Precautionary Principle

Miscellaneous Notes

The precautionary principle (PP) states that if an action or policy has a suspected risk of causing severe harm to the public domain, the action should not be taken in the absence of scientific near-certainty about its safety. Under these conditions, the burden of proof about absence of harm falls on those proposing an action, not those opposing it.

PP is intended to deal with uncertainty and risk in cases where the absence of evidence and the incompleteness of scientific knowledge carries profound implications and in the presence of risks of “black swans”, unforeseen and unforeseeable events of extreme consequence.

Thin Tails from Tinkering, Bottom-Up, Evolution

In nature no individual variation represents a large share of the sum of the variations. Natural boundaries prevent cascading effects from propagating globally. Mass extinctions arise from the rare cases where large impacts (meteorite hits and vulcanism) propagate across the globe through the atmosphere and oceans.

Fat Tails from a Top-Down, Engineered Design

In human made variations the tightly connected global system implies a single deviation will eventually dominate the sum of their effects. Examples include pandemics, invasive species, financial crises and monoculture.

The Precautionary Principle (PP)

Avoid paranoia and paralysis by confining precaution to specific domains and problems.

What appears to be small and reasonable risks accumulate inevitably to certain irreversible harm. Traditional cost-benefit analyses which seek quantitatively weigh outcomes to determine the best option, do not apply, as outcomes may have infinite costs.

Even high-benefit, high probability outcomes do not outweigh the existence of low probability, infinite cost options.

The analysis show that GMOs represent a public risk of global harm, while harm from nuclear energy is comparatively limited and better characterized.

Types of Risk and Decision-Making

1. Localized and non-spreading.
2. Propagating and resulting in irreversible and widespread damage.

PP focuses on irreversible and wide spreading damage.

The key point is to differentiate between naive and non-naive PP.

Risk aversion and risk seeking are both well-studied human behaviors.

Fat Tails Vs Thin Tails

The two classes of probability distribution:

1. Gaussian or thin tails: Events are accompanied by well-behaved, mild variations, e.g. typical of human weight distribution
2. Power Law or fat tails: Small probabilities are associated with large variations that have no characteristic scale, e.g. typical of human wealth distribution.

More examples: No human can be heavier than, say ten average adults (weight is thin-tailed). On the other hand, a single individual can be richer than the poorest two billion humans wealth combined (wealth is fat tailed).

In thin tail domains harm comes from the collective effect of many events, no single event causes enough affect to the aggregate.

In fat tail domains harm comes from the largest single event. Relevant statistical distributions: Pareto, Cauchy, and power law distribution, especially with larger exponents.

Interdependency brings fat tails because the coupling of behavior in different places therefore cascades propagate through the system in a way that can cause large impacts.

As connectivity increases, the risk of extinction increases dramatically and non-linearly.

Reference

Nassim Nicholas Taleb, Rupert Read, Raphael Douady, Joseph Norman, and Yaneer Bar-Yam (2014). The Precautionary Principle. https://necsi.edu/the-precautionary-principle