Nassim Nicholas Taleb (Scholar Investor) – Small is Beautiful – But Also Less Fragile | NYU Urban Management (Dec 2014)
Chapters
00:00:12 An Exploration of Fragility, Anti-Fragility, and Allometry in Complex
Fragility: Fragility is defined as a property of systems or objects that dislike disorder and are negatively affected by random events. Fragile systems experience only neutral or negative outcomes from events, making them vulnerable to harm.
Size and Fragility: As systems grow in size, they become more fragile due to their inability to handle disorder effectively. This is evident in the nonlinear relationship between metabolic rate and size in animals, where larger animals have a higher metabolic rate and are more susceptible to harm.
Anti-fragility: Anti-fragility is the opposite of fragility and refers to systems that benefit from disorder and uncertainty. Anti-fragile systems thrive in chaotic environments and gain from random events. Anti-fragility is associated with properties such as uncertainty, variability, and time.
Organic vs. Engineered Systems: Organic systems, such as biological organisms, are anti-fragile and benefit from moderate amounts of disorder. Engineered systems, such as machines and technology, are fragile and do not benefit from disorder. Organic systems can adapt and improve through exposure to stress, while engineered systems tend to break down.
Precautionary Principle against GMOs: Taleb highlights the tendency of people to comment on topics without fully understanding them, as seen in the case of GMOs. He criticizes the precautionary principle against GMOs, arguing that it is often based on misconceptions and a lack of scientific evidence.
00:10:34 Organic and Engineered: A Complex System's Perspective
Risk and Variability: Variability is not synonymous with risk, and controlling variability does not control risk. Economic systems, like complex organic systems, need variability and shocks to clean up bad companies and probe uncertainty.
Over-Intervention and Stability: Over-intervention in complex systems can lead to apparent stability, but this stability is often illusory and can lead to collapse. Low variability and overstability can be indicators of fragility and impending collapse.
Post-traumatic Growth: Post-traumatic growth, or the ability to bounce back from trauma and overcompensate, is often overlooked compared to post-traumatic disorder. This phenomenon is rarely addressed due to lack of financial incentive for its treatment.
City-States and Overcompensation: Some city-states have achieved wealth and prosperity by overcompensating for their lack of resources through trade and innovation. This overcompensation may be related to post-traumatic growth and the Lindy effect, which states that things that have survived a long time are likely to continue to survive.
Scale and Governance: Governance systems and political systems do not scale linearly. Smaller entities like Singapore and Venice may have different governance systems than larger entities like China and Saudi Arabia, and these differences cannot be directly compared.
Non-linearity and Fragility: Fragility is easily detectable by observing the relationship between the magnitude of harm and the severity of the punishment. Anything alive has a sensitivity to uncertainty, and fragility is a measure of this sensitivity. Sigma, a measure of uncertainty, is always associated with time in economics and physics, except in a few exceptions.
00:21:26 The Nonlinearity of Harm: Convexity Effects and Stochastic Diseconomies of Scale
Summary of Key Insights: The concept of “fragility” can be defined based on a measure of uncertainty. Distributed systems often fare better than centralized systems due to their resilience to shocks. The Kerviel banking scandal illustrates the potential consequences of centralized systems. Nonlinear systems are more sensitive to large deviations than linear systems. Surviving systems are sensitive to large deviations, while small deviations are less harmful. Economies of scale have limits, and large organizations may experience diseconomies of scale due to increased fragility. Cost overruns and execution challenges in large projects exhibit a nonlinear relationship with project size. Smaller political units may have an advantage due to their resilience to shocks and ability to handle uncertainty.
00:28:21 Nature's S-Curves: Understanding Convexity and Concavity in Nonlinear Responses
Second Order Effects: Fragility emphasizes the importance of second-order effects and nonlinearities, which are often overlooked in traditional risk assessment.
Convexity and Concavity: Systems with convex properties benefit from uncertainty in a certain range, while concave systems are more susceptible to fragility.
Tower of Babel: The Tower of Babel analogy illustrates that large, complex systems can be more fragile than smaller, simpler ones.
Fragility and Second Order Effects: Fragile systems are more sensitive to second-order effects than first-order effects, meaning that the consequences of small changes can be significant.
S-Curve in Nature: Many natural systems exhibit an S-shaped response curve, with a convex phase where volatility is beneficial and a concave phase where it is detrimental.
Convexity in Medical Treatments: Medical treatments with nonlinear responses can benefit from uncertainty and randomness, suggesting that varying treatment doses may lead to improved outcomes.
Evidence for Antifragility: Evidence for antifragility can be found in various fields, including medicine, where studies have shown that varying treatment doses can improve patient outcomes.
Understanding Fragility: Fragile systems are vulnerable to uncertainty, variability, and shocks. Time can provide valuable insights into a system’s ability to handle disorder.
The Lindy Effect: Older technologies and systems tend to be more robust and resilient than newer ones. The longer something survives, the more likely it is to continue surviving. This effect is observed in various domains, including technology, politics, and culture.
Examples of Resilient Technologies and Cities: The car has remained a dominant mode of transportation despite numerous attempts to replace it. The airplane and bicycle are also examples of enduring technologies. City-states have historically proven to be more resilient than centralized nation-states. Ancient technologies, such as the fork, have survived for millennia and continue to be used today.
The Importance of Dimensionality: Humans are drawn to environments with high dimensionality, which offer complexity and variety. This preference for dimensionality is reflected in our appreciation for intricate architecture, art, and natural landscapes.
Conclusion: Fragility is a crucial concept for understanding the resilience of systems and technologies. Ancient technologies and cities offer valuable lessons about what works and what lasts. Our preference for dimensionality shapes our perception of beauty and our desire for complex environments.
00:43:14 Economics: A Robust System Despite Imperfect Economists
Technology and Its Origins: Technology is often mistakenly seen as the application of science to practical problems. In reality, science tends to come from technology, not the other way around. Examples like Euclidean geometry illustrate how science can sometimes be a hindrance to progress.
The Limitations of Economists: Economists are often unable to provide wise guidance, despite efforts by individuals like Bill Easterly to improve the field. Relying on economists to make wise decisions is not a reliable strategy.
Building Robust Systems: The focus should be on building systems that can withstand the mistakes made by economists. One approach is to profit from the mistakes economists make, although this can be challenging. Ultimately, the goal is to create a world with built-in robustness to errors made by professionals.
The Role of City States: City states, with their smaller size and distributed decision-making, allow for greater robustness. This distributed decision-making helps to mitigate the negative impact of errors made by individuals.
Conclusion: It is unrealistic to expect economists to suddenly become wise and provide infallible guidance. The focus should be on building systems that can handle the mistakes made by economists and creating a world with built-in robustness. City states, with their distributed decision-making, can serve as models for this approach.
00:45:24 Predicting the Future by Understanding the Past
Visualizing the Future by Eliminating Past: To predict the future, one should examine the past and remove elements from the present that were present in the past 20 years. This approach helps in identifying what is likely to continue existing in the future rather than predicting specific technological advancements.
Architecture and Organic Change: Modern architecture tends to favor natural elements with added dimensionality. Preserving historical neighborhoods can lead to stagnation and hinder organic transformation. Top-down solutions often result in aesthetically unappealing urban landscapes.
Nature’s Organic Progression: Nature is not conservative; it destroys and creates, leading to progress. Progress in nature occurs locally and through evolution, not through centralized control. Creating conditions for organic growth is essential for sustainable urban development.
Buildings as Time Capsules: Buildings reflect the evolution of societies over time. Architectural styles change and adapt to changing needs and preferences.
00:48:06 Second-Order Effects: Intuition, Psychology, and Model Complexity
Convexity and Risk: Owning property in a city can provide more upside potential but less downside protection compared to renting. Buying in cities with excessive ornamentation and inequality is not a wise investment.
Second-Order Effects and Intuition: Second-order effects are crucial but often overlooked in decision-making. Intuition incorporates second-order effects, which can lead to more accurate judgments.
Critique of Psychologists and Rational Analysis: Psychologists often focus on first-order effects, leading them to underestimate large deviations and risks. So-called rational analysis is not truly rational due to incomplete models and the omission of second-order effects.
Hyperbolic Discounting and Nudge Theory: Hyperbolic discounting is not necessarily irrational; it can be explained by considering second-order effects. Nudge theory often suggests the opposite of what should be done due to its reliance on incomplete models.
Convexity and Investment Decisions: The choice between stocks and bonds depends on the model used. Using a mean-variance distribution may lead to a preference for stocks, while a fat-tailed model may suggest investing in bonds.
Big Data and Spurious Correlations: Big data can lead to spurious correlations due to the large number of variables and observations. The number of fake correlations generated in a random matrix increases with the number of variables and observations.
Statistical Significance: Statistical significance is the probability of obtaining a result as extreme as or more extreme than the observed result, assuming that the null hypothesis is true. Statistical significance is important because it helps researchers determine whether their results are due to chance or to a real effect. Statistical significance grows at the rate of the square root of n, where n is the sample size.
The Problem with Big Data: As the number of variables in a dataset increases, the number of possible correlations between those variables increases non-linearly. This means that, with a large enough dataset, it is almost impossible not to find some correlations that are statistically significant. However, these correlations may be due to chance rather than to a real relationship between the variables.
The Solution: One way to avoid the problem of spurious correlations is to reduce the dimensionality of the dataset by pre-specifying the thing of interest. This means only looking for correlations between variables that are known to be related. Another way to avoid the problem of spurious correlations is to use clinical trials rather than statistical analysis.
Conclusion: Big data can be a useful tool for research, but it is important to be aware of the potential problems associated with it. Researchers need to be careful not to overinterpret the results of statistical analysis and to use clinical trials to confirm their findings.
The Impact of State Control on Urban Development: State control and top-down planning lead to an allergy for variability, resulting in the compression of variation and a loss of resilience.
The Example of Aleppo: Aleppo was once a wealthy city, richer than many Western cities in Europe, due to its system of city states and its ability to handle invaders. Aleppo’s prosperity declined with the arrival of the state, which replaced the organic development of the city with centralized planning and control.
Preservationists’ Understanding of the Lindy Effect: Preservationists recognize that what has survived the longest is likely to continue to be valuable, but they may lack a framework for explaining this phenomenon.
The Link Between Aesthetics and Longevity: The author cautions against using personal aesthetics to judge the value of a city, as what one person finds attractive may not be appealing to others.
The Bias Against Variability in Western Society: Western society exhibits a cultural bias against variability, which is associated with shame and a preference for uniformity and control.
The Resilience of Ancient Urban Design: Ancient cities like Damascus and Beirut have survived for thousands of years due to their villagey appearance and preservation of traditional neighborhoods. These cities have adapted to earthquakes and other challenges by rebuilding along existing lines, rather than completely redesigning them.
The Decline of Ancient Cities: The prosperity of ancient cities declined with the arrival of the state, which imposed centralized control and stifled the organic development of the city.
Abstract
The Resilience and Fragility of Systems: Insights from Nassim Nicholas Taleb
Understanding Fragility and Anti-Fragility in a Complex World
In a world defined by uncertainty and complexity, the concepts of fragility and anti-fragility, as introduced by Nassim Nicholas Taleb, hold increasing relevance. Fragility, defined as an object’s aversion to disorder or random events, impacts various aspects of life, including time, variability, and size. Fragile systems experience only neutral or negative outcomes from events, making them vulnerable to harm. In contrast, its opposite, anti-fragility, thrives on disorder and benefits from random events, representing a fundamental aspect of organic systems, such as the human body, which adapt and grow stronger from stressors. In contrast, non-organic systems, like machines, deteriorate under stress.
Second-order effects, often overlooked in traditional risk assessments, are pivotal to understanding fragility. Fragile systems are more sensitive to second-order effects than first-order effects, implying that the consequences of small changes can be significant. Convex systems benefit from uncertainty in a certain range, while concave systems are more susceptible to fragility. The Tower of Babel analogy illustrates that large, complex systems can be more fragile than smaller, simpler ones.
Visualizing the Future by Eliminating Past:
To predict the future, one should examine the past and remove elements from the present that were present in the past 20 years. This approach helps in identifying what is likely to continue existing in the future rather than predicting specific technological advancements.
The Intrinsic Nature of Fragility and Its Implications
Fragility is a universal property of living systems, sensitive to uncertainty and increasing with the size of a shock or stressor. It is crucial in understanding the dynamics of different systems, whether organic or engineered. Engineered systems, designed top-down, often fail to account for the organic complexity that allows organic systems to respond and adapt through bottom-up processes. This distinction is pivotal in fields ranging from economics to urban planning and medicine. Organic systems, such as biological organisms, are anti-fragile and benefit from moderate amounts of disorder. Engineered systems, such as machines and technology, are fragile and do not benefit from disorder. Organic systems can adapt and improve through exposure to stress, while engineered systems tend to break down.
Architecture and Organic Change:
Modern architecture tends to favor natural elements with added dimensionality. Preserving historical neighborhoods can lead to stagnation and hinder organic transformation. Top-down solutions often result in aesthetically unappealing urban landscapes.
Time provides valuable insights into a system’s ability to handle disorder. The Lindy effect suggests that the life expectancy of a technology or idea increases with its age. Taleb’s observation that older technologies like cars, planes, and bicycles adapt over time, while newer technologies are more likely to be supplanted, underscores the importance of time-tested systems and designs. This principle is also evident in the resilience of city-states, which have historically shown an ability to adapt and innovate in the face of challenges.
Nature’s Organic Progression:
Nature is not conservative; it destroys and creates, leading to progress. Progress in nature occurs locally and through evolution, not through centralized control. Creating conditions for organic growth is essential for sustainable urban development.
The Role of Scale and Response to Stress
The size of a system plays a crucial role in its fragility. As entities grow larger, they tend to become more fragile, a phenomenon evident in the nonlinear relationship between metabolic rate and size in animals. This relationship extends to various systems, including economic and urban frameworks. For instance, the overcompensation in response to stressors can lead to positive outcomes like economic growth, but it also highlights the importance of scale in governance and system behavior. As systems grow in size, they become more fragile due to their inability to handle disorder effectively. This is evident in the nonlinear relationship between metabolic rate and size in animals, where larger animals have a higher metabolic rate and are more susceptible to harm.
The S-curve in nature demonstrates that many natural systems exhibit a convex phase where volatility is beneficial and a concave phase where it is detrimental. Medical treatments with nonlinear responses can benefit from uncertainty and randomness, suggesting that varying treatment doses may lead to improved outcomes. Evidence for antifragility can be found in various fields, including medicine, where studies have shown that varying treatment doses can improve patient outcomes.
Buildings as Time Capsules:
Buildings reflect the evolution of societies over time. Architectural styles change and adapt to changing needs and preferences.
Redefining Risk and Variability
The conventional understanding of risk and variability often conflates the two, overlooking their distinct natures. Controlling variability does not necessarily control risk, and in some cases, eliminating variability can lead to system collapse. Economic systems, like complex organic systems, need variability and shocks to clean up bad companies and probe uncertainty. This insight is crucial in project management and policymaking, where understanding the convexity effect and the existence of stochastic diseconomies of scale can inform more effective and resilient strategies.
Convexity and Risk:
Owning property in a city can provide more upside potential but less downside protection compared to renting. Buying in cities with excessive ornamentation and inequality is not a wise investment.
Post-Traumatic Growth and System Robustness
The concept of post-traumatic growth, where individuals or systems emerge stronger after trauma, contrasts with the more commonly discussed post-traumatic stress disorder. This concept is integral to the idea of anti-fragility, where systems benefit from stressors and uncertainties. In the context of financial systems and organizations, designing structures to be resilient to large shocks can significantly enhance their robustness and performance. Post-traumatic growth, or the ability to bounce back from trauma and overcompensate, is often overlooked compared to post-traumatic disorder. This phenomenon is rarely addressed due to a lack of financial incentive for its treatment.
Second-Order Effects and Intuition:
Second-order effects are crucial but often overlooked in decision-making. Intuition incorporates second-order effects, which can lead to more accurate judgments.
The Lindy Effect and the Evolution of Technologies and Cities
The Lindy effect, suggesting that the life expectancy of a technology or idea increases with its age, plays a critical role in understanding system resilience. Taleb’s observation that older technologies like cars, planes, and bicycles adapt over time, while newer technologies are more likely to be supplanted, underscores the importance of time-tested systems and designs. This principle is also evident in the resilience of city-states, which have historically shown an ability to adapt and innovate in the face of challenges. Some city-states have achieved wealth and prosperity by overcompensating for their lack of resources through trade and innovation. This overcompensation may be related to post-traumatic growth and the Lindy effect, which states that things that have survived a long time are likely to continue to survive.
The importance of dimensionality cannot be understated. Humans are drawn to environments with high dimensionality, which offer complexity and variety. This preference for dimensionality is reflected in our appreciation for intricate architecture, art, and natural landscapes.
Critique of Psychologists and Rational Analysis:
Psychologists often focus on first-order effects, leading them to underestimate large deviations and risks. So-called rational analysis is not truly rational due to incomplete models and the omission of second-order effects.
Challenging Conventional Wisdom in Economics and Urban Design
Economics, often perceived as a fragile discipline due to its reliance on models and assumptions, faces challenges in capturing real-world dynamics. Similarly, urban design, influenced by personal aesthetics and cultural biases, can either contribute to or detract from a city’s resilience. Taleb’s critique extends to the approach of academia and policymaking, where a bottom-up approach and recognition of the importance of distributed decision-making can lead to more robust and adaptable systems. Distributed systems often fare better than centralized systems due to their resilience to shocks. The Kerviel banking scandal illustrates the potential consequences of centralized systems. The precautionary principle against GMOs is based on misconceptions and a lack of scientific evidence.
Hyperbolic Discounting and Nudge Theory:
Hyperbolic discounting is not necessarily irrational; it can be explained by considering second-order effects. Nudge theory often suggests the opposite of what should be done due to its reliance on incomplete models.
Technology and its origins are often misunderstood. Technology is often mistakenly seen as the application of science to practical problems. In reality, science tends to come from technology, not the other way around. Examples like Euclidean geometry illustrate how science can sometimes be a hindrance to progress. The limitations of economists are evident in their inability to provide wise guidance, despite efforts by individuals like Bill Easterly to improve the field. Relying on economists to make wise decisions is not a reliable strategy. Instead, the focus should be on building systems that can withstand the mistakes made by economists. One approach is to profit from the mistakes economists make, although this can be challenging. Ultimately, the goal is to create a world with built-in robustness to errors made by professionals. The role of city-states, with their smaller size and distributed decision-making, allow for greater robustness. This distributed decision-making helps to mitigate the negative impact of errors made by individuals.
Convexity and Investment Decisions:
The choice between stocks and bonds depends on the model used. Using a mean-variance distribution may lead to a preference for stocks, while a fat-tailed model may suggest investing in bonds.
The Impact of State Control on Urban Development
– State control and top-down planning lead to an allergy for variability, resulting in the compression of variation and a loss of resilience.
– Aleppo was once a wealthy city, richer than many Western cities in Europe, due to its system of city states and its ability to handle invaders.
– Aleppo’s prosperity declined with the arrival of the state, which replaced the organic development of the city with centralized planning and control.
– Preservationists recognize that what has survived the longest is likely to continue to be valuable, but they may lack a framework for explaining this phenomenon.
– The author cautions against using personal aesthetics to judge the value of a city, as what one person finds attractive may not be appealing to others.
– Western society exhibits a cultural bias against variability, which is associated with shame and a preference for uniformity and control.
– Ancient cities like Damascus and Beirut have survived for thousands of years due to their villagey appearance and preservation of traditional neighborhoods.
– These cities have adapted to earthquakes and other challenges by rebuilding along existing lines, rather than completely redesigning them.
– The prosperity of ancient cities declined with the arrival of the state, which imposed centralized control and stifled the organic development of the city.
Embracing Uncertainty for a More Resilient Future
The insights from Nassim Nicholas Taleb’s exploration of fragility and anti-fragility provide a comprehensive framework for understanding and designing systems that can thrive in an uncertain world. By recognizing the nuances of risk, variability, scale, and the role of time, we can create more resilient and adaptable structures, whether in economics, urban planning, or technology. This paradigm shift towards embracing uncertainty and complexity not only challenges conventional wisdom but also opens new pathways for innovation and progress.
Big Data and Spurious Correlations:
– Big data can lead to spurious correlations due to the large number of variables and observations. The number of fake correlations generated in a random matrix increases with the number of variables and observations.
Statistical Significance and Big Data: Convexity vs. Concavity:
– Statistical significance is important, but it can be misleading with big data. As the number of variables and observations increases, the number of statistically significant correlations also increases, even if there is no real relationship between the variables. This is because statistical significance is based on the probability of obtaining a result as extreme as or more extreme than the observed result, assuming that the null hypothesis is true. However, with a large enough dataset, it is almost impossible not to find some correlations that are statistically significant.
Taleb and Kahneman's theories explore uncertainty, decision-making, and the human psyche, emphasizing the limitations of predictive models and the value of heuristics and intuition in navigating complex situations. Antifragility, the ability of systems to benefit from stressors, is contrasted with fragility and robustness....
Fragility is the susceptibility to harm from disorder or stress, while antifragility is thriving and growing stronger from disorder or stress. The triad of fragility, robustness, and antifragility can aid decision-making in a complex and uncertain world....
Systems can be fragile, harmed by stressors, or antifragile, benefiting from volatility; measuring fragility and antifragility helps understand resilience and decision-making....
Anti-fragility is the ability of systems to thrive and benefit from volatility, uncertainty, and stressors, rather than merely withstanding them. It challenges conventional wisdom by suggesting that we can create systems and societies that not only survive but also flourish in the face of unpredictable events....
Anti-fragility, the ability to thrive from disorder, contrasts with fragility, which leads to breakage under stress. Decentralization and frequent small crises promote resilience and stability in systems....
Nassim Nicholas Taleb's philosophies emphasize embracing variability, anti-fragility, and ethical decision-making to build resilient individuals and societies capable of thriving in uncertain times. His ideas challenge conventional wisdom and promote decentralized structures, accountability, and open dialogue....
Optionality enables flexibility, risk mitigation, and the exploration of opportunities, while anti-fragility allows systems to thrive in uncertain and volatile environments by benefiting from shocks and stressors....