawn to multiple meanings, surrealities and pattern recognition. We thrive on metaphors and similes, rejoice in symbols, dance to nonsense syllables and ad hoc syncopations. And paradoxes? We both hate and love them — paradoxically, of course.
No More Artful Ambiguities
This may be one of the reasons so many people become frustrated and even fearful when confronted by math and logic. Those disciplines feel so cold and hard-edged with their unitary meanings and wearisome concatenations of implacable reasoning.
It’s the same with computer coding. If you take an Introduction to Computer Science course, the professors often go out of their way to compare natural languages (a phrase which itself is an oxymoron) with computer languages.
Yao graph with number of ray k=8; from Wikimedia, by Rocchini
The gist is that while while both types of language share common and, indeed, essential properties such as syntax and semantics, they differ widely in that natural language can often be understood even when the speaker or writer fails to follow basic spelling or grammatical rules. In contrast, a computer program (much like a mathematical equation) will typically fail to work if even a single character is left out or misplaced. An absent bracket can be a fatal bug, a backwards greater-than symbol can cause an infinite loop, a poorly assigned variable can inadvertently turn 100 dollars into a dime.
A computer has no use for the artful ambiguities and multiple meanings of poetry. If you give the machine a couple of lines of verse such as “anyone lived in a pretty how town (with up so floating many bells down)”, it will — unless you carefully guide the words into the code as a string — give you an error message. (I know a lot of people who might respond the same way, of course.) Yet, without the precisely imprecise wordplay of e e cummings, those lines of poetry would not be poetry at all.
How Does People Management Fit?
So, what does any of this have to do with people management?
Just this: people management is sometimes poetry, sometimes programming, and it helps to know which is which. Before the rise of civilizations and cities, when virtually all people were hunting and gathering in smallish bands and clans, people management (in the forms it would have existed then) was all poetry.
Sure, there were unwritten rules, harsh taboos, constant rumors and deadly serious superstitions. And a leader, to the degree there were leaders as we understand them today, could leverage those cultural components to influence his or her clansmen. But this was mostly a matter of nuance, persuasion, the formation of alliances, the wielding of knowledge and lore (when, that is, it wasn’t a matter of force and coercion). In the largest sense, it was art and song.
Today, good managers must still be attuned to the poetry of human attitudes and actions, able to sort through the ambiguities of rumor mills and hurt feelings and arrogant posturings. But now managers must also cope with or even rely on laws, regulations and rules.
Hard Coding Humanity
Is there a “zero tolerance” clause in the company policy somewhere? Then even a terrific employee who gets caught using illegal drugs may need to go. Are there complex legal regulations barring a worker from having financial holdings in a certain client company? Well, then, the employee must divest or hit the door. There are countless other examples of rules that are as hard-and-fast as rule-of-law societies can make them. Although these human rules will never be quite as rigorous as the requirements of programming languages, they are a kind of human programming; there are true and false statements, barriers that can’t be broken, classifications that should never be breached.
This is why we have legal departments. It is also why uncertain managers call in the hired gun of the HR professional to take care of dismissals and drug tests and background checks.
We simultaneously hate this programming of human behavior and depend on it. We can, for example, rely on the kind of code that states:
while worker performance >= level 3: { {
provide paycheck and health insurance }
else if: {
performance <= level 2:
leverage performance review proceedings
}}
Okay, the coding in companies is much more complex than that. Still, the point is that we rely on it because it’s clean, logical and, best of all, spares us from having to make hard and potentially dangerous decisions on our own. In such settings, we are no longer “poets of people management,” the kind of managers who might have led a clan though a vast and dangerous prehistoric wilderness in millennia gone by.
People in Both Programs and Poetry
This dependence on programming is a shame in many ways, one that harried managers should ponder from time to time. I know we can’t utterly avoid modern programming — at least, not unless we retreat into the wildness, as metaphorically isolated as Thoreau in his cabin by Walden Pond. Nor should we. The rule of law is essential to our modern societies, and formal policies are often forged to protect employees from arbitrary or biased decisions. Still, we might strive to be better poets, respecting employees as the people they are rather than viewing them as components of a well-programmed machine.
A nest or hive can best be considered a body built rather than grown. A shelter is animal technology, the animal extended. The extended human is the technium.
Kevin Kelly
I like the phrase “extended human” because these days so much of our lives is spent doing just that: extending. We extend toward one another via our increasingly pervasive networking technologies, of course, but also via our words, our art, our organizations and our sometimes frighteningly fervent tribes of like-minded people.
Without these extensions, there can be no reticula – or, at least, none that includes humanity. It’s as if we are all connected neurons, the tentacled creatures of our own dreams and nightmares.
Kevin Kelly, the author of What Technology Wants, uses the phrase extended human to mean the same thing as the technium, which he defines as the “greater, global, massively interconnected system of technology vibrating around us.” But I see the extended human as beginning not with our technologies but with the reticula within: our woven, language-loving, community-seeking minds. A human who is armed only with ideas and imagination still has an amazing ability to extend herself into the universe.
Connection Matrix of the Human Brain
Technological Kudzu
Still, it’s true that the technium vastly enhances our natural tendency toward extension. In fact, as Kelly points out (and all anthropologists know), our inclination toward tool usage predates our emergence as a species. Our evolutionary predecessors such as Homo erectus were tool users, suggesting this propensity is somehow encoded or, at least made more likely, by our DNA.
These days, our extensions are growing like so much technological kudzu. Think about the growth of Zoom and other video conferencing applications. These technologies have become among of the latest technological imperatives, along with basics such as electricity, plumbing and phones/cell phones.
But there’s something missing in all this. Extensions are powerful alright, but what, exactly, are we extending? That is, what is at the core of the extended human? It isn’t a technological issue but, rather, a philosophical, psychological, existential or even spiritual one.
How Far Is Too Far?
This is where things not only get tricky but downright divisive. The Buddhist may argue that “nothing” is at the core, that most of what we want to extend is sheer ego and delusion. The Christian may argue that immortal souls are at the human core, souls which have the propensity for good or evil in the eyes of God. The Transhumanist may argue that the human body and brain are the core, both of which can be enhanced and extended in potentially unlimited ways.
Few would argue against the idea that humans should be an extended species. Even the lowest-tech Luddites rely on tools and technologies. What we will spend the next several decades arguing about are two related issues:
1) What is at the core of humanity? What should we value and preserve? What can we afford to leave behind in the name of progress and freedom?
2) How far should we extend ourselves? Should we set collective limits for fear that we’ll lose our essential humanity or cause our own extinction? If so, how can we reasonably set limits without magnifying the risks of tyranny or stagnation?
All sorts of other subjects will be incorporated into these two basic issues. For example, collective limits on technological advances become more likely if associated dangers – higher rates of unemployment, increased risks of terrorism, environmental crises, etc. – loom larger over time. Although we will frame these issues in various ways, they will increasingly be at the center of our collective anxiety for years to come. It’s the price of being the most extended species in the reticulum.
Featured image by Sheila1988; Agricultural tools at show
When I first heard of the talking drums, it make me think of how little we know about our fellow human beings and about the other citizens of the planet as well.
It’s a small but genuine annoyance. I’ll be listening some “expert,” often a professor, being interviewed for a radio show or podcast. If the idea of cognition comes up, they’ll state as a fact that humans are far more intelligent than any other animal on the planet. And, almost inevitably, one piece of evidence they’ll point to is communication. There’s the assumed inability of other animals to communicate with as much sophistication as we do.
Now, they might be right about these things, though obviously we’d need to define intelligence and communication to even establish a working hypotheses. What irritates me, though, is the certainty with which they make their claims. In truth, we just don’t know how we stack up in the animal kingdom because we still live in such a deep state of ignorance about our fellow creatures.
The Talking Drums
When I hear such claims, I think about the talking drums. For hundreds of years, certain African cultures were able to communicate effectively across vast distances. They did this right beneath the noses and within the hearing of ignorant, superior-feeling Europeans.
In his book The Information, James Gleick lays out the story of the talking drums in Chapter One. Via drums, certain African peoples were able to quickly communicate detailed and nuanced messages over long distances well before Europeans acquired comparable technologies. At least as far back as the 1700s, these African peoples were able to relay messages from village to village, messages that “could rumble a hundred miles or more in a matter of an hour…. Here was a messaging system that outpaced the best couriers, the fastest horses on good roads with say stations and relays.”
It was only in the 19th century that the missionary Roger T. Clarke recognized that “the signals represent the tones of the syllables of conventional phrases of a traditional and highly poetic character.” Because many African languages are tonal in the same way Chinese is, the pitch is crucial in determining the meaning of a particular word. What the drums allowed these peoples to do was communicate complex messages using tones rather than vowels or consonants.
Using low tones, the drummer communicates through the phrases and pauses. Extra phrases are added to each short “word” beaten on the drums. These extra phrases would be be redundant in speech, but they can provide context to the core drum signal.
Enormous Chasms
The technology and innovativeness of the talking drums is amazing, of course, but what’s especially startling is the centuries-long depth of European ignorance about the technology. Even once some Europeans admitted that actual information was being communicated across vast distances, they could not fathom how.
Why? Sure, racism no doubt played a part. But the larger truth is that they simply didn’t have enough information and wisdom to figure it out. That is despite the fact that we are talking about members of the same species and, indeed, a species with very little genetic diversity.
Here’s how the Smithsonian Institution reports on this lack of diversity:
[C]ompared with many other mammalian species, humans are genetically far less diverse – a counterintuitive finding, given our large population and worldwide distribution. For example, the subspecies of the chimpanzee that lives just in central Africa, Pan troglodytes troglodytes, has higher levels of diversity than do humans globally, and the genetic differentiation between the western (P. t. verus) and central (P. t. troglodytes) subspecies of chimpanzees is much greater than that between human populations.
On average, any two members of our species differ at about 1 in 1,000 DNA base pairs (0.1%). This suggests that we’re a relatively new species and that at one time our entire population was very small, at around 10,000 or so breeding individuals.
For Europeans to remain so ignorant about a technology created by other members of their own barely diversified species tells us how truly awful we are at understanding the communication capabilities of others. Now add in the exponentially higher levels of genetic diversity between species. For example, the last known common ancestor between whales and human existed about 97 million years ago. How about the last known ancestor between birds and humans? About 300 million years ago.
These timescales represent enormous genetic chasms that we are not remotely capable of bridging at the moment. We are still in the dark ages of understanding animal cognition and communication. So far, our most successful way of communicating with other animals is by teaching them our languages. So now we have chimpanzees using sign language and parrots imitating our speech patterns. African Grey parrots, for example, can learn up to 1,000 words that they can use in context.
Yet, when these species do not use human language as well as humans, we consider them inferior.
If We’re So Bloody Bright…
But if we as a species are so intelligent, why aren’t we using their means of communication? I’m not suggesting that other animals use words, symbols and grammar the way humans do. But communicate they do. I live in Florida, which is basically a suburbanized rainforest, and have become familiar with the calls of various birds, tropical and otherwise. One of the more common local denizens is the fish crow. I hear crows that are perched blocks away from one another do calls and responses. The calls vary considerably even to my ignorant, human ears, and there are probably countless nuances I’m missing.
Are they speaking a “language”? I don’t know, but it seems highly unlikely they’re expending all the vocal and cognitive energy for no reason. Their vocalizations mean something, even if we can’t grasp what.
Inevitably, humans think all animal communication is about food, sex and territory. But that’s just a guess on our part. We assume that their vocalizations are otherwise meaningless just as many Europeans assumed the talking drums were mostly meaningless noise. In short, we’re human-centric bigots.
Consider the songs of the humpback whales. These are extremely complex vocalizations that can be registered over vast distances. Indeed, scientists estimate that whales’ low frequency sounds can travel up to 10,000 miles! Yet, we’re only guessing about why males engage in such “songs.” For all we know, they’re passing along arcane mathematical conceits that would put our human Fields Medal winners to shame.
On Human Ignorance
The point is that we continue to live in a state of deep ignorance when it comes to other our fellow creatures. That’s okay as long as we remain humble, but we humility is not what people do best. We assume we are far more intelligent and/or far better communicators than are other species.
Yet, consider the counterevidence. Just look the various environmental, political and even nuclear crises in which we conflict-loving primates are so dangerously enmeshed. It hardly seems like intelligence. Maybe the whales and parrots are really discussing what incapable morons humans are compared to themselves. With that, mind you, it would be hard to argue.
In myfirst post on Peter Wohlleben’s The Hidden Life of Trees, I wrote a bit about the how certain hyphae–that is, the branching filaments that make up the mycelium of a fungi–play a key role in establishing the “wood wide web.” So much is happening under the forest floor. But perhaps you were left wondering, “Okay, but what’s in for the fungi?”
The Enlighted Entrepreneurship of Fungus
As it turns out, a lot. The fungi definitely take their cut of the sugar and other carbohydrates produced by trees. Indeed, they can take as much as a third of a tree’s total food production for services rendered. A third!
The IRS has got nothing on the fungi.
So, what do the trees get in return? Well, as we previously noted, they extend the reach of tree roots and allow trees to share not only nutrients but also information with one another. Let’s face it, that’s pretty good service. It’s as if our Internet provider was not only letting us exchange information but also allowing us to directly send food and water to one another.
But, as the Ronco people used to say, “And that’s not all!”
The beneficial fungi also provide certain medical benefits. Not only do they filter out poisonous heavy metals, they ward off bacteria and the more destructive types of brethren fungi.
But these tree-loving fungi are not dedicated to just one species of tree. They play the field, willing to connect trees of different species. Wohlleben writes, “Although many species of tree fight each other mercilessly above ground and even try to crowd out each other’s root systems, the fungi that populate them seem to be intent on compromise.”
In a way, the fungi are like a huge retail chain (think Amazon), helping many companies because betting on just one corporation could be disastrous if that corporation failed. Similarly, the fungi do not want to bet on just one species of tree because if some plague takes out that species, then they their fates are tied only that failing species. If a beech tree complains to that it’s local fungi should not also be helping their competitors the oaks, you can almost hear the fungi say, “Sorry there Beech boy, it’s not personal, it’s business.”
Plumbing the Mysteries of Trees
Not only don’t we fully grasp the complexities of trees, we don’t even understand a lot of the basics. One of those basics is plumbing. That is, how do trees pump water all the way from their roots to their crowns?
Wohlleben discusses two primary theories. First, there’s capillary action. Wikipedia defines the action this way:
[T]he process of a liquid flowing in a narrow space without the assistance of, or even in opposition to, any external forces like gravity. The effect can be seen in the drawing up of liquids between the hairs of a paint-brush, in a thin tube, in porous materials such as paper and plaster, in some non-porous materials such as sand and liquefied carbon fiber, or in a biological cell. It occurs because of intermolecular forces between the liquid and surrounding solid surfaces. If the diameter of the tube is sufficiently small, then the combination of surface tension (which is caused by cohesion within the liquid) and adhesive forces between the liquid and container wall act to propel the liquid.
Here’s how I think of it: when you put water in a narrow vessel, the water itself stands above the lip of the vessel. So, when you fill a glass of water to the brim, the water actually stands slightly above the rim of the glass due to capillary action. The narrower the vessel, the higher it stands.
Although I’ve noticed this before, I’ve never thought much about it. However, this action accounts for some of the rise of water up the trunk of a tree. How much? Wohlleben says 3 feet in a 300 foot tree. In other words, more than you might think but not all that much.
The second way trees pump water is transpiration. Wohlleben describes it thus:
In the warmer part of the year, leaves and needles transpire by steadily breathing out water vapor. In the case of a mature beech, the tree exhales hundreds of gallons of water a day. This exhalation causes suction, which pulls a constant supply of water up through the transportation pathways in the tree.
So, the tree uses suction, the same principle by which we drink our juice boxes. Which is very cool!
There’s just one problem with this transpiration idea. It doesn’t explain the mysterious rise of water in trees before the leaves emerge. In fact, water pressure is highest in trees before leaves open in the spring!
So, we can glibly toss around terms such as capillary action and transpiration, but they alone can’t account for what trees are doing in the real world. And, if we can’t even account for basic plumbing in trees, imagine how much else we’re missing.
Skin in the Losing Game of Life
Bark is the skin of trees. Like our skin, tree bark is constantly being shed. As with our skin, bark holds in life-giving water and protects a tree’s inner organs from the deadly world outside. As with our skin, bark wrinkles as the trees age.
The wrinkles aren’t the only things we share with trees. Like us, trees actually start to bald and shrink a bit as they get old. And, as with us, they finally succumb to entropy, and their bark begins to fail.
When it does, the non-beneficial types of fungi help bring about their demise. Wohlleben writes:
Small moist wounds have become portals for fungi to enter. The fungi advertise their triumphant advance through the tree by displaying magnificent fruiting bodies that jut out from the trunk in the shape of semicircular saucers that grow larger with each passing year…Then one day it’s all over. The truck snaps and the tree’s life it at an end.
And so the tree dies and eventually becomes part of the forest floor, feeding the roots of its competitors and children. Meanwhile, the fraternizing fungi below continue their work, taking in the big picture, ultimately seeing the forest for the trees.
Note: In case you were left wondering, this post approximately covers chapters 9 through 13, though I can never quite keep myself from deviating beyond the confines of the text itself.
