Creative Ruins: Review Of The Road To Ruin By James Rickards

My 2021 started with a thrilling, terrifying, and terrific The Road to Ruin: The Global Elites’ Secret Plan for the Next Financial Crisis by James Rickards.

I have withdrawn a lot of food for thought from that book, including the following 4 things that can be immensely valuable for legal practitioners.

Hippocrates

Rickards uses the Hippocratic Oath — an oath of ethics historically taken by physicians — to elegantly illustrate the importance of —

• abstaining from ill action
• being aware of your frailty
• preferring prevention to cure, and
• freely acknowledging your expertise insufficiency.

(You can find some allusions with the Hippocratic Oath in codes of ethics developed by bars, universities, and departments of justice.)

Remembering those basic things can save legal practitioners and their clients’ time, money and reputation.

Do no harm. The default setting should be to do no harm, not to do something. Action does not necessarily help to avoid harm. An ill-prepared or unauthorized action can even make things worse. Sometimes you can get better results by doing nothing.

Do not play at God. Professional degree does not justify any kind of superiority over laypeople, but outlines an awesome responsibility to them.

Prevent unfavorable results whenever possible. For example, competent contract drafting can help avoid court disputes.

And do not be ashamed to say “I know not.” Do not fail to call colleagues when their skills are needed. Nourishing ego should not be the priority.

Bayes

Rickards reminds of the Bayes’ theorem — a mathematical formula for determining conditional probability — and gives reasons for its efficiency when you need to model future events based on insufficient or no data.

A bit of theory:

The equation below illustrates the Bayes’ theorem:

P(A|B) = (P(B|A) * P(A)) / P(B)

where —

• A and B are different events
• P(A) is the likelihood of A being true
• P(B) is the likelihood of B being true, and it does not equal 0
• P(A|B) is the probability of A being true, given that B is true, and
• P(B|A) is the probability of B being true, given that A is true.

For example, to answer what is the probability that there is thunder given that there is lightning, solve the equation:

P(Thunder|Lightning) = (P(Lightning|Thunder) * P(Thunder)) / P (Lightning)

If thunder is related to lightning, you can use lightning to more accurately assess the probability that there is thunder, compared to the assessment of the probability of thunder made without knowledge of lightning.

Using the Bayes’ theorem, you start with a hypothesis — a provisional explanation that fits the evidence and can be confirmed or disproved — and a degree of belief in that hypothesis.

Then, you gather data and update your initial beliefs. Updated data influence the preceding data.

If the data support the hypothesis, the probability goes up. If the data do not support the hypothesis, the probability goes down.

Simply put, by adding new data to the hypothesis, you begin to understand the situation better.

This method — albeit of some drawbacks — allows you to draw unambiguous conclusions, while others wait for “sufficient enough” data.

To date, Bayes’ theorem has made only minimal impact on the law.

The objections to the use of Bayes’ theorem in the legal domain include —

• that probabilistic reasoning is not compatible with the law, for policy reasons
• that not all evidence can be considered or valued in probabilistic terms
• that no probability value can be reconciled with “beyond reasonable doubt”
• that some evidence cannot be mathematically valued and therefore be inserted into the model, due to the existence of ‘soft variable’, etc.

To make things worse, add poor experience (witnesses who use “bad statistics” in courts) and difficulties in interpretation (lawyers who allow witnesses to use “bad statistics” in courts or who support “no such thing as probability” argument).

However, a lawyer thinking mathematically is not an oxymoron: proper use of Bayesian reasoning can improve the transparency, efficiency, and fairness of legal proceedings.

The Bayes’ theorem is not merely a method of quantified mathematical modelling: the Bayes’ theorem helps to —

• understand the relation between pieces of evidence and their causal pathways to a given hypothesis
• avoid probabilistic fallacies
• identify errors and unjustified assumptions in expert opinions
• recognise the crucial issue of context, and
• identify and negate natural biases and intuitions.

To dig deeper into this topic, please consult —

• Bayes and the Law, Norman Fenton, Martin Neil, and Daniel Berger
• Bayes’ theorem, and its role in the law, Tony O’Hagan
• Improving Legal Reasoning using Bayesian Probability Methods by Daniel Berger, and
• Improve statistics in courts, Norman Fenton.

Butterflies

The butterfly effect — the idea that a very small change in one part of a deterministic nonlinear system can have large effects in other parts — is acknowledged by the basic science, Rickards says.

In the legal context, predictability of legal issues is one of the key values. However, as Michael C. Dorf notes, the butterfly effect demonstrates why calculations about the likely long-term impact of any decision is misguided.

Any decision may have large but inherently unpredictable consequences. Popular ruling today may result in the disastrous tomorrow, and unpopular ruling today may move the society to the better tomorrow.

Making decisions based on remote consequences might be a guesswork at best. This revokes discussions about how to interpret and apply the law — according to the direct meaning of words, or the context, or the policy.

‘Too soon to tell”: time will tell whether your legal reasoning was appropriate to the goals and the context — or played a role of a butterfly which flap caused hurricanes. In the meantime, making decisions based on remote consequences might be a guesswork at best.

And take note that not every butterfly flap causes a hurricane, and not every hurricane is caused by a butterfly flap. What is more or less clear, hurricanes emerge unexpectedly, being the result of unpredicted events.

Black Swans

Rickards argues that the black swan theory — the theory developed by Nassim Nicholas Taleb to explain unpredictable events that are characterized by extreme impact, rarity, and retrospective (though not prospective) predictability — vulgarises science and gives events a touch of fatality, as if to say “it just happened.”

In Rickards’ opinion, the real world differs from the coin toss: the chain of events does not consist of discrete events — the chain of events has memory; new events do not happen in isolation from past events — new events depend on past events.

Legal practitioners — whether they agree or disagree with the black swan theory — can benefit from both Taleb’s and Rickards’ points of view.

Prepare, prepare, and prepare. Befriend with black swans, but do not use them as an excuse for your ignorance. Not every ‘surprising’ bad thing is a black swan — some of such things can result from your ill-preparedness. Prepare so that to be better able to cope with random events. Build legal solutions that can survive random stresses, rather than break under any particular one.

Speaking allusively, take care of every singly transformer, to the best of your capabilities, — given that the failure of a single transformer can collapse an electricity grid.

Forewarned is forearmed. Among the things to think about are the crisis team and crises scenarios.

• Model the crisis team ahead of time, and allocate rules within it. The crisis team should be able to make and implement decisions within hours, build a wall of confidentiality around those who are responding, and protect those who are not involved from distraction. For this purpose, small size, high level of decision-making authority and funding, light approval procedures, a full-time senior leader are required.
• In preparation of crisis scenarios, seek a healthy balance between preparation and real-time action: both too much specificity and too much abstraction are inappropriate. Construct plausible crisis scenarios in advance — based on top threats your client might face.

Maintain healthy skepticism. Expert advice can be useless. Forecasting can be pseudoscientific. Human mind can be clouded by illusions, biases, and blind spots. Highly consequential but unlikely events can render predictions and standard explanations worse than worthless.

Know that you can not know. Think outside your usual, conceptual categories. Remember that as a forecasting period lengthens, prediction errors grow exponentially.

Look for what is not evident. Think “what even would refute this theory” rather than get stack in confirming evidence.

And think for yourself. Avoid dogmatism, nerds, and herds.

Originally published on https://dearall.medium.com/the-road-to-ruin-17a5331e367f.

Disclaimer: This is my personal blog. This is neither a legal opinion nor a piece of legal advice. The opinions I express in this blog are mine, and do not reflect opinions of any third party, including employers. My blog is not an investment advice. I do not intend to malign or discriminate anyone. I reserve the right to rethink and amend the blog at any time, for any or no reason, without notice.