Observations

Summary:

  • We live at the border of order and disorder.
    • Sufficient order to exploit and sufficient disorder to explore.
    • Stability for survival and change and novelty for adaptation.
    • Maintaining any level of order requires constant energy.
  • We exploit order.
    • Certainty, predictability.
    • Maximizing efficiency.
    • Survival.
    • Fixed behavior, biases are productive.
  • We explore disorder.
    • Uncertainty, unpredictability.
    • Reducing uncertainty.
    • Adaptation.
    • Adjust behavior, actions, biases.
  • As we explore and exploit, progress emerges.
    • Progress emerges in the form of increasing complexity.
  • Continued progress requires some level of stability and cohesion.
    • Otherwise we are on shaky ground.
  • Threats to continued progress:
    • Increasing disorder: excess novelty, environmental change.
      • Response: keep it simple, re-think habits, adjust beliefs, social learning.
    • No adaptation: overly rigid beliefs.
      • Response: temporarily relax beliefs.
    • Increasing complexity.
      • Environments are becoming more unpredictable (more uncertainty).
      • Increased probability of winner-takes-all outcomes (less stability).
      • Limits to problem solving capacity (more uncertainty).
      • Easier to break stuff than fixing it (less stability).
      • Response: smaller scale, better stories (and conversations), updated institutions.
  • Other observations:
    • Fairness and inequality: people don’t want to lose stuff.
    • Maintaining order requires constant energy.
    • Economics is not a science.
    • It’s not nature versus nurture.

At the border of order and disorder

  • Life emerges at critical points. (“Complexity — David Krakauer, Part 3”)
    • The border of chaos and stability.
    • The right mix of order and chaos, rigidness and adaptability.
  • Life is imbalance: (“The Vital Question”)
    • The creation of order and resisting decay.
    • The interaction between forming structure and heating up the environment.
    • Energy generation, capture and usage: electron flow and proton power.
    • The most comfortable state.
  • Life is surprising. (“The information theory of individuality”)
    • Physics and chemistry are universal.
    • Biology may not be.
    • Working down (reduction) provides certainty: biology breaks down into physics and chemistry – nothing left.
    • Working up (emergence) is uncertain: difficult to predict
  • Life is self propagation and evolution. (“Complexity Explorer”)
    • Life is a self-propagating chemical system capable of undergoing adaptive evolution.
      • Self-propagating: growth and reproduction.
      • Adaptive evolution: potential to complexify and become more out-of-equilibrium.
      • Through mutation and selection.
      • Explains how more complex structures can arise over time.
  • Life is driven by internal and external constraints. (“Complexity — David Krakauer, Part 3”)
    •  Regulatory or energetic constraints limit possible outcomes.
    • External environmental constraints select fittest from possible outcomes.
    • Change in external constraints: explore previously unfit outcomes.
    • Change in external constraints: may change regulatory constraints.

Maintaining order requires constant energy

  • Order needs: (“Why Information Grows“)
    • Constant energy (to emerge).
    • The right type of matter (to last).
    • Predictable computation (to grow).
  • Keeping your house in order requires constant work.
    • Institutions, relationships, etc.

Exploiting order = certainty, predictability = efficient survival (biases are good) 

  • You need regularities in the environment. (“Life’s Information Hierarchy”)
    • Low variance, regularity in outcomes.
    • No regularities to “exploit” = no complex biological systems.
  • All cognition is a process of recognition. (“The Master and His Emissary“)
    • We recognize something only if we already have a model in our brain.
  • Regularities -> stable internal model -> intuitions, beliefs, knowledge, knowhow.
  • Internal models, beliefs -> prediction (intelligence). (“On Intelligence“)
    • A measure of the ability of a system to predict what happens next.
    • Not measured by actual behavior or actions.
    • Requires structured inputs: need for a patterned world.
  • Prediction is the verification of reality and the essence of understanding. (“On Intelligence“)
    • The odds that the same patterns occur randomly are low.
    • The repeated pattern must therefore exist (at least at our level of observation).
  • Predictive coding. (“How to Change Your Mind“)  (“REBUS“)
    • Used to predict what will happen next.
    • Objective: minimize errors between prediction and experience.
    • Efficient and optimized for survival.
    • Stimulates achievement.
    • Learn from the past, plan for the future.
  • Learning combines bottom-up classification and top-down pattern prediction. (“On Intelligence“)
    • Memory and learning are meaningless if inputs are random, without patterns.
    • Parts of our outside world need to have (repeating) structure to be predictable.
    • Used by all living systems to exploit the structure of the world.
  • Better prediction allows for handling more uncertainty and complexity. (“Prediction Machines“)
  • Better prediction drives more efficient survival, faster adaptation and increased complexity. (“Life’s Information Hierarchy”)
  • Improve predictions through trial and error, test and update. (“Complexity — David Krakauer, Part 4”)
  • Develop good models: (“Complexity — David Krakauer, Part 4”)
    • Priors: in order to interpret (noisy) data we need to have an expectation.
    • Simulation: in order to have an expectation we need rigorous simulation.
  • Priors, derived from experience of regularities over time, drive better prediction. (“Life’s Information Hierarchy”)
  • Error correction. (“EconTalk – Doug Lemov”)
    • Getting it wrong is the normal state of learning .
  • Decision-making is based on anticipated memories: (“Making Sense — Daniel Kahneman“)
    • Which experience is likely to produce the best memory.
    • Weighing anticipated regret versus anticipated satisfaction.
  • Survival and the winner effect. (“The Hour Between Dog and Wolf“)
    • Winners emerge with higher levels of testosterone, helping them win yet again.
  • Survival and the risk of ruin. (“EconTalk – Nassim Nicholas Taleb“)
    • Biases may seem irrational in isolated events, but can be rational over time if they allow you to avoid the risk of ruin in the long run.

Disorder = uncertainty = adaptation (need to adjust your actions, biases)

  • Brain is an uncertainty reduction machine. (“How to Change Your Mind“)
  • We evolved to pay attention to uncertainty, information. (“The Hour Between Dog and Wolf“)
    • Information: things we do not already know, novelty, uncertainty.
  • If you do not need to move, you do not need a brain. (“The Hour Between Dog and Wolf“)
    • Or, we only think when we are not good at an activity.
  • We evolved to seek out novelty. (“The Hour Between Dog and Wolf“)
    • Novel things are addictive (dopamine). (“The Hour Between Dog and Wolf“)
    • Dopamine: the desire for information and unexpected reward
    • The compensation we receive for valuable effort.
    • Rewards us for novel physical actions that lead to unexpected reward.
    • Pushes us beyond established routines to try new search patterns (optimism).
    • Curiosity itself, the need to know, can become a form of addiction.
    • We develop a preference for effortful consumption.
    • We don’t want to be fed, we want to hunt.
  • Explore uncertainty (“REBUS”):
    • Curious, novelty seeking behavior, inquiring state of mind.
    • Relaxation of priors for the sake of knowledge/learning.
  • Reduce uncertainty (“REBUS and the Anarchic Brain”):
    • Removing redundant parameters (unconsciously).
    • Revealing the underlying core structure.

As we exploit and explore, progress emerges: the world gets more complex

  • Complexity is not achieved by the number of parts, but by the organization of them (the structure of the network). (“The Gene“)
  • Accumulation of culture, knowledge and knowhow.
    • Crystallize information in the form of new objects and products that augment society, drive growth and complexity. (“Why Information Grows”)
    • The ever-increasing amount of culture is the biggest source of economic growth. (“Blueprint“)
    • The larger the group studying any problem, the faster the knowledge advances. (“Free Solo and Economic Growth“)
    • Diversity and complexity of a country’s industry is a strong predictor of its future growth. (“Why Information Grows”)
  • Larger wholes allow for increasing complexity.
    • Value of ideas: (“EconTalk — Paul Romer“)
      • Ideas are insights about how to rearrange the objects in the world.
      • More people = more insights = create new objects = more value/person.

Continued emergence of progress requires stability, cohesion

  • Progress is neither automatic nor mechanistic; it is rare. (“Peter Thiel’s Religion“)
  • Progress occurs when properties evolve and emerge that make doing the right thing for the group (societal good) the right thing for the individual (self-interest). (EconTalk — Agnes CallardEcon – Callard)
  • As individual humans interact in social groups that are sufficiently large and homogeneous, positive social properties may emerge.
    • Justice, norms, rights, institutions, culture.
  • These emerging properties over time feedback into the social group and affect individual behavior.
    • Influence individual decision making.
    • Allow for social learning
  • If social groups are sufficiently durable, over time complexity increases.
    • Social learning allows for cultural evolution.
  • If social groups lose their cohesion, emergent properties lose their relevance.
    • Abuse by one part of the group to exploit another.
    • As differences widen, further loss of cohesion.
    • What is good on average is no longer good for the whole.
    • Utilitarian principles are not as useful any more.
    • An “above zero” decision outcome is no longer a useful indicator of societal well-being if some groups are consistently left out.

Otherwise, we are on shaky ground

  • Lack of trust in experts, institutions
    • Institutions rely on faith in the strength of error correction mechanisms (to what degree are experts challenged). (“Making Sense — David Deutsch“)
    • Institutions require trust among its members (“EconTalk — Yuval Levin”)
      • If behavior is different from expectations, we lose trust in the institutions.
      • Current institutions were built to leverage mainstream collective action.
      • No more mainstream: fragmentation.
        • Technology has created many profitable, small worlds (in terms of financial rewards and status).
      • No more collective action: individualization.
        • Technology allows us to be functional loners (we don’t need to come together as much to achieve things).
  • Lack of morals, abuse, easy to cheat.
  • Lack of cohesion.
    • Differences within groups tend to be larger than differences between groups. (“The Gene“)
    • We are culturally inclined to magnify differences, even if they are minor. (“The Gene“)
  • Lack of stability. (“EconTalk — Branko Milanovic”)
    • Gig-jobs instead of normal jobs.
    • Societal changes.
    • Reduced role of family (incentives to form households have gone down).
    • Atomization of social life (individuals become private enterprises).
  • Lack of balance of pro- and anti-social behaviors. (“Blueprint“)
    • Evolving and interacting genetic and cultural forces prime human social behaviors.
    • Certain pro-social tendencies and capabilities shape the emergence of certain types of human social order.
    • We are capable of both pro- and anti-social behavior.
    • Various types of human behavior (cheating, punishing, cooperating, loners, etc.) co-exist and co-evolve, ensuring that no particular type will disappear or dominate the population.

Increasing disorder: excess novelty, changing environment.

  • Excess novelty causes stress. (“The Hour Between Dog and Wolf“)
    • Novel things can be bad (cortisol and chronic stress). (“The Hour Between Dog and Wolf“)
    • Novelty and uncertainty can also signal a threat and elicit a stress response.
    • Short-term, moderate stress exposure triggers focus heightened awareness.
    • Long-term, chronic stress response impairs cognitive functioning.
    • Thinking becomes more emotional, less factual (pessimistic, risk aversion).

Response to novelty: keep it simple, re-think habits, adjust beliefs, social learning

  • Certainty is acquired slowly. (“Complexity — David Krakauer, Part 1”)
    • Requires trial and error.
    • Tension between certainty needed to make decisions and uncertainty of predictions.
    • Bad science -> false certainty -> bad predictions -> loss of credibility.
  • Be tolerant of simplicity in times of uncertainty. (“Complexity — David Krakauer, Part 1”)
    • When data is bad, use simple models.
  • When environment changes, re-think your habits. (“Complexity — David Krakauer, Part 1”)
    • Habitual thinking exploits regularity.
    • If regularity disappears, drop associated automatic behaviors.
    • Analyze and build new habits (slowly).
  • Limiting novelty: use what you already know to gain insight about what you don’t. (“Complexity — David Krakauer, Part 1“)
  • Handling uncertainty is about manipulating beliefs. (“The Laws of Medicine“)
    • Predict: use and test your beliefs.
    • Be open: adjust your beliefs.
    • Be aware: beliefs have limits.
  • Be a better belief calibrator. (“Thinking in Bets“)
    • Test, adjust, be open.
  • Handling novel things as a positive challenge, not a threat (mental resilience). (“The Hour Between Dog and Wolf“)
    • Nature: balance of anabolic (testosterone) and catabolic hormones (cortisol), neurotransmitter profile, vagal tone (vagus nerve ability to reduce stress response).
    • Nurture: exposure to productive short-term stressors (exercise, cold), limitation of unnecessary stressors (uncertainty, lack of control).
  • If the environment changes so frequently that genetic evolution can’t provide the appropriate adaptation fast enough, cultural evolution through (brains capable of) social learning becomes more adaptive. (“Blueprint“)

No adaptation: trapped in rigid beliefs

  • We start adaptive (“How to Change Your Mind“).
    • Wide focus, disordered, diffused attention.
    • Less predictable answers, high error rates.
  • Over time, we become more rigid, preservation (“How to Change Your Mind“).
    • Spotlight, ordered, narrower focus.
    • More probable answers, lower error rates.
  • Maladaptive behaviors. (“How to Change Your Mind“)
    • Narrow or fixed perspectives, behaviors and emotional repertoires.
    • Negative thinking (stuck in the past or worried about the future).
    • Inverse learning (repeating the same destructive thoughts or behavior, thereby reinforcing (unproductive) neural connections).
  • We get trapped in thoughts. (“Waking Up“)
    • Thoughts themselves are not a problem, but being identified with your thoughts is and being lost in thoughts is.
    • We constantly create and repair a world that our minds want to be in.
    • Distraction is the normal condition of our minds.
  • We become overly confident. (“Making Sense – Shane Parrish“)
    • The smarter you are, the better story you’re going to tell yourself about why a bias doesn’t apply.
    • Biases create overconfidence about outcomes and worse decisions.
  • Higher IQ increases the risk of larger blind spots. (“Thinking in Bets“)
    • Better at constructing elaborate narratives supporting beliefs.
  • We can’t do it all on our own. (“EconTalk — Agnes Callard“)
    • Experiental learning limited by biases, prejudices and assumptions.
    • Even if you try to mitigate blind-spots, you are still governed by the same biases and assumptions.
    • You need others to ask the questions you are not asking.
    • Leverage social learning.

Response to no adaptation: temporarily relax your beliefs. 

  • Change your state of mind. (“How to Change Yousr Mind“)
    • Reduction of activity in the brain’s default mode network.
    • Reduction of top-down control (beliefs), increased access to bottom-up stimuli.
    • Flatten the grooves of habit, create new pathways of thought.
    • How: psychedelics, meditation, task-oriented behavior.
    • Meditation: (“Making Sense — Stephen Fry“)
      • A tool to train your mind.
      • Recognize and snap out of in-the-moment unproductive emotions.
    • Importance of serotonin. (“REBUS and the Anarchic Brain“)
      • Increased flow promotes adaptation to environmental uncertainty.
      • Creates “hot state” of cognitive flexibility and neuroplasticity.
      • More suggestible to influences from the environment (adaptation).

Environments are becoming more unpredictable (more uncertainty).

Increased probability of winner-takes-all outcomes (less stability).

  • Complex problems. (Complexity — David Krakauer, Part 5)
    • Broad averages are misleading.
    • Outcomes can be much more volatile than expected.
    • Need to understand local variation.
    • Need to present all possible outcomes.
  • The rich get richer, the fit get fitter (Linked.)
    • If a system grows and its parts sufficiently differ.
    • Most parts have only a few connections (friends).
    • Some have many (acquaintances).
  • The winner take all effect. (Finance — Geometric Balancing)
    • Averages becomes meaningless.
    • The few winners drive up the average.
    • Most of the outcomes are below the average.

Limits to problem solving capacity (more uncertainty).

  • Liberal democratic capitalism is ill equipped to handle major complex challenges. (“Conversations with Tyler — Slavoj Žižek”)
  • Our bias is preservation over adaptation (“REBUS and the Anarchic Brain”).
    • We prefer our high-level models and prior beliefs over data.
    • We are less efficient in a high change environment, uncertainty.
  • We are not built to handle long-term disturbances. (“The Hour Between Dog and Wolf“)
  • We are constrained by the limits of human nature / rationality / behavior / cognition. (“EconTalk — John Gray“)
  • (Understanding) complexity is restrained by the computing capacity of its elements. (“Why Information Grows”)
    • Human restrictions: we have to learn by doing (experiential) or from others (social).
    • Network restrictions: transaction costs, ability to form social bonds (trust).
  • Limits of (reductive) science.

Easier to break stuff than fixing it (less stability).

  • Complex problems are solvable, but there is no common, consensus solution. (EconTalk — Agnes Callard)
    • Just because a problem is solvable doesn’t mean it can be solved by someone other than you.
    • You have to do the work yourself.
    • Requires individual trial and error.
    • Creates a lot uncertainty.
    • For solving complex problems, difficult to trust anyone but yourself.
  • Complex problems require complex interventions. (Complexity — David Krakauer, Part 5)
    • We tend to collapse causality into single causes.
    • Important problems tend to be complex and rarely have simple causes.
    • We poorly understand how to resolve complex problems.
    • We typically don’t look for complex solutions as we prefer simple ones.
  • No unifying solutions. (Complexity — David Krakauer, Part 5)
  • Broken systems: (“Permanent Record“)
    • The people that make the rules have no incentive to act against them (and fix the system).
  • More complexity = easier to break than to fix. (“EconTalk — Martin Gurri”)
    • Easier to figure out what you are against, than what you are for.
    • Easier to break the system down, than to figure out how to fix it.

Response: smaller scale, better stories (and conversations), updated institutions

  • Reduce scale.
  • Circuit breakers. (“Circuit Breakers”)
    • Regulations tend to be optimized for everyday life.
      • Not for emergency situations (such as the current pandemic).
    • Fast, low-cost adaptation.
      • Immediate interruption of normal procedures.
      • Achieve maximum results when the costs for doing so are still low.
      • Normal regulations may get you to the same place, but much slower (too slow).
  • Better stories. (“Making Sense — Daniel Kahneman“)
    • Avoid stories that are remote and abstract.
  • Better conversations.
    • Ingredients for a healthy conversation: (“Making Sense — Jack Dorsey“)
      • Shared attention.
      • Shared reality.
      • Receptivity.
      • Variety of perspective.
      • (Risk of) Reputation.
    • Civility and compromise (EconTalk — Yuval Levin)
      • Compromise: disagree productively – the other side is not always the problem.
      • Civility: rooted in the premise that the people that I don’t like aren’t going anywhere.
  • Update institutions (“EconTalk — Yuval Levin”)
    • If there are no institutions, people don’t connect.
    • People only come together to do something.
    • Excessively high expectations of the individual.
    • Excessively low expectations of our institutions.

Fairness and inequality: people don’t want to lose stuff.

Capitalism, markets: work for everyone in the long run, hurt and displace some in the short run

  • Families versus societies: (“EconTalk — Jonah Goldberg“)
    • Families function under socialist norms (sharing, top down)
    • Societies function under capitalist norms (contractual, bottom up).
  • Markets are inventive, not necessarily efficient. (“EconTalk — Rory Sutherland“)
    • Solving the same problem for different people in different ways.
  • Long-term compounding, short-term aggregation: (“EconTalk — Arnold Kling“)
    • Long-term impact of compounding: ultimately, the boat rises for everyone.
    • Short-term impact of aggregation: in the short run, some are better off than others.
  • “Front row” and “back row”: (“EconTalk — Chris Arnade“)
    • Path to financial well-being is narrow, weaving through elite (educational) institutions.
    • Growing number of people lack access to this “credential machine”
  • Economic change and social disruption: (“EconTalk — Chris Arnade“)
    • Tension between the pace of economic change and social displacement.
    • Difficult to think through the first, second, third waves of (social) impact of economic changes.
    • If the pace of change is too fast, can be socially disruptive.

Economics is not a science

It’s not nature versus nurture

  • Start with nature. (“Superintelligence“)
    • Innate preferences shaped by natural, sexual and cultural selection.
    • Then, experience and interaction.
    • “Life events” (experience) shape human values.
  • It’s not nature vs. nurture. (“The Gene“)
    • Patterns evolve as nature and nurture interact with and influence each other iteratively over time.

Various

  • One gene: good and bad traits. (“Cellular Senescence“)
    • Antagonistic pleiotropy.
    • One gene is associated with good traits (usually early in life) and bad traits (usually later in life).
    • Example: senescent cells signal tissue repair early in life, but as they accumulate in old age lead to chronic inflammation
  • One trait: good at first, bad later. (“The Drive with Peter Attia — David Sabatini“)
    • One trait may be adaptive for survival early in life, but may become a threat to survival later in life.
    • Example: mTOR signaling high and productive early in life, but fails to slow down (and may increase) with age.
  • Happiness versus satisfaction: (“Making Sense — Daniel Kahneman“)
    • In the moment happiness: social, love, etc.
    • Retrospective satisfaction: achievements, rewards, success
  • Love is wanting the best possible outcome for someone. (“12 Rules for Life“)
  • Individuals and organizations: (“The Spy and the TraitorThe Spy and the Traitor“)
    • People hurt by fate or nature.
    • Crave power and influence, but defeated by unfavorable circumstances.
    • Belonging to a powerful organization provides feeling of superiority.
  • Totalitarian regimes: (“The Spy and the Traitor“)
    • The interests of society come before personal welfare.
    • Betrayal for the greater good is the mark of ideological purity.
    • When honest failure is punished, do nothing and hope the problem will go away.
  • When we pursue optionality, we avoid bold decisions. (“Peter Thiel’s Religion“)
  • Friendship: (“Blueprint“)
    • Non-conditional exchanges that are tracked over time and build relationships that provide insurance against setbacks and lay the foundation for many other pro-social traits.
  •  Brands: (“EconTalk — Rory Sutherland)
    • Provide certainty of limited downside.
  • Technological progress: (“Permanent Record“)
    • If something is technologically feasible, it will likely happen.
  • Access to information. (“Permanent Record“)
    • Within an organization often disproportionate to formal authority and ability to influence decisions.
  • Artificial intelligence: all plausible scenarios (counter-intuitive, outliers). (“The Sentient Machine“)
    • Fewer size restrictions (ability to scan and hold complete solution landscapes).
    • Potential for inputs from a broader range of sensors.
    • Higher processing speed.

Quotes:

  • “You go after the king, you best not miss.” (unknown, “Bad Blood“)
  • “Be polite, be professional, but have a plan to kill everybody you meet.” (James Mattis, “Bad Blood“).

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