The 21st Century’s Most Important Idea… & Older Natural Algorithmic Forces

Article Image

1. “The 21st century will be dominated by algorithms,” says Yuval Harari. That makes “‘algorithm’ arguably the single most important concept in our world.”

2. He’s almost right. Natural algorithms have ruled every century with life in it. He means unnatural algorithms (which have been called “weaponized math“) now matter.

3. Daniel Dennett says, “Darwin discovered the fundamental algorithm of evolution.” Of course Darwin couldn’t have seen natural selection as algorithmic, but technomorphic analogies to our unnatural computers mean we’re beginning to recognize “algorithmic forces.”

4. For instance, Gregory Chaitin says, “the origin of life is really the origin of software,” and “DNA is multibillion-year-old software.”

5. Algorithms are sequences of step-by-step instructions for complex processes (like recipes, or software). They describe how dumber sub-steps compose complex tasks.

6. Evolution’s survival-of-the-fittest algorithm is very loosely “survive, replicate with variation, repeat.”

7. Out of that dumb process-logic arises all the intelligence and complexity of all living systems. Including what Dennett calls “competence without comprehension.”

8. Consider “termite castles” that look like a monumental Gaudí…

Yale Researchers Find That Autism Genes Helped Us to Become Smarter

Article Image

Those with autism face distinct challenges. These usually have to do with certain social deficits. That might be why the results of a new study appear a bit puzzling. Genes linked to autism spectrum disorders (ASD) were actually preserved through the process of evolution, Yale researchers concluded. These genes actually made us smarter.

If you find these results strange, consider the large numbers of scientists and engineers known to have Asperger’s syndrome. There are autistic savants as well, as the movie Rain Man can attest, which was based on a true story. Or perhaps you’ve seen the work of mind-blowing artist Stephen Wiltshire, who can draw panoramic scenes of whole cities with perfect detail, from his memory alone.

This was a genome-wide study, zeroing in on gene variants associated with ASD. Researchers examined 5,000 cases of autism and analyzed the genome of each participant. They focused on evolutionary gene selection, particularly on which genes were positively selected. One clue which led researchers to these findings was that, more genes associated with autism were preserved by evolution than would have been through sheer randomness.


Competition, Cooperation, and the Selfish Gene

Richard Dawkins has one of the best-selling books of all time for a serious piece of scientific writing.

Often labeled “pop science”, The Selfish Gene pulls together the “gene-centered” view of evolution: It is not really individuals being selected for in the competition for life, but their genes. The individual bodies (phenotypes) are simply carrying out the instructions of the genes. This leads most people to a very “competition focused” view of life. But is that all?


More than 100 years before The Selfish Gene, Charles Darwin had famously outlined his Theory of Natural Selection in The Origin of Species.

We’re all hopefully familiar with this concept: Species evolve over long periods time through a process of heredity, variation, competition, and differential survival.

The mechanism of heredity was invisible to Darwin, but a series of scientists, not without a little argument, had figured it out by the 1970’s: Strands of the protein DNA (“genes”) encoded instructions for the building of physical structures. These genes were passed on to offspring in a particular way – the process of heredity. Advantageous genes were propagated in greater numbers. Disadvantageous genes, vice versa.

The Selfish Gene makes a particular kind of case: Specific gene variants grow in proportion to a gene pool by, on average, creating advantaged physical bodies and brains. The genes do their work through “phenotypes” – the physical representation of their information. As Helena Cronin would put in her book The Ant and the Peacock, “It is the net selective value of a gene’s phenotypic effect that determines the fate of the gene.”

This take of the evolutionary process became influential because of the range of hard-to-explain behavior that it illuminated.

Why do we see altruistic behavior? Because copies of genes are present throughout a population, not just in single individuals, and altruism can cause great advantages in those gene variants surviving and thriving. (In other words, genes that cause individuals to sacrifice themselves for other copies of those same genes will tend to thrive.)

Why do we see more altruistic behavior among family members? Because they are closely related, and share more genes!

Many problems seemed to be solved here, and the Selfish Gene model became one for all-time, worth having in your head.

However, buried in the logic of the gene-centered view of evolution is a statistical argument. Gene variants rapidly grow in proportion to the rest of the gene pool because they provide survival advantages in the average environment that the gene will experience over its existence. Thus, advantageous genes “selfishly” dominate their environment before long. It’s all about gene competition.

This has led many people, some biologists especially, to view evolution solely through the lens of competition. Unsurprisingly, this also led to some false paradigms about a strictly “dog eat dog” world where unrestricted and ruthless individual competition is deemed “natural”.

But what about cooperation?


The complex systems researcher Yaneer Bar-Yam argues that not only is the Selfish Gene a limiting concept biologically and possibly wrong mathematically (too complex to address here, but if you want to read about it, check out these pieces), but that there are more nuanced ways to understand the way competition and cooperation comfortably coexist. Not only that, but Bar-Yam argues that this has implications for optimal team formation.

In his book Making Things Work, Bar-Yam lays…

The Fear of Supernatural Punishment and Not “Big Gods,” Gave Rise to Societal Complexity

Article Image

Though larger numbers of people in developed countries are abandoning organized religion, no one can deny that religion or perhaps spirituality, has been a significant part of the human experience, historically. It’s been found in all cultures throughout the world. This leads evolutionary scientists to believe that spirituality must have played a critical role in our development. But exactly how has been difficult to discern.

Of all religions, Islam and Christianity have been the most successful. Together they account for 3.5 billion people in the world. The global population currently is a little over seven billion. To be so successful and grow so complex, you need to include the help of almost everyone in society. Freeloaders or those who go off to serve their own interests could hamper development. So how do you ensure that everyone buys in?

A previous study posited that the strong gods portrayed in Christianity and Islam helped to develop their respective societies into larger, more complex civilizations. These are omnipotent, high gods who enforce the moral code, and punish those who run afoul of it. One study out of the University of British Columbia concluded that such gods may have helped spur societal development. However, there isn’t consensus among scholars, as to whether a belief in such gods is in fact a driving force.

A New Zealand research team now says that these societies were already well on their way before “big gods,” came along. Instead, it was fear of supernatural punishment that kept everyone in line, they suggest. These included punishments from mighty gods, “fallible localized ancestral spirits,” and even, “inanimate processes like karma.”

Hindu God.

Do you need a moralizing high god for society to develop, or is a belief in supernatural punishment enough?

One problem is how to study such influences. Some cultures share lots of traits, not only because of common development, but a common ancestry, history, and so on. Following back which associations influenced what development, has traditionally, been difficult. Researchers at the University of Auckland borrowed a technique from evolutionary biology that analyzes data models, to arrive at their conclusions.

Researchers looked at 96 out of 400 indigenous Austronesian cultures. This is was a great seafaring culture of the Asia Pacific region who at one time inhabited parts of Taiwan, Australia, the Philippines, Madagascar, and many of the Pacific Islands, including Hawaii and Easter Island. Cultural evolution expert Joseph Watts was one of the researchers on this study. He said, “Austronesian cultures offer an ideal sample to test theories about the evolution of…

Number of species depends how you count them

Hercules beetles
DRAWING LINES Scientists sometimes have difficulty determining whether organisms, such as these Hercules beetles, are members of different species. Genetic analysis alone may divide populations into species that don’t exist by other biological criteria.

Genetic methods for counting new species may be a little too good at their jobs, a new study suggests.

Computer programs that rely on genetic data alone split populations of organisms into five to 13 times as many species as actually exist, researchers report online January 30 in Proceedings of the National Academy of Sciences. These overestimates may muddy researchers’ views of how species evolve and undermine conservation efforts by claiming protections for species that don’t really exist, say computational evolutionary biologist Jeet Sukumaran and evolutionary biologist L. Lacey Knowles.

The lesson, says Knowles, “is that we shouldn’t use genetic data alone” to draw lines between species.

Scientists have historically used data about organisms’ ecological distribution, appearance and behavior to classify species. But the number of experts in taxonomy is dwindling, and researchers have turned increasingly to genetics to help them draw distinctions. Large genetic datasets and powerful computer programs can quickly sort out groups that have become or are in the process of becoming different species. That’s especially important in analyzing organisms for which scientists don’t have much ecological data, such as insects in remote locations or recently extinct organisms.

Knowles and Sukumaran, both of the University of Michigan in Ann Arbor, examined a commonly used computer analysis method, called multispecies coalescent, which picks out genetic differences among individuals that have arisen recently in evolutionary time. Such differences could indicate that a population of organisms is becoming a separate species. The researchers used a set of known species and tested the program’s ability to correctly predict…