The document presents a formalized version of the precautionary principle that distinguishes between regular risk and the risk of total ruin or systemic harm. It argues the precautionary principle should only be applied in cases of potential ruin, not regular risk. Ruin involves irreversible harm to an entire system, while regular risk involves localized harm. The risk of ruin justifies a precautionary approach rather than cost-benefit analysis, since the potential harm of ruin is effectively infinite. The document also discusses how complex systems can exhibit unpredictable "fat tail" behaviors that increase the risk of unforeseen ruin.
The document analysis the concepts of vulnerability, resilience and adaptive capacity and how useful can they be to study small states. It also discuss alliances as possible strategies for small states to survive and participate in the international system.
The document analysis the concepts of vulnerability, resilience and adaptive capacity and how useful can they be to study small states. It also discuss alliances as possible strategies for small states to survive and participate in the international system.
DRIE Central Luncheon, June 2011
Presenter: Michael Dudley, Research Associate, Institute of Urban Studies, University of Winnipeg
How many recent natural disasters that have befallen
metropolitan areas in the past several years (forest fires, floods and earthquakes) aren't so much "natural" but are instead the result of (or
exacerbated by) poor planning decisions in the past, such as building on flood plains and other vulnerable locations, but that our "psychology of
previous investment" prevents us from altering our building patterns? As well, our rigid, centralized "big pipes" approach to city building,
infrastructure and commodities makes our cities vulnerable to shocks and
system breakdowns, such as those associated with energy prices and availability. The presentation will argue for the incorporation of resilience principles in urban planning, which in many ways will mean a return to historical practices and forms.
DRIE Central Luncheon, June 2011
Presenter: Michael Dudley, Research Associate, Institute of Urban Studies, University of Winnipeg
How many recent natural disasters that have befallen
metropolitan areas in the past several years (forest fires, floods and earthquakes) aren't so much "natural" but are instead the result of (or
exacerbated by) poor planning decisions in the past, such as building on flood plains and other vulnerable locations, but that our "psychology of
previous investment" prevents us from altering our building patterns? As well, our rigid, centralized "big pipes" approach to city building,
infrastructure and commodities makes our cities vulnerable to shocks and
system breakdowns, such as those associated with energy prices and availability. The presentation will argue for the incorporation of resilience principles in urban planning, which in many ways will mean a return to historical practices and forms.
Existential Risk Prevention as Global PriorityKarlos Svoboda
•Existential risk is a concept that can focus long-term global efforts and sustainability concerns.
• The biggest existential risks are anthropogenic and related to potential future technologies.
• A moral case can be made that existential risk reduction is strictly more important than any other global public
good.
• Sustainability should be reconceptualised in dynamic terms, as aiming for a sustainable trajectory rather than a sustainable state.
• Some small existential risks can be mitigated today directly (e.g. asteroids) or indirectly (by building resilience and
reserves to increase survivability in a range of extreme scenarios) but it is more important to build capacity to
improve humanity’s ability to deal with the larger existential risks that will arise later in this century. This will
require collective wisdom, technology foresight, and the ability when necessary to mobilise a strong global coordinated response to anticipated existential risks.
• Perhaps the most cost-effective way to reduce existential risks today is to fund analysis of a wide range of existential risks and potential mitigation strategies, with a long-term perspective
Utilitarianism and riskMorten Fibieger ByskovDepartmen.docxjolleybendicty
Utilitarianism and risk
Morten Fibieger Byskov
Department of Politics and International Studies, Northern University of Warwick, Coventry,
United Kingdom
ABSTRACT
In day-to-day life, we are continuously exposed to different kinds of risk.
Unfortunately, avoiding risk can often come at societal or individual
costs. Hence, an important task within risk management is deciding
how much it can be justified to expose members of society to risk x in
order to avoid societal and individual costs y – and vice versa. We can
refer to this as the task of setting an acceptable risk threshold. Judging
whether a risk threshold is justified requires normative reasoning about
what levels of risk exposure that are permissible. One such prominent
normative theory is utilitarianism. According to utilitarians, the preferred
risk threshold is the one that yields more utility for the most people
compared to alternative risk thresholds. In this paper, I investigate
whether and the extent to which utilitarian theory can be used to nor-
matively ground a particular risk threshold in this way. In particular, I
argue that there are (at least) seven different utilitarian approaches to
setting an acceptable risk threshold. I discuss each of these approaches
in turn and argue that neither can satisfactorily ground an acceptable
risk threshold.
ARTICLE HISTORY
Received 28 February 2018
Accepted 10 July 2018
KEYWORDS
Philosophy of risk; ethics;
utilitarianism; equality
In day-to-day life, we are continuously exposed to different kinds of risk. These risks may range
from the longer-term and potentially life threatening, such as climate change, to the mundane,
such as catching the flu or being involved in a car accident. Unfortunately, avoiding risk can
often come at societal or individual costs. We may, for example, restrict access to public areas
during a disease outbreak or impose mass surveillance measures to prevent terrorist attacks.
Hence, an important task within risk management is deciding how much it can be justified to
expose members of society to risk x in order to avoid societal and individual costs y – and vice
versa. We can refer to this as the task of setting an acceptable risk threshold. Judging whether a
risk threshold is justified requires normative reasoning about what levels of risk exposure that
are permissible. One such prominent normative theory is utilitarianism. Utilitarians hold that pref-
erable action in a certain situation is the one that maximizes the most utility for the most peo-
ple. Hence, according to utilitarians, the preferred risk threshold is the one that yields more
utility for the most people compared to alternative risk thresholds.
Although the cost-benefit calculus of utilitarianism has often been invoked within risk man-
agement and assessment (Guehlstorf 2012, 45–47), little philosophical literature has investigated
whether utilitarianism can be applied to the task of setting an acceptable risk threshold.
CONTACT Morten Fibi.
In 17th century Europe all observable swans were white and by extension all swans were therefore assumed to be white. No non-white swan had ever been observed. In the 18th century, however, black swans were discovered in Western Australia and that discovery undermined the statistics of swans to that date. Previously, the “risk” of a Black Swan was essentially nil, but upon recognition that the improbable was not the same as the impossible the possibility of Black Swans became more likely.
What had changed that made Black Swans more probable? Simply put our perceptions were broadened. In this article we will look at large programs, what creates the possibility of Black Swans and what are some of the new risks we must pay attention to.
Possibility of Black Swans
Program Management is very much about meeting the challenges of scale and complexity. These challenges largely focus on the management of known knowns and known unknowns. But large programs by their very nature move into a new neighborhood where previously rare unknown unknowns are more prevalent. In effect large program risks grow in new non linear ways. What causes this growth? Simply put:
- Scale and complexity move you into a new neighborhood where black swans may be more common
- Scaling drives non linear and non correlated growth in risks
- Complexity masks existing risks
- Complexity creates new risks
So what are Black Swans?
My paper in this month\'s issue of PM World Today tries to provide some guidance for those responsible for large engineering & construction programs.
An overview of natural hazards, focusing on tectonic and early warning systmes; leans very heavily on the article: "Global early warning systems for natural
hazards: systematic and people-centred
By Re?d Basher*"i
Latino Buying Power - May 2024 Presentation for Latino CaucusDanay Escanaverino
Unlock the potential of Latino Buying Power with this in-depth SlideShare presentation. Explore how the Latino consumer market is transforming the American economy, driven by their significant buying power, entrepreneurial contributions, and growing influence across various sectors.
**Key Sections Covered:**
1. **Economic Impact:** Understand the profound economic impact of Latino consumers on the U.S. economy. Discover how their increasing purchasing power is fueling growth in key industries and contributing to national economic prosperity.
2. **Buying Power:** Dive into detailed analyses of Latino buying power, including its growth trends, key drivers, and projections for the future. Learn how this influential group’s spending habits are shaping market dynamics and creating opportunities for businesses.
3. **Entrepreneurial Contributions:** Explore the entrepreneurial spirit within the Latino community. Examine how Latino-owned businesses are thriving and contributing to job creation, innovation, and economic diversification.
4. **Workforce Statistics:** Gain insights into the role of Latino workers in the American labor market. Review statistics on employment rates, occupational distribution, and the economic contributions of Latino professionals across various industries.
5. **Media Consumption:** Understand the media consumption habits of Latino audiences. Discover their preferences for digital platforms, television, radio, and social media. Learn how these consumption patterns are influencing advertising strategies and media content.
6. **Education:** Examine the educational achievements and challenges within the Latino community. Review statistics on enrollment, graduation rates, and fields of study. Understand the implications of education on economic mobility and workforce readiness.
7. **Home Ownership:** Explore trends in Latino home ownership. Understand the factors driving home buying decisions, the challenges faced by Latino homeowners, and the impact of home ownership on community stability and economic growth.
This SlideShare provides valuable insights for marketers, business owners, policymakers, and anyone interested in the economic influence of the Latino community. By understanding the various facets of Latino buying power, you can effectively engage with this dynamic and growing market segment.
Equip yourself with the knowledge to leverage Latino buying power, tap into their entrepreneurial spirit, and connect with their unique cultural and consumer preferences. Drive your business success by embracing the economic potential of Latino consumers.
**Keywords:** Latino buying power, economic impact, entrepreneurial contributions, workforce statistics, media consumption, education, home ownership, Latino market, Hispanic buying power, Latino purchasing power.
The European Unemployment Puzzle: implications from population agingGRAPE
We study the link between the evolving age structure of the working population and unemployment. We build a large new Keynesian OLG model with a realistic age structure, labor market frictions, sticky prices, and aggregate shocks. Once calibrated to the European economy, we quantify the extent to which demographic changes over the last three decades have contributed to the decline of the unemployment rate. Our findings yield important implications for the future evolution of unemployment given the anticipated further aging of the working population in Europe. We also quantify the implications for optimal monetary policy: lowering inflation volatility becomes less costly in terms of GDP and unemployment volatility, which hints that optimal monetary policy may be more hawkish in an aging society. Finally, our results also propose a partial reversal of the European-US unemployment puzzle due to the fact that the share of young workers is expected to remain robust in the US.
Turin Startup Ecosystem 2024 - Ricerca sulle Startup e il Sistema dell'Innov...Quotidiano Piemontese
Turin Startup Ecosystem 2024
Una ricerca de il Club degli Investitori, in collaborazione con ToTeM Torino Tech Map e con il supporto della ESCP Business School e di Growth Capital
what is the future of Pi Network currency.DOT TECH
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
Message: @Pi_vendor_247 on telegram if u want to sell PI COINS.
1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
how to sell pi coins in South Korea profitably.DOT TECH
Yes. You can sell your pi network coins in South Korea or any other country, by finding a verified pi merchant
What is a verified pi merchant?
Since pi network is not launched yet on any exchange, the only way you can sell pi coins is by selling to a verified pi merchant, and this is because pi network is not launched yet on any exchange and no pre-sale or ico offerings Is done on pi.
Since there is no pre-sale, the only way exchanges can get pi is by buying from miners. So a pi merchant facilitates these transactions by acting as a bridge for both transactions.
How can i find a pi vendor/merchant?
Well for those who haven't traded with a pi merchant or who don't already have one. I will leave the telegram id of my personal pi merchant who i trade pi with.
Tele gram: @Pi_vendor_247
#pi #sell #nigeria #pinetwork #picoins #sellpi #Nigerian #tradepi #pinetworkcoins #sellmypi
What price will pi network be listed on exchangesDOT TECH
The rate at which pi will be listed is practically unknown. But due to speculations surrounding it the predicted rate is tends to be from 30$ — 50$.
So if you are interested in selling your pi network coins at a high rate tho. Or you can't wait till the mainnet launch in 2026. You can easily trade your pi coins with a merchant.
A merchant is someone who buys pi coins from miners and resell them to Investors looking forward to hold massive quantities till mainnet launch.
I will leave the telegram contact of my personal pi vendor to trade with.
@Pi_vendor_247
The secret way to sell pi coins effortlessly.DOT TECH
Well as we all know pi isn't launched yet. But you can still sell your pi coins effortlessly because some whales in China are interested in holding massive pi coins. And they are willing to pay good money for it. If you are interested in selling I will leave a contact for you. Just telegram this number below. I sold about 3000 pi coins to him and he paid me immediately.
Telegram: @Pi_vendor_247
Empowering the Unbanked: The Vital Role of NBFCs in Promoting Financial Inclu...Vighnesh Shashtri
In India, financial inclusion remains a critical challenge, with a significant portion of the population still unbanked. Non-Banking Financial Companies (NBFCs) have emerged as key players in bridging this gap by providing financial services to those often overlooked by traditional banking institutions. This article delves into how NBFCs are fostering financial inclusion and empowering the unbanked.
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
USDA Loans in California: A Comprehensive Overview.pptxmarketing367770
USDA Loans in California: A Comprehensive Overview
If you're dreaming of owning a home in California's rural or suburban areas, a USDA loan might be the perfect solution. The U.S. Department of Agriculture (USDA) offers these loans to help low-to-moderate-income individuals and families achieve homeownership.
Key Features of USDA Loans:
Zero Down Payment: USDA loans require no down payment, making homeownership more accessible.
Competitive Interest Rates: These loans often come with lower interest rates compared to conventional loans.
Flexible Credit Requirements: USDA loans have more lenient credit score requirements, helping those with less-than-perfect credit.
Guaranteed Loan Program: The USDA guarantees a portion of the loan, reducing risk for lenders and expanding borrowing options.
Eligibility Criteria:
Location: The property must be located in a USDA-designated rural or suburban area. Many areas in California qualify.
Income Limits: Applicants must meet income guidelines, which vary by region and household size.
Primary Residence: The home must be used as the borrower's primary residence.
Application Process:
Find a USDA-Approved Lender: Not all lenders offer USDA loans, so it's essential to choose one approved by the USDA.
Pre-Qualification: Determine your eligibility and the amount you can borrow.
Property Search: Look for properties in eligible rural or suburban areas.
Loan Application: Submit your application, including financial and personal information.
Processing and Approval: The lender and USDA will review your application. If approved, you can proceed to closing.
USDA loans are an excellent option for those looking to buy a home in California's rural and suburban areas. With no down payment and flexible requirements, these loans make homeownership more attainable for many families. Explore your eligibility today and take the first step toward owning your dream home.
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
1. The Precautionary Principle
Yaneer Bar-Yam⇤, Rupert Read†, Nassim Nicholas Taleb‡ †New England Complex Systems Institute
†School of Philosophy, University of East Anglia
‡School of Engineering, New York University
Abstract—The precautionary principle is useful only in certain
contexts and can justify only a certain type of actions. We
present a non-naive, fragility-based version of the precautionary
principle, placing it under formal statistical and probabilistic
structure of “ruin” problems, in which an entire system is at a
risk of total failure. We discuss the implications this definition
has on current questions about the use of nuclear energy and
the creation of GMOs, and address common counterarguments
to our claims.
CONTENTS
I Introduction 1
II Decision making and types of Risk 1
III A Non-Naive PP 2
III-A Harm vs. Ruin: When the PP is necessary 2
III-B Naive Interventionism . . . . . . . . . . 3
IV Fat Tails and Fragility 3
IV-A Thin and Fat Tails . . . . . . . . . . . . 3
IV-B Fragility as a Nonlinear Response . . . 4
V Why is fragility the general rule? 5
V-A Fragility and Replicating Organisms . . 5
V-B Fragility, Dose response and the 1/n rule 5
VI Why are GMOs to be put under PP but not the
nuclear? 5
VI-A GMOs . . . . . . . . . . . . . . . . . . 5
VI-B Risk of famine without GMOs . . . . . 6
VI-C Nuclear . . . . . . . . . . . . . . . . . . 6
VII Preventive Strikes 6
VIII Fallacious arguments against PP 6
VIII-A Crossing the road (the paralysis argument) 6
VIII-B The Loch Ness fallacy . . . . . . . . . 6
VIII-C The fallacy of misusing the naturalistic
fallacy . . . . . . . . . . . . . . . . . . 6
VIII-D The "Butterfly in India" fallacy . . . . . 7
VIII-E The potato fallacy . . . . . . . . . . . . 7
VIII-F The Russian roulette fallacy (the coun-
terexamples in the risk domain) . . . . 7
VIII-G The Carpenter fallacy . . . . . . . . . . 7
VIII-H The pathologization fallacy . . . . . . . 7
IX Conclusions 8
I. INTRODUCTION
The aim of the precautionary principle (PP) is to prevent
decision makers from putting society as a whole —or a
significant segment of it —at risk, from the unseen side effects
of a certain type of decisions. The PP states that if an action
or policy has a suspected risk of causing severe harm to the
public domain (such as general health or the environment),
in the absence of scientific near-certainty about the safety of
the action, the burden of proof about absence of harm falls
on those proposing an action. It is meant to deal with effects
of absence of evidence and the incompleteness of scientific
knowledge in some risky domains.1
We believe that it should be used only in extreme situations:
when the potential harm is systemic (rather than isolated), and
the consequences can involve total irreversible ruin, such as
the extinction of human beings or even all of life on the planet.
The aim of this paper is to place the concept of precaution
within a formal statistical and risk-based structure, grounding
it in probability theory and the properties of complex systems.
Our aim is to allow decision makers to discern which course of
events warrant the use of the PP and in which cases one may
be acting out of paranoia and using the PP inappropriately, in
a way that restricts benign (and necessary) risk-taking.
II. DECISION MAKING AND TYPES OF RISK
Decision and policy makers tend to assume all risks are
created equal, and thus all potential sources of randomness are
subject to the same set of approaches (for instance standard
risk-management techniques or the invocation of the precau-
tionary principle). However, taking into account the structure
of randomness in a given system can have a dramatic effect on
which kinds of actions are or are not appropriate and justified.
Two kinds of potential harm must be considered when
determining an appropriate approach to risk: 1) localized, non-
spreading errors and 2) systemic, spreading errors that propa-
gate through a system, resulting in irreversible damage. When
the potential for harm is localized, non-systemic, and risk is
easy to calculate from past data, risk-management techniques,
cost-benefit analyses and standard mitigation techniques are
appropriate, as any error in the calculations will be non-
spreading and the potential harm from miscalculation will be
bounded. In these situations of idiosyncratic, i.e., non-systemic
harm, cost benefit analysis enables balancing of potential
benefits against potential losses.
1The Rio Declaration presents it as follows "In order to protect the
environment, the precautionary approach shall be widely applied by States
according to their capabilities. Where there are threats of serious or irreversible
damage, lack of full scientific certainty shall not be used as a reason for
postponing cost-effective measures to prevent environmental degradation."
1
2. Table 1 encapsulates the central idea of the paper and shows
the differences between decisions with a risk of harm (warrant-
ing regular risk management techniques) and decisions with a
risk of total ruin (warranting the PP).
Standard Risk Management Precautionary Approach
localized harm systemic ruin
nuanced cost-benefit avoid at all costs
statistical probabilistic non statistical
variations ruin
convergent probab. divergent probabilities
local systemic
recoverable irreversible
independent factors interconnected factors
evidence based precautionary
thin tails fat tails
bottom-up, tinkering, evolution top-down, human-made
Table I: The two different types of risk and their respective
characteristics compared
III. A NON-NAIVE PP
Taking risks is not just unavoidable, but necessary for the
functioning and advancement of society; accordingly, the aim
of PP is precisely to avoid constraining such risk-taking while
protecting ourselves from its most severe consequences.
Various critics of the PP have expressed concern that it
will be applied in an overreaching manner, eliminating the
ability to take reasonable risks, those that are needed for
individual or societal gains. Indeed one can naively invoke
the precautionary principle to justify constraining risk in an
undiscriminate manner given the abstract nature of the risks
of events that did not take place.
Likewise one can make the error of suspending the PP in
cases when it is vital.
Hence, a non-naive view of the precautionary principle is
one in which it is only invoked when necessary, and only to
justify reasonable interventions that prevent a certain variety of
very precisely defined risks based on probabilistic structures.
But, also, in that view, the PP should never be omitted when
needed.
This section will outline the difference between the naive
and non-naive approaches.
A. Harm vs. Ruin: When the PP is necessary
The purpose of the PP is to avoid a certain class of what
is called in probability and insurance "ruin" problems, rather
than regular fluctuations and variations that do not represent
a severe existential threat. Regular variations within a system,
even drastic ones, differ from "ruin" problems in a funda-
mental way: once a system at some scale reaches an absolute
termination point, it cannot recover; a gambler who has lost
his entire fortune cannot bounce back into the game; a species
that has gone extinct cannot spring back into existence. While
an individual may be advised to not "bet the farm", whether
or not he does so is a matter of individual preferences. Policy
makers have a responsibility to avoid catastrophic harm for
society as a whole; the focus is on aggregate, not at the level
of single individuals, and on global-systemic, not idiosyncratic
harm. This is the domain of collective "ruin" problems. On the
level of the ecosystem, the “ruin" is ecocide: a systemwide,
irreversible extinction of life at some scale, which could be
the planet.
Even if the risk of ruin of a specific were minuscule, with
enough exposures ruin becomes essentially guaranteed. Taking
one such risk in a "one-off" manner may sound reasonable
but it also means that an additional one is reasonable. For
this reason the risk of ruin is not sustainable. This can be
quantified as the probability of ruin approaching 1 as the
number of exposures increases (see Fig. 1). The good news
is that not all classes of systems present such a risk of ruin;
some have a probability of practically zero per single exposure.
For example, the planet must have taken close to zero risks of
ecocide in trillions of trillions of variations over 3 billion years,
otherwise we would not be here.2
For this reason we must
consider any genuine risk of total ruin as if it were inevitable.
2000 4000 6000 8000 10000
Exposure
0.2
0.4
0.6
0.8
1.0
Probability of Ruin
Figure 1: Why Ruin is not a Renewable Resource. No
matter how small the probability, with enough exposures ruin
becomes guaranteed.
For humanity, global devastation cannot be measured on
a standard scale in which harm is proportional to level of
devastation. The harm due to complete destruction is not the
same as 10 times the destruction of 1/10 of the system. As the
percentage of destruction approaches 100%, the assessment of
harm diverges to infinity (instead of converging to a particular
number) due to the value placed on a future that ceases to
exist.
Because the “cost” of ruin is effectively infinite, cost-benefit
analysis (in which the potential harm and potential gain are
multiplied by their probabilities and weighed against each
other) is no longer a useful paradigm. The potential harm is
so substantial that everything else in the equation ceases to
matter. In this case, we must do everything we can to avoid
the catastrophe.
A formalization of the ruin problem identifies harm as not
about proportion of destruction, but rather a measure of the
2We can demonstrate that the probability of ruin from endogenous variation
(that is, not taking into account external shocks such as meteorites) is
practically zero, even adjusting for 1) survivorship bias, 2) risks taken by
the system in its early stages, 3) such catastrophic events as the Permian
mass extinction.
2
3. integrated level of destruction over the time it persists. When
the impact of harm extends to all future times, then the harm
is an infinite quantity. When the harm is infinite, the product
of the risk probability and the harm is also infinite, and cannot
be balanced against any potential gains, which are necessarily
finite. This strategy for evaluation of harm as involving the
duration of destruction can be extended to localized harms
for better assessment in risk management. Our focus here
is on the case where destruction is complete for a system
or irreplaceable aspect of a system and therefore the harm
diverges.
Just as the imperative of decision making changes when
there is a divergent harm even for a finite (non-zero) risk,
so is there a fundamental change in the ability to apply
conventional scientific methods to the evaluation of that harm.
This influences the way we evaluate both the existence of and
risk associated with ruin.
Critically, traditional empirical approaches do not apply to
ruin problems. Standard evidence-based approaches cannot
work. In an evidentiary approach to risk (relying on evidence
based methods), the existence of a risk or harm occurs when
we experience that risk or harm.
In the case of ruin, by the time evidence comes it will by
definition be too late to avoid it. Nothing in the past may
predict one large fatal deviation as illustrated in Fig. 3.
Statistical-evidentiary approaches to risk analysis and miti-
gation assume that the risk itself (i.e likelihood or probabilities
of outcomes) is well known. However, the level of risk may
be hard to gauge, the error attending its evaluation may be
high, its probability may be unknown, and in the case of an
essentially infinite harm, the uncertainty about both probability
and harm becomes itself a random variable, so we face the
consequences of the severely intractable "probability that the
model may be wrong". 3
Structural and Incompressible Unpredictability: It has been
shown that the complexity of real world systems limit the
ability of empirical observations to determine the outcomes
of actions (Bar-Yam, 2013). This means that a certain class
of systemic risks will remain inherently unknown. Those who
want to introduce innovations use controlled experiments to
evaluate impact. But, in some class of complex systems,
controlled experiments cannot evaluate all of the possible
systemic consequences under real-world conditions. In these
circumstances, efforts to provide assurance of the "lack of
harm" are insufficiently reliable for one to take action.
Since there are mathematical limitations to predictability in
a complex system, the central point to determine is whether
the threat is local (hence globally benign) or carries systemic
consequences. Local risks can handle mistakes without spread-
3Statistical-evidentiary approaches for risk management are split in two
general methods. For pure statistical approaches, devoid of experiments,
risk assessors base themselves of time series analysis, computing various
attributes of past data. They can either count the frequency of past events
(robust statistics) or calibrate parameters that allow the building of statistical
distributions from which to generate probabilities of future events (called the
parametric approach), or both. Experimental evidentiary methods follow the
model of medical trials, computing probabilities of harm from side effects of
drugs or interventions by observing the reactions in a variety of animal and
human models.
ing through the entire system. Scientific analysis can robustly
determine whether a risk is systemic, i.e. by evaluating the
connectivity of the system to propagation of harm, without
determining the specifics of such a risk. If the consequences
are systemic the associated uncertainty of risks must be treated
differently. In cases such as this, precautionary action is not
based on "evidence" but purely on analytical approaches. It
relies on probability theory without computing probabilities.
B. Naive Interventionism
Often when a risk is perceived as having the potential for
ruin, it is assumed that any preventive measure is justified.
There are at least two problems with such a perspective.
First, as outlined above, localized harm is often mistaken for
ruin, and the PP is wrongly invoked where risk management
techniques should be employed. When a risk is not systemic,
overreaction will typically cause more harm than benefits, like
undergoing dangerous surgery to remove a benign growth.
Second, even if the threat of ruin is real, taking specific
(positive) action in order to ward off the perceived threat may
introduce new systemic risks, fragilizing the system further. It
is often wiser to reduce or remove activity that is generating
or supporting the threat and allow natural variations to play
out in localized ways. For example, preemptive U.S. military
interventions which have been justified as threat reduction may
ultimately embolden anti-American sentiment and amplify the
threat they purport to minimize.
IV. FAT TAILS AND FRAGILITY
A. Thin and Fat Tails
To understand whether a given decision involves the risk
of ruin and thus warrants the use of the PP, we must first
understand the relevant underlying probabilistic structures.
There are two broad types of probability domains: ones where
the event is accompanied with well behaved mild effects (Thin
Tails, or "Mediocristan"), the other where small probabilities
are associated with large and unpredictable consequences that
have no characteristic scale (Fat Tails, or "Extremistan")4
. The
demarcation between the two is as follows. 5
• In Thin Tailed domains, i.e., Mediocristan, harm comes
from the collective effect of many, many events; no
event alone can be consequential enough to affect the
aggregate. It is practically impossible for a single day
to account for 99% of all heart attacks in a given
year (the probability is small enough to be practically
4The designation Mediocristan and Extremistan were presented in The
Black Swan to illustrate that in one domain the bulk of the variations come
from the collective effect of the "mediocre", that is belongs to the center of
the distribution while in the other domain, Extremistan, changes result from
jumps and exception, the extreme events.
5More technically, in Silent Risk, Taleb (2014) distinguishes between
different classes ranging between extreme thin-tailed (Bernoulli) and extreme
fat tailed 1) Compact support but not degenerate, 2) Subgaussian, 3) Gaussian,
4) subexponential, 5) Power Laws with exponent > 2, 6) Power Laws with
Exponent 2, 7) Power law tails with exponents 3. The borderline between
Mediocristan and Extremistan is defined along the class of subexponential
with a certain parametrization worse than lognormal, i.e., distributions not
having any exponential moments.
3
4. zero), (see Fig 2 for an illustration). Example of well-
known statistical distributions that belong squarely to the
thin-tailed domain are: Gaussian, Binomial, Bernoulli,
Standard Poisson, Gamma, Beta, Exponential.
• In Fat Tailed domains, i.e., Extremistan, the aggregate is
determined by the largest variation.(see Fig. 3) While no
human being can be heavier than, say, ten adults (since
weight is thin-tailed), a single one can be richer than the
bottom two billion humans (since wealth is fat tailed).
Example of statistical distributions: Pareto distribution,
Levy-Stable distributions with infinite variance, Cauchy
distribution, mixture distributions with power-law jumps.
Nature, on the largest scale, is a case of thin tails : no
single variation represents a large share of the sum of the
total variation; even occasional mass extinctions are a blip
in the total variation. This is characteristic of a bottom-
up, tinkering design, where things change only mildly and
iteratively. Working backwards, we can see that were this not
the case we would not be alive today, since a single one in the
trillions, perhaps the trillions of trillions, of variations would
have terminated life on the planet, and we would not have been
able to recover from extinction. Therefore while tails can be
fat for any particular isolated subsystem, nature remains thin-
tailed at the level of the planet (Taleb, 2014).
Humanmade systems, by contrast, those constructed in a
top-down manner, tend to have fat-tailed variations. A single
deviation will eventually dominate the sum.
Figure 2: Thin Tails from Tinkering, Bottom Up, Broad
Design. A typical manifestation in Mediocristan.
Figure 3: Fat Tails from Systemic Effects, Top-down,
Concentrated Design A typical distribution in which the sum
is dominated by a single data point
Interdependence is frequently a feature of fat tails at a sys-
temic scale6
. Consider the global financial crash of 2008. As
financial firms became increasingly interdependent, the system
started exhibiting periods of calm and efficiency, masking the
fact that, overall, the system became very vulnerable as an
error can spead through the economy. Instead of a local shock
in an independent section, we experienced a global shock with
cascading effects.
The crisis of 2008, in addition, illustrates the failure of
evidentiary risk management since data from time series
exhibited more stability than ever before, causing the period
to be dubbed "the great moderation", and fooling those relying
on statistical risk management.
B. Fragility as a Nonlinear Response
Everything that survived is necessarily non-linear to harm.
If I fall from a height of 10 meters I am injured more than
10 times than if I fell from a height of 1 meter, or more than
1000 times than if I fell from a height of 1 centimeter, hence
I am fragile. Every additional meter, up to the point of my
destruction, hurts me more than the previous one. If I were
not fragile (susceptible to harm linearly), I would be destroyed
even by accumulated small events, and thus would not survive.
Similarly, if I am hit with a big stone I will be harmed a lot
more than if I were pelted serially with pebbles of the same
total weight. Everything that is fragile and still in existence
(that is, unbroken), will be harmed more by a certain stressor
of intensity X than by k times a stressor of intensity X/k, up
to the point of breaking. This non-linear response is central for
everything on planet earth, from objects to ideas to companies
to technologies.
This explain the the necessity of using scale when invoking
the PP. Polluting in a small way does not warrant the PP
because it is exponentially less harmful than polluting in large
quantities, since harm is non-linear.
We should be careful, however, of actions that may seem
small and local but then lead to systemic consequences.
Figure 4: The non-linear response compared to the linear.
6Interdependence causes fat tails, but not all fat tails come from interde-
pendence
4
5. V. WHY IS FRAGILITY THE GENERAL RULE?
The statistical structure of stressors is such that small
deviations are much, much more frequent than large ones.
Look at the coffee cup on the table: there are millions of
recorded earthquakes every year. Simply, if the coffee cup were
linearly sensitive to earthquakes, it would not have existed at
all as it would have been broken in the early stages of its
life. The coffee cup, however, is non-linear to harm, so that
the small earthquakes only make it wobble, whereas one large
one would break it forever.
This nonlinearity is necessarily present in everything fragile.
A. Fragility and Replicating Organisms
In the world of coffee cups, it is acceptable if one breaks
when exposed to a large quake; we simply replace it with
another that will last until the next extreme shock. Because
of the infrequency of large events, the cup serves its purpose
through most events, and is not terribly missed when the big
one strikes.
Biological organisms share a similar characteristic. They are
able to survive many, many events that incur small amounts
of harm (or stress), but break when exposed to extreme
shocks. Unlike coffee cups, organisms enjoy the feature of
(self-)replication, such that no external agent is necessary to
make a new one. This allows the exposures of two similar
organisms to become decorrelated as they move essentially
independently throughout space. This means that exposure to
an extreme event of one organism of a given species does
not imply exposure to all individuals of the species. By the
time an extreme shock rolls around, replication has minimized
the exposure to a small subset of individuals; risk has been
localized.
Variations among replicated organisms allow the system of
organisms as a whole to develop new and better ways of
surviving the typical stressors individuals are exposed to. The
fragility of the individual provides information for the system:
what does not work. An overly-fragile organism is not able to
replicate itself sufficiently, as a coffee cup that breaks when
set on the table would not enjoy wide popularity.
B. Fragility, Dose response and the 1/n rule
Another area we see non-linear responses to harm is the
dose-response relationship. As the dose of some chemical or
stressor increases, the response to it grows non-linearly. Many
low-dose exposures do not cause great harm, but a single
large-dose can cause irreversible damage to the system, like
overdosing on painkillers.
In decision theory, the 1/n heuristic is a simple rule in
which an agent invests equally across n funds (or sources
of risk) rather than weighting their investments according to
some optimization criterion such as mean-variance or Modern
Portfolio Theory (MPT), which dictate some amount of con-
centration in order to increase the potential payoff. The 1/n
heuristic mitigates the risk of suffering ruin due to an error
in the model; there is no single asset whose failure can bring
down the ship. While the potential upside of the large payoff
is dampened, ruin due to an error in prediction is avoided.
The heuristic works best when the sources of variations are
uncorrelated and, in the presence of correlation or dependence
between the various sources of risk, the total exposure needs
to be reduced.
Hence, because of non-linearities, it is preferable to spread
pollutants, or more generally our effect on the planet, across
the broadest number of uncorrelated sources of harm, rather
than concentrate them. In this way, we avoid the risk of an
unforeseen disproportionately harmful response to a pollutant
deemed "safe" by virtue of responses observed only in rela-
tively small doses.
VI. WHY ARE GMOS TO BE PUT UNDER PP BUT NOT THE
NUCLEAR?
A. GMOs
Genetically Modified Organisms (GMOs) and their risk are
currently the subject of debate. Here we argue that they fall
squarely under the PP not because of the potential harm
to the consumer, but because the nature of their risk is
systemic. In addition to intentional cultivation, GMOs have the
propensity to spread uncontrollably, and thus their risks cannot
be localized. The cross-breeding of wild-type plants with
genetically modified ones prevents their disentangling, leading
to irreversible system-wide effects with unknown downsides.
One argument in favor of GMOs is that they are no more
"unnatural" than the selective farming our ancestors have been
doing for generations. In fact, the ideas developed in this
paper show that this is not the case. Selective breeding is a
process in which change still happens in a bottom-up way,
and results in a thin-tailed distribution. If there is a mistake,
some harmful mutation, it will simply not spread throughout
the whole system but end up dying out in isolation.
Top-down modifications to the system (through GMOs)
are categorically and statistically different from bottom up
ones. Bottom-up modifications do not remove the crops from
their coevolutionary context, enabling the push and pull of
the ecosystem to locally extinguish harmful mutations. Top-
down modifications that bypass this evolutionary pathway
manipulate large sets of interdependent factors at a time. They
thus result in fat-tailed distributions and place a huge risk on
the food system as a whole. We should exert the precautionary
principle here – our non-naive version – because we do not
want to discover errors after considerable and irreversible
environmental damage.
Labeling the GMO approach “scientific" betrays a very
poor—indeed warped—understanding of probabilistic payoffs
and risk management. A lack of observations of explicit harm
does not show absence of hidden risks. In complex systems it
is often difficult to identify the relevant variables, and models
only contain the subset of reality that is deemed relevant by
the scientist. Nature is much richer than any model of it. To
expose an entire system to something whose potential harm is
not understood because extant models do not predict a negative
outcome is not justifiable; the relevant variables may not have
been adequately identified.
5
6. B. Risk of famine without GMOs
Invoking the risk of "famine" as an alternative to GMOs is
a deceitful strategy, no different from urging people to play
Russian roulette in order to get out of poverty. While hunger is
a serious threat to human welfare, as long as the threat remains
localized, it falls under risk management and not the PP.
Some attempts have been made to counter GMO skeptics
on grounds of "morality". A GMO variety, "golden rice"
supposedly adds the needed vitamins to consumers – as if
vitamins cannot be offered separately. Aside from the defects
in the logic of the argument, we fail to see the morality
of putting people at risk with untested methods instead of
focusing on (less profitable) but safer mechanisms.
C. Nuclear
In large quantities we should worry about an unseen risk
from nuclear energy and certainly invoke the PP. In small
quantities, however, it may simply be a matter of risk man-
agement. Although exactly where the cutoff is has yet to be
determined, we must make sure threats never cease to be local.
It is important to keep in mind that small mistakes with the
storage of nuclear energy are compounded by the length of
time they stay around. The same reasoning applies to fossil
fuels, and other sources of pollution.
If the dose remains small in each source, then the response
(the damage) will also be relatively small. In this case, we
are the ones throwing rocks at the environment; if we want to
minimize harm, we should be throwing lots of little pebbles
instead of one big rock. Unfortunately the scientists evaluating
the safety of current methods are limited in their view to one
source at a time. Taking a systemic view reveals that it is
important to consider the global effects when evaluating the
consequences of one source.
VII. PREVENTIVE STRIKES
Preventive action needs to be limited to correcting situations
via negativa in order to bring them back in line with a
statistical structure that avoids ruin. It is often better to remove
structure or allow natural variation to take place rather than to
add something additional to the system.
When one takes the opposite approach, taking specific
action designed to diminish some perceived threat, one is
almost guaranteed to induce unforeseen consequences. One
might imagine a straight line from a specific action to a
specific preventive outcome, but the web of causality ex-
tends outwards from the action in complex paths far from
the intended goal. These unintended consequences can often
have counter-intuitive effects: generating new vulnerabilities or
strengthening the very source of risk one is hoping to diminish.
My coffee cups are fragile, so I put them in a large, heavy-
duty box to protect them from shocks in the outside world.
When the whole box tumbles, all of the coffee cups smash
together. Whenever possible, one should focus on removing
fragilizing interdependencies rather than imposing additional
structure and activity that will only increase the fragility of
the system as a whole.
VIII. FALLACIOUS ARGUMENTS AGAINST PP
Next is a continuously updated list of the arguments against
PP that we find flawed.
A. Crossing the road (the paralysis argument)
Many have countered invocation of the PP with "nothing is
ever totally safe", "I take risks crossing the road every day, so
according to you I should stay home in a state of paralysis".
The answer is that we don’t cross the street blindfolded, we
use sensory information to mitigate risks and reduce exposure
to extreme shocks.
Even more importantly in the context of the PP, the probabil-
ity distribution of death from road accidents at the population
level is thin-tailed; I do not incur the risk of generalized human
extinction by crossing the street —a human life is bounded and
its unavoidable termination is part of the logic of the system
(Taleb, 2007). In fact, the very idea of the PP is to avoid such
a frivolous focus. The error of my crossing the street at the
wrong time and meeting an untimely demise in general does
not cause others to do the same; the error does not spread. If
anything, one might expect the opposite effect, that others in
the system benefit from my mistake by adapting their behavior
to avoid exposing themselves to similar risks.
The paralysis argument is also used to present our idea as
incompatible with progress. This is untrue: tinkering, bottom-
up progress where mistakes are bounded is how true progress
has taken place in history. The non-naive PP simply asserts that
the risks we take as we innovate must not extend to the entire
system; local failure serves as information for improvement.
B. The Loch Ness fallacy
Many have countered that we have no evidence that the
Loch Ness monster doesn’t exist, and to take the argument of
evidence of absence being different from absence of evidence,
we should act as if the Loch Ness monster existed. The
argument is a corruption of the absence of evidence problem
(paranoia is not risk management) and certainly not part of
the PP, rather part of risk management.
If the Loch Ness monster did exist, there would still be no
reason to invoke the PP, as the harm he might cause is limited
in scope to Loch Ness itself, and does not present the risk of
ruin.
C. The fallacy of misusing the naturalistic fallacy
Some people invoke "the naturalistic fallacy", a philosoph-
ical concept that is limited to the moral domain. We do not
claim to use nature to derive a notion of how things "ought"
to be organized. Rather, as scientists, we respect nature for
its statistical significance; a large n cannot be ignored. Nature
may not have arrived at the most intelligent solution, but there
is reason to believe that it is smarter than our technology based
only on statistical significance.
The question about what kinds of systems work (as demon-
strated by nature) is different than the question about what
working systems ought to do. We can take a lesson from nature
—and time —about what kinds of organizations are robust
6
7. against, or even benefit from, shocks, and in that sense systems
should be structured in ways that allow them to function.
Conversely, we cannot derive the structure of a functioning
system from what we believe the outcomes ought to be.
To take one example, Cass Sunstein — a skeptic of the
precautionary principle — claims that agents have a "false
belief that nature is benign." However, his papers fail to
distinguish between thin and fat tails (Sunstein, 2003). The
method of analysis misses both the statistical significance of
nature and the fact that it is not necessary to believe in the
perfection of nature, or in the "benign" attributes, rather, in its
track record, its sheer statistical power as a risk manager.
D. The "Butterfly in India" fallacy
The statement “if I move my finger to scratch my nose, by
the butterfly-in-India effect, owing to non-linearities, I may
terminate life on earth" is known to be flawed, but there has
been no explanation of why it is flawed. Our thesis, can rebut it
with the argument that in the aggregate, nature has experienced
trillions of such small actions and yet it survives. Therefore
we know that the effects of scratching one’s nose fall into the
thin tailed domain and thus does not warrant the precautionary
principle.
Not every small action sets off a chain of events that
culminates in some disproportionately large-scale event. This
is because nature has found a way of decorrelating small events
such that their effect balances out in the aggregate. Unlike
the typical statistical assumptions of independence among
components, natural systems display a high-degree of inter-
dependence among components. Understanding how systems
with a high-degree of connectivity achieve decorrelation in
the aggregate, such that a butterfly in India does not cause
catastrophe, is essential for understanding when it is and isn’t
appropriate to use the PP.
E. The potato fallacy
Many species were abruptly introduced into the Old World
starting in the 16th Century that did not cause environmen-
tal consequences. Some use that fact in defense of GMOs.
However, the argument is fallacious at two levels:
First, by the fragility argument, potatoes, tomatoes, and
similar "New World" goods were developed locally through
progressive bottom-up tinkering in a complex system in the
context of its interactions with its environment. Had they
had an impact on the environment, it would have caused ad-
verse consequences that would have prevented their continual
spread.
Second, a counterexample is not evidence in the risk do-
main, particularly when the evidence is that taking a similar
action previously did not lead to ruin. This is the Russian
roulette fallacy, detailed below.
F. The Russian roulette fallacy (the counterexamples in the
risk domain)
The potato example, assuming potatoes had not been gener-
ated top-down by some engineers, would still not be sufficient.
Nobody says "look, the other day there was no war, so we
don’t need an army", as we know better in real-life domains.
Nobody argues that a giant Russian roulette with many barrels
is "safe" and great money making opportunity because it didn’t
blow someone’s brain up last time.
There are many reasons a previous action may not have led
to ruin while still having the potential to do so. There are
many reasons one might have ‘gotten away’ with actions that
have inherent risk. If you attempt to cross the street with a
blindfold and earmuffs on, you may get lucky and make it
across, but this is not evidence that such an action carries no
risk.
More generally one needs a large sample for claims of
absence of risk in the presence of a small probability of ruin,
while a single “n = 1" example would be sufficient to counter
the claims of safety —this is the Black Swan argument. Simply
put, systemic modifications require a very long history in order
for the evidence of lack of harm to carry any weight.
G. The Carpenter fallacy
Risk managers who are skeptical of the understanding of
risk of biological processes such as GMOs by the experts
are sometimes asked "are you a biologist?". But nobody
asks a probabilist dealing with roulette sequences if he is a
carpenter. To understand the gambler’s ruin problem with the
miscalibration of roulette betting, we know to ask a probabilist,
not a carpenter. No amount of expertise in carpentry can
replace probabilisitic rigor in understanding the properties of
long sequences of small probability bets. Likewise no amount
of expertise in the details of biological processes can be a
substitute for probabilistic rigor.
The track record of the experts in understanding biological
risks has been extremely poor, and we need the system to
remain robust to their miscalculations. For there has been
an “expert problem,” a very poor record historically in un-
derstanding the risks of innovations in biological products,
from misestimated risks of biofuels to transfat to nicotine, etc.
Consider the recent major drug recalls such as Thalidomide,
Fen-Phen, Tylenol, Vioxx —all of these show chronic Black
Swan blindness on the part of the specialist. Yet these risks
were local not systemic: with the systemic the recall happens
too late, which is why we need this strong version of the PP.
H. The pathologization fallacy
Often narrow models reveal biases that, in fact, turn out
to be rational positions, except that it is the modeler who is
using an incomplete representation. Often the modelers are
not familiar with the dynamics of complex systems or use
Gaussian statistical methods that do not take into account fat-
tails and make inferences that would not be acceptable under
different classes of probability distributions. Many biases such
as the ones used by Cass Sunstein (mentioned above) about
the overestimation of the probabilities of rare events in fact
correspond to the testers using a bad probability model that
is thin-tailed. See Silent Risk, Taleb (2014) for a deeper
discussion.
7
8. It became popular to claim irrationality for GMO and other
skepticism on the part of the general public —not realizing
that there is in fact an "expert problem" and such skepticism
is healthy and even necessary for survival. For instance, in
The Rational Animal 7
, the authors pathologize people for
not accepting GMOs although "the World Health Organization
has never found evidence of ill effects" a standard confusion
of evidence of absence and absence of evidence. Such a
pathologizing is similar to behavioral researchers labeling
hyperbolic discounting as "irrational" when in fact it is largely
the researcher who has a very narrow model and richer models
make the "irrationality" go away.
These researchers fail to understand that humans may have
precautionary principles against systemic risks, and can be
skeptical of the untested for deeply rational reasons.
IX. CONCLUSIONS
This formalization of the two different types of uncer-
tainty about risk (local and systemic) makes clear when the
precautionary principle is, and when it isn’t, appropriate.
The examples of GMOs and nuclear help to elucidate the
application of these ideas. We hope this will help decision
makers to avoid ruin in the future.
REFERENCES, FURTHER READING, & TECHNICAL BACKUP
Bar-Yam, Y., 2013, The Limits of Phenomenology: From
Behaviorism to Drug Testing and Engineering Design, arXiv
1308.3094
Rauch, E. M. and Y. Bar-Yam, 2006, Long-range interactions
and evolutionary stability in a predator-prey system, Physical
Review E 73, 020903
Hutchinson, Phil and Read, Rupert, What’s wrong with GM
food?,The Philosophers Magazine Issue 65, 2nd Quarter of
2014.
Taleb, N.N., 2014, Silent Risk: Lectures on Fat Tails, (Anti)
Fragility, and Asymmetric Exposures, SSRN
Taleb, N.N. and Tetlock, P.E., 2014, On the Difference be-
tween Binary Prediction and True Exposure with Implications
for Forecasting Tournaments and Decision Making Research
http://dx.doi.org/10.2139/ssrn.2284964
Sunstein, Cass R., Beyond the Precautionary Principle (Jan-
uary 2003). U Chicago Law & Economics, Ol in Working
Paper No. 149; U of Chicago, Public Law Working Paper No.
38.
CONFLICTS OF INTEREST
One of the authors (Taleb) reports having received monetary
compensation for lecturing on risk management and Black
Swan risks by the Institute of Nuclear Power Operations,
INPO, the main association in the United States, in 2011, in
the wake of the Fukushima accident.
7Kenrick, D. T. and V. Griskevicius (2013), The rational animal: How
evolution made us smarter than we think. Basic Books.
8