Richard Alley - Predicting Future Sea-Level Rise

Members of our broader research group are working extensively in the field. This especially involves the International Thwaites Glacier Collaboration, the major project to learn what is going on in the most vulnerable part of the most vulnerable ice sheet in the Antarctic, the West Antarctic Ice Sheet, which includes the Thwaites Glacier. After seasons lost to Covid, a major expedition will be traversing down Thwaites, using radars, seismic sensors and more to characterize the ice and its bed.

Other groups are working farther downstream, extending work that has been done on the ice shelf and in the ocean beyond. Thwaites is vast, larger than the state of Florida. It is some 80 miles across, making it arguably the widest glacier on Earth. Since the 1990s, scientists have reported on the increased velocity of its movement and the doubling of its contribution to sea-level rise. Its collapse would trigger meters of sea-level rise in the decades and centuries to come, hence its popular nickname in the media, Doomsday Glacier.

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What are the challenges in predicting how much warming will ultimately cause the Thwaites Glacier to break apart?

Some of this is really difficult, especially where fractures are involved. Think about ceramic coffee cups dropped on hard floors. Sometimes the coffee cup just bounces, or the rim chips, or the handle breaks off, but sometimes the whole thing shatters. Scientists can accurately predict the average behavior of a lot of coffee cups dropped on a lot of floors, if you tell us the height of the drop, the type of floor, the type of cup and a few other things. But predicting the exact behavior of the next cup dropped is really difficult, in part because the behavior depends on whether there are small cracks buried deep in the material of the cup, among others. Predicting exactly how much warming is needed to break parts of Thwaites will be harder than predicting coffee cups.

Sounds like there’s still a lot of uncertainty here. How should policymakers cope with that?

First of all, the uncertainties are not our friend. There is basically no way that sea-level rise can be notably smaller than expected. When we make the climate warmer, the ocean warms up. That makes the water expand, which raises sea level. That’s relatively easy.

The glaciers in the mountains are doing what we projected decades ago: They really are melting. That takes water that was ice out of the mountains and puts it into the ocean, and that raises sea level. Those are fairly easy predictions. There are not large uncertainties in those. The uncertainties are: Will the ice shelves break off, will the flow of the big ice sheets change a lot, with the potential to drive these very large, rapid sea-level rises. So the uncertainties are on the bad side.

In other areas of our lives, we tend to invest a lot to avoid the possibility of a catastrophe, even if we are not sure it is going to happen. The example I like to use is highway safety. We have highway engineers, we have crumple zones in the car, we have airbags and antilock brakes and seatbelts and we have police out there trying to stop drunken drivers. We are not very likely to get killed by a drunken driver, but the catastrophe would be so bad if it happened that we invest a lot in heading that off.

What would make sense may be to think about sea-level rise and our response to it with the same sort of lens: There are things we can do to better understand why it happens and what the causes are. Next steps might be communities taking steps that reflect scientific findings, which of course have economic as well as social benefits.

- More Here

Beauty Of Uncertainty - A Source Of Inspiration

When I’m asked about this on occasion, I hedge the question too. But my answer is this: inspiration is not the exclusive privilege of poets or artists generally. There is, has been, and will always be a certain group of people whom inspiration visits. It’s made up of all those who’ve consciously chosen their calling and do their job with love and imagination. It may include doctors, teachers, gardeners – and I could list a hundred more professions. Their work becomes one continuous adventure as long as they manage to keep discovering new challenges in it. Difficulties and setbacks never quell their curiosity. A swarm of new questions emerges from every problem they solve. Whatever inspiration is, it’s born from a continuous ‘I don’t know.

- Poet Wisława Szymborska

I don't know is one of the reasons that kept me alive. There is so much that I don't know that I need to understand whatever little I can before my time is up. 

The Coincidence Project

In February 1973, Dr. Bernard Beitman found himself hunched over a kitchen sink in an old Victorian house in San Francisco, choking uncontrollably. He wasn’t eating or drinking, so there was nothing to cough up, and yet for several minutes he couldn’t catch his breath or swallow.

The next day his brother called to tell him that 3,000 miles away, in Wilmington, Del., their father had died. He had bled into his throat, choking on his own blood at the same time as Beitman’s mysterious episode.

Overcome with awe and emotion, Beitman became fascinated with what he calls meaningful coincidences. After becoming a professor of psychiatry at the University of Missouri-Columbia, he published several papers and two books on the subject and started a nonprofit, the Coincidence Project, to encourage people to share their coincidence stories.

“What I look for as a scientist and a spiritual seeker are the patterns that lead to meaningful coincidences,” said Beitman, 80, from his home in Charlottesville, Va. “So many people are reporting this kind of experience. Understanding how it happens is part of the fun.”

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Beitman defines a coincidence as “two events coming together with apparently no causal explanation.” They can be life-changing, like his experience with his father, or comforting, such as when a loved one’s favorite song comes on the radio just when you are missing them most.

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People who describe themselves as spiritual or religious report noticing more meaningful coincidences than those who do not, and people are more likely to experience coincidences when they are in a heightened emotional state — perhaps under stress or grieving.

The most popular explanation among survey respondents for mysterious coincidences: God or fate. The second explanation: randomness. The third is that our minds are connected to one another. The fourth is that our minds are connected to the environment.

For Beitman, no single explanation suffices. “Some say God, some say universe, some say random and I say ‘Yes,’” he said. “People want things to be black and white, yes or no, but I say there is mystery.”

He’s particularly interested in what he’s dubbed simulpathity — feeling a loved one’s pain at a distance, as he believes he did with his father. Science can’t currently explain how it might occur, but in his books he offers some nontraditional ideas, such as the existence of “the psychosphere,” a kind of mental atmosphere through which information and energy can travel between two people who are emotionally close though physically distant.

In his new book published in September, “Meaningful Coincidences: How and Why Synchronicity and Serendipity Happen,” he shares the story of a young man who intended to end his life by the shore of an isolated lake. While he sat crying in his car, another car pulled up and his brother got out.

When the young man asked for an explanation, the brother said he didn’t know why he got in the car, where he was going, or what he would do when he got there. He just knew he needed to get in the car and drive.

- More Here

What I've Been Reading

Unicellular genes that enhance competition and survival are precisely those genes that cause cancer in multicellular organisms. The seed of cancer already exists in every multicellular organism, because it is simply a remnant of our evolutionary past. When the new rule break down, the old unicellular behaviors reassert themselves. The seed of cancer grows, is immortal, moves around, and uses the Warburg effect. This is an ancient tool kit of survival responses. These are the hallmarks of cancer. This is the new invasive species known as cancer. 

The Cancer Code: A Revolutionary New Understanding of a Medical Mystery by Dr. Jason Fung.

Dr. Jason's book was published few months after Max passed away but until I read this book, I have no idea that cancer is a unicellular organism that was competing with Max and every one of us who are multicellular organisms. This changes everything I knew about cancer and the treatment options. To be clear, none of the treatments given to Max nor available now are nothing but playing Russian roulette with not only genetics, lifestyle, ecology but against a primordial unicellular organism which is evolved before we did. 

What is Cancer?

The term cancer does not refer to a single disease, but denotes a collection of many different diseases related to certain qualities. Something can be considered cancer when it has the following 8 characteristics:

• Grows
• It sustains proliferative signaling
• It evades growth suppressors
• It resists cell death
• It induces angiogenesis.
• Is Immortal
• It enables replicative immortality
• Moves Around
• It activates invasion and metastasis
• It evades immune destruction
• Uses the Warburg Effect
• It deregulates cellular energetics

Benign cancer shares all the first five characteristics and without the ability to metastasize, cancer is more a nuisance than a serious health concern. 

Somatic Mutation Theory (SMT)

The basic postulates of SMT include: 

1. Cancer is caused by acquiring multiple DNA mutations.
2. These mutations accumulate randomly.
3. The cells in the tumor are all derived from one original clone. 

The somatic mutation theory of carcinogenesis patched together all the disparate know causes of cancer into a coherent, unified theory (mine: very similar to a religious, free-market, or soviet style ideologies).  This paradigm focused research from extrinsic agents (chemicals, radiations, and viruses) onto intrinsic defects (genetic mutations). 

The great contemporary thinker and philosopher Nassim Taleb often uses this allegory of the Procrustean bed to describe how facts are often tortured to fit a certain narrative. The widely and often blindly followed somatic mutation theory of cancer required a Procrustean bed to fit the facts, too. 

Cancer was far, far more different genetically than they were alike since:

• Different types of cancer had different mutations 
• The same type of cancer in different patients had different mutations. 
• The same cancer in the same patient had different mutations in the primary tumor compared to metastatic cancer. 
• The same cancer in the same patient had different mutations in different mutations at different sites of metastasis. 
• The same cancer in the same patients in the same tumor mass had different mutations. 

Cancer was a baffling mishmash of genetic peculiarities that had almost no connection to one another. Genetic mutations were everywhere and nowhere. Some cancers had hundreds of mutations, and others had none at all. The rate of mutations necessary to develop a cancer is much higher than the known rate of mutation in human cells. Normal cells just don't mutate anywhere close to the rate needed to produce cancer. Finally, the genetic mutations were a proximate, rather than a root, cause of cancer. 

Genetic mutations may explain the mechanism of how cancers keep growing, but they do not explain the fundamental question of why these genes mutated. The SMT fails because it is entirely inward-looking, towards our genes, instead of outward-looking, toward the environment. The seed is important, but the soil matters most. 

Cancer is older than humanity

The oncogenes and the tumor suppressor genes discovered so laboriously over the last quarter-century are mutations of normal genes. Every single cell in our body contains the seed of cancer. Why?

Dogs get cancer. Cats get cancer. Rats get cancer. Even the most primitive multicellular organisms develop cancer. In 2014, cancer was discovered in two species of hydra. You may recall from high school biology class that hydra are simple, small aquatic organisms that evolved very early on from single-cell organisms. 

The origins of cancer are found at the origins of all multicellular life itself. This may have seemed obvious to a cancer outsider, but not to an insider with the curse of knowledge. Cancer is very deeply embedded into the way multicellular life is done. 

Cancer is older than humanity. Searching for the answers to cancer's origin among the evolutionarily recent genes of humans is futile. The answers are simply not there. Cancer was something much older and more fundamental to life on earth than humanity. 

Single-cell organisms differ from multicellular organisms by the following four main characteristics: 

1. They grow
2. They are immortal
3. They move around
4. They use glycolysis (also called the Warburg effect)

These are precisely the characteristics of cancer!

Cancer originates from cells of a multicellular organism, but it behaves precisely as a single-cell organism. This is a spectacular and novel finding. 

The roots of cancer lie in our evolutionary past. Perhaps cancer was not a forward-looking evolutionary process, but a backward-looking one. 

Today's standard cancer treatments resemble ancient existential threats: radiation (pre-ozone layer), poison, and antimetabolites (nutritional challenges, periodic starvation). Unicellular cells are no strangers to these threats and have evolved effective responses to flourish under these precise conditions. 

We've long treated cancer as some kind of random genetic mistake. A mistake that arises in all animals throughout history and evolves independently in millions of people a year? Cancer is hardly a mistake. Cancer is the ultimate survivor. When all else dies, cancer is there because it is the core of the cell that will survive at all costs. Cancer is not random, and it is not stupid. It has developed the tools it needs to survive. 

This model fits the known facts of cancer better than any previous paradigm. Undoubtedly, this will not be the final word on cancer, and it should not be judged as such. Nor are all its suppositions proven facts. There will always be much to learn about cancer, but I believe this new paradigm is a huge and useful step forward, explaining many of cancer's mysteries. 

Nutrition & Cancer: 

Fiber - By comparative study between African (with lots of fiber) and Western diet (little fiber); cancer was not simply a disease of too little fiber, and thus, eating more fiber didn't translate into less cancer. 

Fat - By comparative study between South Pacific Islanders (with lots of fat) and Indian vegetarians (low fat); lowering dietary fat resulted in no measurable protection against cancer. 

Vitamins - When vital nutrients like beta-carotene are available in large doses, cancer cells are highly active and grow like weeds. Same with folic acid (vitamin B9), Vitamin E while Vitamin C, D, and Omega-3 oils were neutral. High-dose vitamins promote cell growth. It is really that simple. 

But diet plays a large role in cancer. 

• Obesity clearly increases the risk of cancer. Obesity also clearly increases the risk of type 2 diabetics. The link - insulin. 
• Avoid - Sugar and refined grains which leads to hyperinsulinemia. 
• Insulin is an important nutrient sensor, signaling the presence of food, but what does that have to do with cancer? Everything! The nutrient sensor insulin is also a highly potent growth factor. 
• Each increase in ten centimeters in height is associated with a 16 percent increase in the risk of cancer. Growth factors increase height. Growth factors also increase cancer risk. 
• The most widely studied natural food for cancer chemoprevention (term used to denote foods, supplements, or drugs that may block progression of cancer) is green tea, which contains high levels of catechins. 

Growth - The common thread that runs through all conditions of increased weight, increased weight, increased eyeball length (myopia), and cancer is that they are all conditions of excessive growth. We often think growth is good, but the truth is that in adults, growth is not necessary or even good. Quite the contrary, growth is bad, sometimes very bad. 

Mammalian target of rapamycin (mTOR) - This was an astonishing revelation for biologists - the equivalent of discovering a new continent in the Atlantic Ocean. Hundreds of years of medical science had somehow missed this fundamental nutrient-sensing pathway that was so essential to life on earth that it had been conserved in animals from yeast all the way to humans. In an evolutionary sense, mTOR is older even than the much better-known sensor insulin. The mTOR pathway is found in virtually all life-forms, rather than just mammals, so the name was changed to a mechanistic target of rapamycin, but it retained its catchy moniker "mTOR". 

AMPK - The nutrient sensors insulin and mTOR respond mainly to dietary intake of carbohydrates and proteins. The nutrient sensor AMPK, however, assesses the overall available cellular energy. 

• Lots of energy stored = low AMPK
• LIttle energy stored = high AMPK
• High AMPK lowers mTOR activity, slowing growth down. AMPK increases the production of new mitochondria, the energy makers in cells, to increase the cell's capacity for burning fat. AMPK also increases autophagy, the important cellular self-cleansing, and the recycling process. 
• Foods and drugs that activate AMPK - Diabetes drug metformin; resveratrol from grapes and red wine; epigallocatechin gallate (EGCG) from green tea and chocolate; capsaicin from peppers; turmeric, garlic, and the traditional Chinese medical herb berberine. Calorie restriction also activates AMPK. 

Autophagy - The word autophagy derives from the Greek word auto, meaning "self" and phagein, meaning "to eat", so it literally means "eating oneself". Autophagy is a regulated, orderly process of degrading cellular components to be recycled into new ones. Autophagy functions as a cellular housekeeper, when mTOR is high, putting the cell into growth mode, so autophagy and mitophagy (the process of removing old and damaged mitochondria) turn off. 

• Nutrient deprivation, especially protein deprivation lowers mTOR and activates autophagy. 

Metastasis:

Cancer cells break off the primary tumor to find more room to grow. This happens early in cancer's course, as the circulating tumor cells (CTCs) consume nutrients rapidly and are very quickly driven by the increased competition for resources. This new environmental stress creates new evolutionary selection pressures. 

Unfortunately, these CTCs find out that the bloodstream is a terribly hostile environment, and most just die. One day, a rare genetic mutant arises that is able to survive both the immune cell attack and the travel through the bloodstream long enough to circulate back to the original tumor site. 

As it returns home, it finds a sanctuary against all the scary things trying to kill it, and it recovers. The tumor has just self-seeded. But this returning cancer is more aggressive and just a tiny bit better able to survive in the bloodstream. This more aggressive variant multiplies within the safety of the primary tumor site. It dominates and outcompetes the incumbent cancer cells. This cycle of tumor self-seeding and metastasis repeats over and over, with cancer continually evolving over time its ability to survive the bloodstream. 

Eventually, a rare genetic mutation allows the cancer cells to reach the new distant shore of the other organs and manage to survive. They might not thrive, but at least they're not dead. This micrometastasis is so small that it is undetectable and may lie dormant for decades. Invasion and metastasis are difficult to skills to master, and most cancers fail. 

Given enough time, Darwinian evolutionary processes select a rare genetic variant to flourish, and the little outpost of metastatic cancer cells grows. Cancer has just become metastatic. This slow process from initial carcinogenesis to metastasis takes decades. 

New Dawn:

The evolutionary/ecologic paradigm recognizes the importance of cell-to-cell interactions and interactions with the environment, making it a far more dynamic, inclusive, and comprehensive theory of cancer. Evolutionary biology links carcinogenesis, progression, and metastasis, whereas genetics considers them all as separate issues. 

This idea is not new; it just needed to be rediscovered. "Cancer is no more a disease of cells than a traffic jam is a disease of cars," wrote cancer researcher D.W. Smithers in 1962. A traffic jam results from the interaction between the car, neighboring cars, and the environment. If you look only at each individual car - Are the brakes working? Was it recently serviced? - you will fail to find the problem. 

Similarly, cancer is not only a genetic disease but also an ecological disease. The environment plays a huge role in determining whether cancer grows. Under certain conditions, such as high insulin levels, cancer will thrive, while under other conditions, it will fail to establish itself. 

Treatments:

Screening

Simply catching more early-stage diseases is not useful by itself. In breast and colorectal cancer, screening reduced late-stage disease but in prostate, esophageal, and pancreatic cancer it has not, and that makes all the difference in the world. 

Many of the early-stage breast cancers are unlikely to ever progress to a dangerous state - as the evolutionary model explains, cancer can be fully contained by the body's own anti-cancer mechanisms. Aggressive treatment of early cancers is simply unnecessary. With toxic treatments such as surgery, radiation, and chemotherapy, the treatment may be worse than the disease. 

Finding and treating cancers that don't need to be treated is not a useful strategy. 

Without good evidence of the benefits of screening, and a better understanding of why it may fail, we must rely on the ancient medical guiding principle of Primum non-nocere, which means, "First, do no harm." 

Dietary Determinants

Autopsy studies find unsuspected prostate cancer in 30 percent of men over the age of fifty, 50 percent by age seventy, and an astounding 80 percent by age ninety. Because the seed of cancer is ever-present in all our cells, an important question is: why don't you get cancer? If it is not a seed problem, then it may be a soil problem. Diet is a hugely important determinant of progression because nutrient availability is inextricably linked to cell growth, particularly for cancer cells. For the most part, dietary prevention of cancer boils down to one key strategy: avoiding diseases of hyperinsulinemia, including obesity and type-2 diabetes.   

Ketones

When fat is metabolized for energy, molecules called ketone bodies are produced, which cancer cells have difficulty using. By simulating the breakdown of muscle protein, amino acids are delivered to the liver and converted to glucose, which cancer cells love. So, while weight loss may be a useful strategy to prevent the progression of cancer, cancer cachexia (a phenomenon of unintentional weight loss in patients with advanced disease), once advanced, limits the effect of diet on cancer treatment. Reducing glucose in an attempt to "starve" cancer is only modestly hopeful because advanced cancer can break down other tissues to free the glucose it needs. Dietary therapy must likely be combined with other treatments to be effective at this stage.

Fasting & Cancer:

• Intermittent fasting is a promising nutritional approach for cancer prevention, as it protects against many risk factors such as obesity, type 2 diabetes, and inflammation. 
• Fasting simultaneously reduces all human nutrient sensors, most of the growth pathways, and also increases autophagy and mitoghagy. 
• Fasting during chemotherapy may also reduce the side effects of treatment while increasing efficacy. Fasting protects the normal cells by putting them into a quiescent state, or maintenance mode, which may help mitigate chemotherapy side effects of hair loss and nausea. Cancer cells do not enjoy this protective state because their genetic programming puts them into continuous growth mode. 

Immunotherapy

Immunotherapy has several inherent advantages over conventional treatments. 

• The boosted immune system is a dynamic system that can better keep pace with cancer's moves. The immune system can adjust and evolve alongside the cancer. 
• Immune system has a memory, so it may prevent recurrence. 
• Immunotherapy has fewer side effects than standard chemotherapies because the immune system is a targeted treatment. 
• Immunotherapy is a systemic treatment, which is crucial because cancer is a systemic disease. Metastasis occurs early in the disease process, so a systemic therapy can treat potential micrometastases throughout the body. The immune system can lock on and destroy cancer cells and does not need to be manually targeted in the same way as local treatments like surgery and radiation. The systemic nature of treatment also means that immunotherapy may be effective even very late in the disease process, after the cancer has metastasized. 

What I've Been Reading

Science, the discipline in which we should find the harshest skepticism, the most pin-sharp rationality, and the hardest-headed empiricism, has become home to a dizzying array of incompetence, delusion, lies, and self-deception.

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That moral case - that making errors in science is much more than just an academic matter, because of the harm it can cause - applies similarly to fields of research that directly sacrifice lives. I'm referring, of course, to research on non-human animals, where the subjects are often 'euthanized' - that is killed - as part of the experiment (for example, to examine their brains after a new drug has been administered). This kind of research is usually strictly regulated by government agencies since virtually everyone agrees it would be immoral to kill lab animals, or even just to cause them to suffice, for no good scientific reason. So animal studies don't just carry the usual of trying to produce accurate, replicable results without wasting resources. They also have an additional responsibility: ensuring that errors in their design and analysis don't render pointless pain and death that they inevitably cause. Unfortunately, a considerable proportion - by some measures, a majority - of animal research studies fail this test. 

Science Fictions: How Fraud, Bias, Negligence, and Hype Undermine the Search for Truth by Stuart Ritchie. 

There is a common misconception that religion, socialism et al., are the only sources that unleash the pain, destruction, and death. No question they caused and still causing immense pain, destruction, and death but we conveniently forget the only common factor amongst these is humans. Science is no exception; last time I checked scientists are humans. 

Unless, we as a society at a meta-level change the incentives from money and fame to morality - this is not going to change. 

The road to hell is paved with good intentions.

- Henry G. Bohn, A Hand-Book of Proverbs

Ultra-Hyped Fields:

Stem cells, genetics, epigenetics, machine learning, and brain imagining; for the past few years, a strong contender for the 'most hyped' award has been research on the microbiome - the countless millions of microbes that inhabit our bodies. 

Perverse Incentives:

Because studies reporting positive, flashy, novel, newsworthy results are rewarded so much more than others, scientists are incentivized to generate them to the detriment of everything else. To convenience the reviewers and editors that their papers really do have all those qualities, too many of them end up bending or breaking the rules (of Mertonian norms of universalism, commonality, disinterestedness, and organized skepticism). 

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The system incentives scientists not to practice science, but simply to meet its own perverse demands. The incentives are at the root of so many of the dubious practices that undermine our research. 

Fixing Science:(addresses symptoms but not causes - which is basic human nature)

Some of the proposed solutions for the corresponding issues:

Fake data and negligence: Algorithms (services such as GRIM and Statcheck) do and could help with these issues. 

Novelty Bias: Journals should also publish null results and journals making the authors responsible for publishing further work checking whether it replicates. 

Statistical bias and p-hacking: Cannot remove them completely since its scary to move towards a subjective metric (current issue with nutrition studies), use more of the Bayesian approach (although the prior is subjective), and other metrics such as multi-verse analysis (if we imagine infinite parallel universes, in each of which you ran the analysis slightly differently, in what proportion of them would you find the complete opposite? Would all these analyses converge to the same overall result?)

Preprints and Pre-registration take out a lot of issues. Registering a study involves positing a public, time-stamped document online that details what the researchers are planning to do, in advance of collecting any data. It allows us to see the hypothesis the researchers intended to test, so we can check if any of them were switched mid-study. This is all about transparency. 

Replication crisis: Team Science - Large Collaborative Projects such as 'Plan S', and Open Access with funding from government and major funders, help force changes in research practice. These large-scale projects can directly address the applicability of their respective fields and because the results are being shared around a larger community of usually very opinionated scientists, they can also, in theory, act as a check on the biases of any individual scientist. 

Just as publishing more null results and replication studies is a more dependable way to build our knowledge, becoming more aware of the uncertain and preliminary nature of research is, in the long run, a better way to appreciate science fully. Let's work to resist our neophiliac, magpie-like focus on shiny research findings, and instead learn to value results that are solid, even if they're less immediately thrilling. In other words, let's Make Science Boring Again. 

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Treating each study as a tentative step towards an answer, rather than as the answer itself.

What I've Been Reading

Complexity science does study something distinctive - namely the emergent features of systems that are composed of a lot of components that interact repeatedly in a disordered way. The reason why it has been hard to identify what is distinctive about complex systems is that there are many different kinds of emergent properties and products of complex systems, and they are not all found in all complex systems. The common features of complex systems manifest themselves differently in different kinds of systems. 

What is a Complex System? by James Ladyman and Karoline Wiesner. 

This is one of the most important books you will read in your life. Developing even a rudimentary understanding of the complexity and complex systems will make one look at life differently (for good) plus it will help develop a sense of humility and gratitude for what we have without believing in magic and conspiracies. 

The complex system helps in understanding things such as how animals sufferings in factory farms will lead to a pandemic that could wipe out our species. 

Ladyman and Karoline attempt to "unpack" complex systems by avoiding biases put forth by existing researchers and keeping it open-ended as humanely as possible. They have also kept math and technical details to the minimum.  

They have done an enormous favor to a common reader by defining some of the salient features of the complex systems (not all always applies to all complex systems):

1. Numerosity: complex systems involve many interactions among many components. 
2. Disorder and diversity: the interactions in a complex system are not coordinated or controlled centrally, and the components may differ. 
3. Feedback: the interactions in complex systems are iterated so that there is feedback from previous interactions on a time scale relevant to the system's emergent dynamics. 
4. Non-equilibrium: complex systems are open to the environment and are often driven by something external. 
5. Spontaneous order and self-organization: complex systems exhibit structure and order that arises out of the interactions among their parts. 
6. Nonlinearity: complex systems exhibit nonlinear dependence on parameters or external drivers. 
7. Robustness: the structure and function of complex systems is stable under relevant perturbations. 
8. Nested structure and modularity: there may be multiple scales of structure, clustering, and specialization of function in complex systems. 
9. History and memory: complex systems often require a very long history to exist and often store information about history. 
10. Adaptive behavior: complex systems are often able to modify their behavior depending on the state of the environment and the predictions they make about it.

We argue that a system is complex if it has some or all of spontaneous order and self-organization, non-linear behavior, robustness history and memory, nested structure and modularity, and adaptive behavior. These features arise from the combination of the properties of numerosity, disorder and diversity, feedback, and non-equilibrium. We argue that there are different kinds of complex systems because some systems exhibit some but not all of the features. 

Chaos is not always complexity:

Complexity is often linked with chaos, and it may be conflated with it, but the behavior of a chaotic system is indistinguishable from random behavior. It is true that there are systems that exhibit complexity partly in virtue of being chaotic, but their complexity is something over and above their chaotic nature. Furthermore, since chaotic behavior is a special feature of some deterministic systems, any dynamical system that is stochastic is by definition not chaotic, and yet complexity scientists study many such systems. 

Measuring Complexity:

Ideas such as "logical depth" measure not complexity but order. Complexity is a multifaceted phenomenon and that complex systems have a variety of features not all of which are found in all of them. This implies that assigning a single number to complexity cannot do justice. 

A variety of different measures would be required to capture all our intuitive ideas about what is meant by complexity. 

- Physicist Murray Gell-Mann

In summary: 

There are many important theoretical questions on which complexity science bears, the most obvious ones concerned with relationships between life and nonliving matter, and between conscious and non-conscious matter. The general implication of our analysis for these matters is that the dichotomy between atoms and molecules and advanced life forms is a very crude way of seeing the many layers of structure that are found at different scales.  The only way to understand the emergence of life is by studying the processes that occur in self-organizing physical systems not just physical structures. 

Once the complexity of nonliving systems, such as the solar system and the Earth and its climate, is grasped in detail, the difference between life and non-life seems to be less of a mysterious leap and more of a continuum. 

When we think about complex systems in the right way, we can abstract from some of their features and understand the simplicity that underlies the wonderful complexity!

Shifting Baselines Syndrome

Similar to cockroaches, humans are extremely adaptable creatures in every direction of the spectrum.  Evolution gave us this adaptability so that if we lose an arm or eye, we can adapt quickly. I am still alive and drinking beer even though I am missing Max. It helps to keep us breathing. 

But the dark side of it maybe this makes most of us lack gratitude for what we have; we would rather lose everything and fight in a mad-max world than sacrifice a few stupid habits. It is scary! 

The "official" term for that is Shifting Baselines Syndrome:

David Wallace-Wells, author of the popular and terrifying climate change book The Uninhabitable Earth, discussed this possibility in a New York Magazine piece written during the apocalyptic fires late last year in Australia. One might have thought that fires consuming hundreds of millions of acres and killing more than a billion animals would be a wake-up call, but instead, Wallace-Wells writes, “a climate disaster of unimaginable horror has been unfolding for almost two full months, and the rest of the world is hardly paying attention.”

Maybe climate chaos, a rising chorus of alarm signals from around the world, will simply become our new normal. Hell, maybe income inequality, political dysfunction, and successive waves of a deadly virus will become our new normal. Maybe we’ll just get used to [waves hands] all this.

Humans often don’t remember what we’ve lost or demand that it be restored. Rather, we adjust to what we’ve got.

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So what are shifting baselines? Consider a species of fish that is fished to extinction in a region over, say, 100 years. A given generation of fishers becomes conscious of the fish at a particular level of abundance. When those fishers retire, the level is lower. To the generation that enters after them, that diminished level is the new normal, the new baseline. They rarely know the baseline used by the previous generation; it holds little emotional salience relative to their personal experience.

And so it goes, each new generation shifting the baseline downward. By the end, the fishers are operating in a radically degraded ecosystem, but it does not seem that way to them, because their baselines were set at an already low level.

Over time, the fish goes extinct — an enormous, tragic loss — but no fisher experiences the full transition from abundance to desolation. No generation experiences the totality of the loss. It is doled out in portions, over time, no portion quite large enough to spur preventative action. By the time the fish go extinct, the fishers barely notice, because they no longer valued the fish anyway.

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Even those big personal moments fade quickly. One of the most robust findings in modern psychology — made famous by Harvard psychologist Daniel Gilbert — is that we have an incredibly robust “psychological immune system.”

We tend to dramatically overestimate the effect that large events, good or bad, will have on our happiness. We think the death of a family member will make us enduringly less happy, or winning the lottery will make us enduringly happier. In fact, what psychologists find again and again is that we quickly return to our personal happiness equilibrium. A soldier who loses a leg and a soldier who returns home safe to a new baby will generally, a year or two later, be roughly as happy as they were before those events. It’s called “hedonic adaptation.”

Scientists Who Study Complex Systems Offer Solutions To The Pandemic

I have ranted a lot on complexity and complex systems in this blog. This week, I even said

Every school, every university, every office, and every household should learn about complex systems. You do too.

I have also ranted enough on "lock-in" syndrome where we get locked into a bad choice by sheer randomness. Think, if only Christianity emerged in Europe or North American or Asian where there is so much diversity of life instead of middle eastern deserts with only a few rodents then we wouldn't have these monolithic religions putting humans on the pedestal. By sheer, randomness we have to live with this bullshit probably for the remainder of this civilization.  Plus that "lock-in" happening in the middle eastern desert as far as we know might be the cause for the demise of this civilization.

Complexity scientists from Sante Fe Institute have finally broken their silence and have a good hypothesis:

The damage we are not attending to is the deeper nature of the crisis—the collapse of multiple coupled complex systems.

Societies the world over are experiencing what might be called the first complexity crisis in history. We should not have been surprised that a random mutation of a virus in a far-off city in China could lead in just a few short months to the crash of financial markets worldwide, the end of football in Spain, a shortage of flour in the United Kingdom, the bankruptcy of Hertz and Niemann-Marcus in the United States, the collapse of travel, and to so much more.

As scientists who study complex systems, we conceive of a complexity crisis as a twofold event. First, it is the failure of multiple coupled systems—our physical bodies, cities, societies, economies, and ecosystems. Second, it involves solutions, such as social distancing, that involve unavoidable tradeoffs, some of which amplify the primary failures. In other words, the way we respond to failing systems can accelerate their decline.

We and our colleagues in the Santa Fe Institute Transmission Project believe there are some non-obvious insights and solutions to this crisis that can be gleaned from studying complex systems and their universal properties. One useful way to think about a complexity crisis is in terms of the strategic tradeoffs that need to be managed and the complex mechanisms that these tradeoffs involve. These mechanisms include ideas of contagion, epidemic cycles, super-spreading events, critical phenomena, scaling, and path dependence.

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The processes of contagion, super-spreading, self-organized criticality, and urban scaling are all nonlinear and tend to result in multiple different outcomes or equilibria. One of the hallmarks of systems with multiple equilibria is path-dependence, meaning it is far easier to move in one direction than another. This often leads to “lock-in.” For example, it is well known that it’s easier to continue with an existing technology than adopt a newer and better one, such as the preference for silicon transistors over the superior metal oxide transistors in the early 1960s. And the same goes for social habits such as the continued preference for the QWERTY keyboard once it was widely adopted over all alternatives. And vastly more worrying is the lock-in around racial and gender-based hiring preferences which perpetuate an historical precedent rather than rewarding ability. The social habits we tend to see as either the fabric of society or unintended corollaries of social life—gathering at high-density, shaking hands as a greeting, traveling, and interacting when infectious—have become established as social norms. Path-dependence tells us that far more energy needs to be invested in campaigns to eliminate these habits than is required to perpetuate the habits.

[---] 

It is high time we attended to issues resulting from the long-term consequences of this crisis and its interconnection with all socio-economic life across the planet. We have modest understanding in these areas, and we are in desperate need of support and new ideas. In the future, we need to be thinking more about the threats of a full complexity crisis with all their attendant tradeoffs rather than the means of mitigating a single threat. The challenge for all healthy societies is deciding where to place the fulcrum that balances competing priorities and not treating priorities as if they were independent concerns. 

Please read the whole piece, it's enlightening.

What I've Been Reading

Everything I am now is because of Max. I had nothing when Max into my life, he gave me everything. Now, I have everything but I don't have Max. That's the irony and brutality life played with me. But that's how of the law of impermanence works.

People usually think my love for Max makes me say "everything I am now is because of Max." Yes, I love him more than anything but that sentence is also true without bringing love into picture. What we did together couldn't have happened if either of us were alone.

Our relationship is not transcendental (whatever that means) but it was more earthly which we don't comprehend yet.  I guess, my life is to meant to document what I experienced for future generations can use our relationship for lack of better term - a data point to comprehend these symbiotic relationships better. My aversion of individualist mindsets with me, me and more me world is hence visceral.

Merlin Sheldrake takes my collaborative and symbiotic relationship with Max to even more at a fundamental level and explains one of the most fundamental truths -  symbiotic relationships were the cause of life on earth in his book Entangled Life: How Fungi Make Our Worlds, Change Our Minds & Shape Our Futures.

Many of the most dramatic events on Earth have been - and continue to be - a result of fungal activity. Plants only made it out of the water around five hundred million years ago because of their collaboration with fungi, which served as their root systems for tens of million years until plants could evolve on their own. Today, more than ninety percent of plants depend on mycorrhizal fungi - from the Greek words for fungi (mykes) and root (rhiza) - which can link trees in shared networks sometimes referred to as the "wood wide web." This ancient association gave rise to all recognizable life on land, the future of which depends on the continued ability of the plants and fungi to form healthy relationships. 

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The study of relationships can be confusing. Almost all are ambiguous. Have leaf-cutter ants domesticated the fungus that they depend on, or has the fungus domesticated the ants? Do plants farm the mycorrhizal fungi that they live with, or do the fungi farm the plants? Which way does the arrow point? This uncertainty is healthy. 

Robert Macfarlane last year with this book Underland: A Deep Time Journey (which I still have to finish) opened our minds to new truths and in turn, his book turned out to be one of the top books of the 21st century.  Merlin Sheldrake repeats history this year with this book with this story of mycorrhizal networks.

One of my favorites and underutilized tools in the AI toolkit is Graph Network Algorithms. Little did I know that David Read, a mycorrhizal biologist, and his team unleashed the network science when in 1984, they showed that carbon could pass between normal plants through fungal connections. Thirteen years later, in 1997, Suzanne Simard replicated Read's findings in natural settings and coined the phrase "Wood Wide Web."

The World Wide Web appeared to have more in common with a cell or an ecological system than a Swiss watch. Today, network science is inescapable. Pick any field of study - from neuroscience, to biochemistry, to economic systems, disease epidemics, web search engines, machine learning algorithms that underpin much of AI, to astronomy and the very structure of the universe itself, a cosmic web crisscrossed with filaments of gas and clusters of galaxies - and the chances are that it makes sense of the phenomenon using a network model.

Simard's paper and her catchy concept of wood wide web found its way into James Cameron's Avatar as Pandora where symbiotic networks and relationships thrive.



It is an impossible task to review all the nuanced details Sheldrake covers in this book. I learned so many things on each and every page!

No kidding - the book closes with how language and analogies affect the research and understandings of mycorrhizal networks.

It's the narrative that we tell that needs to be examined. I'd really love to get past the language and try to understand the phenomenon. Once again, it may be more helpful to ask why this behavior has evolved in the first place: who stands to benefit.

Today, the study of shared mycorrhizal networks is one of the fields most commonly beset with political baggage. Some portray these systems as a form of socialism by which wealth of the forest can be redistributed. Others take inspiration from mammalian family structures and parental care, with young trees nourished by their fungal connections to older and larger "mother trees". Some describe networks in terms of "biological markets," in which plants and fungi are portrayed as rational economic individuals trading on the floor of an ecological stock exchange, engaging in "sanctions," "strategic trading investments," and "market gains."

Yes, it is that ridiculous and hilarious how our language biases us into mindless ideologies that affect our thinking and makes it close to impossible to change our minds.

On the positive note, the word "symbiosis" was coined by Albert Bernhard Frank in 1877 while describing the mutualistic relationship in lichens. There is an entire chapter on lichens in this book.

We need to learn to evolve our language as our understandings of realities evolves. Unfortunately, we are dwelling in the bed of Procrustes where we twist reality to fit into our stubborn and static world of languages.

One of the great mistakes I made because of my ignorance is not adding mushrooms to Max's diet regularly. I didn't know. But now, Fluffy, Garph, Neo, and I get our daily dose of mushrooms. This is how knowledge and truth works. A simple bayesian update to learn constantly, change the mind, and bring into action every day.

The bigger question is what other known unknowns I don't know yet?

Fluffy, Panopticon & An Unspoken Deal

In the process of growing up with Max, Fluffy absorbed lots of his mannerisms including for the lack of better term - "a basic sense of decency" from him as well.

When she was a kitten (and to date) she followed a lot of things Max did - she wants to be kissed before every meal, coming to the door when I get home to following me to bed to get her bedtime treats. I am so grateful when she does what she does... I get to see my Max in her.



During her early days, one thing that pissed her off big time was "inequality".

Why does Max get to go out and she doesn't? This sense of morality in her always reached its peak when Max went out in the backyard while she wasn't allowed.

I don't like cats roaming freely outside the house. In this country, pet cats kill 1.4 billion to 3.7 billion birds (not including the small mammals they kill) so I have a strict rule of not letting her (and Garph) roaming outside.

If you are surprised to see me use Fluffy, pissed, and inequality in the same sentence, Frans de Waal in his book Age of Empathy: Nature's Lessons for a Kinder Society covers a lot of ground on animal emotions.

Ultimately, I believe that reluctance to talk about animal emotions has less to do with science than religion. And not just any religion, but particularly religions that arose in isolation from animals that look like us. With monkeys and apes around every corner, no rain forest culture has ever produced a religion that places humans outside of nature. Similarly, in the East - surrounded by native primates in India, China, and Japan - religions don't draw a sharp line between humans and other animals. Reincarnation occurs in many shapes and forms: A man may become a fish and a fish may become God. Monkey god, such as Hanuman, are common. Only in Judeo-Christian religions place humans on a pedestal, making them the only species with a soul. It's not hard to see how desert nomads might have arrived at this view. Without animals to hold up a mirror to them, the notion that we're alone come naturally to them. They saw themselves as created in God's image and as the only intelligent life on earth. Even today, we're so convinced of this that we search for other such life by training powerful telescopes on distant galaxies.

When first live apes went on display, people couldn't believe their eyes. In 1835, a male chimpanzee arrived at London Zoo, clothed in sailor's suit. He was followed by a female orangutan, who was put in a dress. She called the apes "frightful, and painfully and disagreeably human." This was a widespread sentiment, and even nowadays I occasionally meet people who call apes "disgusting." When the same apes at the London Zoo were studied by the young Charles Darwin, he shared the queen's conclusion but without her revulsion. Darwin felt that anyone convinced of man's superiority ought to go take a look at these apes.

Frans de Waal TED talk on the moral behavior of animals covers exactly how animals get disturbed when they encounter inequality (the famous cucumber vs. grapes treats to monkeys).

This study became very famous and we got a lot of comments, especially anthropologists, economists, philosophers. They didn't like this at all. Because they had decided in their minds, I believe, that fairness is a very complex issue, and that animals cannot have it. And so one philosopher even wrote us that it was impossible that monkeys had a sense of fairness because fairness was invented during the French Revolution. 

I rest my case.

In time, Fluffy, and I came up with an unspoken deal. She can go out with Max if she stays in the patio without jumping outside. In the beginning, she used to run away, hid inside the bushes and I had to chase her to bring inside the house. But in time, with constant and immediate feedback, she learned. Her basic sense of decency inherited from Max came to rescue. She honored our unspoken deal.  She honors it to date.

People ask me how does she stay in the patio without jumping out like other cats? I have to put Garph on a leash in the patio (remember, he didn't grow up with Max) but he is getting better every day.

Of course, an easy and convenient answer of sapiens anchors towards anthropomorphism, and people give me all the credit.  I train them well or some other bullshit such as I am good with animals. That is not true.

The only credit that goes to me is that I signed that unspoken deal with Fluffy. Oxymoronically, the unspoken deal involves constantly talking to her. I talk to her like I do with any other person. If I sense that she is getting ready to jump out I would call out "Fluffy, no", "stop it", "you are not going that" and so on.

This would work when I am with her in the patio. But how does it work even when I am not in the patio and working inside the house? Fluffy has her cat instincts to pounce on a bird or squirrel in the backyard. How does control her innate instincts and respect our deal?

I have written reams and reams on how people cannot even control their gastro-intestinal pleasures and sponsor cruelty against animals. The same goes for other habits of mind such as religion, drinking, and the sheer inability of humans to change their minds. And here Fluffy, the cat is controlling her innate instincts.

Yes, a lot of the factors I mentioned above - Max, instant feedback,  and the unspoken deal helped. But I am a student of complexity and I don't like simple answers for complex questions. There must numerous other and subtle factors influencing her behavior.

It dawned on me last month that missed a huge factor, namely Panopticon:

The panopticon is a type of institutional building and a system of control designed by the English philosopher and social theorist Jeremy Bentham in the 18th century. The concept of the design is to allow all prisoners of an institution to be observed by a single security guard, without the inmates being able to tell whether they are being watched.

Yes, Jeremey Bentham's idea of panopticon changed the economics of prisons.  Most prisons including the design of the infamous Supermax Prisons in this country was influenced by panopticon.

The simple idea here is that there are more prisoners than guards. So one needs to create an illusion that guards are watching the prisons all the time. This, in turn, would force prisoners to behave. The prison buildings are designed to create that illusion.

 

It goes without saying that I would never treat Fluffy as a prisoner. It dawned on that the panopticon I created for Fluffy wasn't structural but oral. 

I would randomly call her name while I am working in the living room or while cooking in the kitchen or whatever else I am doing inside the house. These calls were never conscious nor regularly timed. I sporadically would call out her name and she has to come inside to show her face otherwise I would go to the patio. The sheer randomness of these calls created an illusion for her that she is being watched by me even though I am not anywhere near the patio. Maybe, this randomness also had a big influence on her honoring the deal we signed three years ago.

With little time and effort, now Fluffy can happily enjoy outdoors, the birds and squirrels are safe, and I am happy that she is safe away from the roads. It is as simple as that. There is no magic.  It just takes awareness, stepping outside of our self-centered life and seeing the world through their perspective.

Montaigne was the one who opened my eyes to the world of cats long before Fluffy came to my life.

Presumption is our natural and original disease. The most wretched and frail of all creatures is man, and withal the proudest. He feels and sees himself lodged here in the dirt and filth of the world, nailed and rivetted to the worst and deadest part of the universe, in the lowest story of the house, the most remote from the heavenly arch, with animals of the worst condition of the three; and yet in his imagination will be placing himself above the circle of the moon, and bringing the heavens under his feet. 'Tis by the same vanity of imagination that he equals himself to God, attributes to himself divine qualities, withdraws and separates himself from the crowd of other creatures, cuts out the shares of the animals, his fellows and companions, and distributes to them portions of faculties and force, as himself thinks fit. How does he know, by the strength of his understanding, the secret and internal motions of animals?—from what comparison betwixt them and us does he conclude the stupidity he attributes to them? When I play with my cat, who knows whether I do not make her more sport than she makes me? We mutually divert one another with our play. If I have my hour to begin or to refuse, she also has hers. 

- An Apology of Raymond Sebond, Michel de Montaigne

Please meditate on those beautiful lines from Montaigne written around the 1560s. He is telling us that we don't know shit about the secret lives, emotions, and intelligence (plus, myriad of other things) of animals but yet we think they are stupid. So who is stupid here?

What I've Been Reading

Skin in the Game: Hidden Asymmetries in Daily Life by Nassim Nicholas Taleb.

Brilliant :-)

1. The minority rule produces low variance outcomes.
2. Never compare a multiplicative, systemic, and fat-tailed risk to a non-multiplicative, idiosyncratic, and thin-tailed one.
3. Courage is when you sacrifice your own well-being for the sake of the survival of a layer higher than yours.
4. How much you truly "believe" in something can be manifested only through what you are willing to risk for it.
5. There is no love without sacrifice, no power without fairness, no facts without rigor, no statistics without logic, no teaching without experience, no complication without depth, no science without skepticism, and nothing without skin in the game.  

A great review here as well.

Law of Unintended Consequences With Complex Systems at Scale

- Via Here

How Life (and Death) Spring From Disorder

There’s a thermodynamic cost to storing information about the past that has no predictive value for the future, Still and colleagues show. To be maximally efficient, a system has to be selective. If it indiscriminately remembers everything that happened, it incurs a large energy cost. On the other hand, if it doesn’t bother storing any information about its environment at all, it will be constantly struggling to cope with the unexpected. “A thermodynamically optimal machine must balance memory against prediction by minimizing its nostalgia — the useless information about the past,’’ said a co-author, David Sivak, now at Simon Fraser University in Burnaby, British Columbia. In short, it must become good at harvesting meaningful information — that which is likely to be useful for future survival.

You’d expect natural selection to favor organisms that use energy efficiently. But even individual biomolecular devices like the pumps and motors in our cells should, in some important way, learn from the past to anticipate the future. To acquire their remarkable efficiency, Still said, these devices must “implicitly construct concise representations of the world they have encountered so far, enabling them to anticipate what’s to come.”

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Entropy maximization has long been thought to be a trait of nonequilibrium systems. But the system in this model obeys a rule that lets it maximize entropy over a fixed time window that stretches into the future. In other words, it has foresight. In effect, the model looks at all the paths the particles could take and compels them to adopt the path that produces the greatest entropy. Crudely speaking, this tends to be the path that keeps open the largest number of options for how the particles might move subsequently.

You might say that the system of particles experiences a kind of urge to preserve freedom of future action, and that this urge guides its behavior at any moment. The researchers who developed the model — Alexander Wissner-Gross at Harvard University and Cameron Freer, a mathematician at the Massachusetts Institute of Technology — call this a “causal entropic force.” In computer simulations of configurations of disk-shaped particles moving around in particular settings, this force creates outcomes that are eerily suggestive of intelligence.

In one case, a large disk was able to “use” a small disk to extract a second small disk from a narrow tube — a process that looked like tool use. Freeing the disk increased the entropy of the system. In another example, two disks in separate compartments synchronized their behavior to pull a larger disk down so that they could interact with it, giving the appearance of social cooperation.

Of course, these simple interacting agents get the benefit of a glimpse into the future. Life, as a general rule, does not. So how relevant is this for biology? That’s not clear, although Wissner-Gross said that he is now working to establish “a practical, biologically plausible, mechanism for causal entropic forces.” In the meantime, he thinks that the approach could have practical spinoffs, offering a shortcut to artificial intelligence. “I predict that a faster way to achieve it will be to discover such behavior first and then work backward from the physical principles and constraints, rather than working forward from particular calculation or prediction techniques,” he said. In other words, first find a system that does what you want it to do and then figure out how it does it.

Aging, too, has conventionally been seen as a trait dictated by evolution. Organisms have a lifespan that creates opportunities to reproduce, the story goes, without inhibiting the survival prospects of offspring by the parents sticking around too long and competing for resources. That seems surely to be part of the story, but Hildegard Meyer-Ortmanns, a physicist at Jacobs University in Bremen, Germany, thinks that ultimately aging is a physical process, not a biological one, governed by the thermodynamics of information.

- More Here

Wisdom Of The Week

The real obstacle is not financial. The financial resources needed are remarkably low and the return on small investments could be incalculably vast. We could significantly improve the decisions of the most powerful 100 people in the UK or the world for less than a million dollars (~£10⁶) and a decade-long project on a scale of just ~£10⁷ could have dramatic effects.

The real obstacle is not a huge task of public persuasion – quite the opposite. A government that tried in a disciplined way to do this would attract huge public support. (I’ve polled some ideas and am confident about this.) Political parties are locked in a game that in trying to win in conventional ways leads to the public despising them. Ironically if a party (established or new) forgets this game and makes the public the target of extreme intelligent focus then it would not only make the world better but would trounce their opponents.

The real obstacle is not a need for breakthrough technologies though technology could help. As Colonel Boyd used to shout, ‘People, ideas, machines – in that order!’

The real obstacle is that although we can all learn and study HPTs it is extremely hard to put this learning to practical use and sustain it against all the forces of entropy that constantly operate to degrade high performance once the original people have gone. HPTs are episodic. They seem to come out of nowhere, shock people, then vanish with the rare individuals. People write about them and many talk about learning from them but in fact almost nobody ever learns from them – apart, perhaps, from those very rare people who did not need to learn – and nobody has found a method to embed this learning reliably and systematically in institutions that can maintain it. The Prussian General Staff remained operationally brilliant but in other ways went badly wrong after the death of the elder Moltke. When George Mueller left NASA it reverted to what it had been before he arrived – management chaos. All the best companies quickly go downhill after the departure of people like Bill Gates – even when such very able people have tried very very hard to avoid exactly this problem.

Charlie Munger, half of the most successful investment team in world history, has a great phrase he uses to explain their success that gets to the heart of this problem:

‘There isn’t one novel thought in all of how Berkshire [Hathaway] is run. It’s all about … exploiting unrecognized simplicities… It’s a community of like-minded people, and that makes most decisions into no-brainers. Warren [Buffett] and I aren’t prodigies. We can’t play chess blindfolded or be concert pianists. But the results are prodigious, because we have a temperamental advantage that more than compensates for a lack of IQ points.’

The simplicities that bring high performance in general, not just in investing, are largely unrecognised because they conflict with many evolved instincts and are therefore psychologically very hard to implement. The principles of the Buffett-Munger success are clear – they have even gone to great pains to explain them and what the rest of us should do – and the results are clear yet still almost nobody really listens to them and above average intelligence people instead constantly put their money into active fund management that is proved to destroy wealth every year!

Most people think they are already implementing these lessons and usually strongly reject the idea that they are not. This means that just explaining things is very unlikely to work:

‘I’d say the history that Charlie [Munger] and I have had of persuading decent, intelligent people who we thought were doing unintelligent things to change their course of action has been poor.’ Buffett.

Even more worrying, it is extremely hard to take over organisations that are not run right and make them excellent.

‘We really don’t believe in buying into organisations to change them.’  - Buffett.

If people won’t listen to the world’s most successful investor in history on his own subject, and even he finds it too hard to take over failing businesses and turn them around, how likely is it that politicians and officials incentivised to keep things as they are will listen to ideas about how to do things better? How likely is it that a team can take over broken government institutions and make them dramatically better in a way that outlasts the people who do it? Bureaucracies are extraordinarily resistant to learning. Even after the debacles of 9/11 and the Iraq War, costing many lives and trillions of dollars, and even after the 2008 Crash, the security and financial bureaucracies in America and Europe are essentially the same and operate on the same principles.
Buffett’s success is partly due to his discipline in sticking within what he and Munger call their ‘circle of competence’. Within this circle they have proved the wisdom of avoiding trying to persuade people to change their minds and avoiding trying to fix broken institutions.

This option is not available in politics. The Enlightenment and the scientific revolution give us no choice but to try to persuade people and try to fix or replace broken institutions. In general ‘it is better to undertake revolution than undergo it’. How might we go about it? What can people who do not have any significant power inside the system do? What international projects are most likely to spark the sort of big changes in attitude we urgently need?

 - Unrecognised simplicities of effective action #1: expertise and a quadrillion dollar business