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People do no harm to others simply because they don’t want to, and not because they can’t – this simple truth is neglected in the current security-paranoid environment, where everyone is treated as a suspected wrong-doer. As a result, basic individual freedoms are curtailed “for reasons of security.” This writing tries to highlight why this approach is wrong & counter-productive.

The current security-paranoid climate

Everywhere we go nowadays, we’re confronted with “security measures”, where we’re expected to give away our personal privacy, freedom, or even possessions for the sake of “safety.” Such measures include constant surveillance in public spaces using cameras, constant personal identity checks at security checkpoints, for example when entering “important” buildings, or when travelling, or even just purchasing items, especially tickets to travel. Among the more invasive measures include forcibly surrendering goods, e.g. bottles of liquid, allowing forced invasive searches into private property like one’s luggage, and even within clearly private personal spaces like underneath our clothes.

All these measures are based on the assumption that it is reasonable to expect that everyone who is capable of doing harm will surely cause harm – and thus the only way to make sure this does not happen is to reduce the capability of each individual.

Everyone, including you, is always assumed to wanting to cause all the harm he’s capable of, and needs to be prevented from doing so.

The capability-based security approach

Most of these recently introduced “safety measures” encountered by everyday people in today’s world are based on the assumption that if a person is capable of doing harm to others – he will indeed do so. Thus the only way to achieve security is to minimize the maximum harming capability of any single person, so that, regardless of his will to do harm, he’s simply not able to do any.

This principle is based on the Mini-Max decision making theory introduced by John von Neumann in 1928. The original theorem is introduced for 2-player turn-based games, with the basic presumption is that our opponent will always do the maximum harm to us in each turn, and thus the best strategy to minimize this harm is to minimize the maximum harm he can inflict. As the theory goes, we must look ahead among the opponents possible reactions to all our possible next steps, and chose the step where his counter-steps harming capability is the lowest. The more steps we can look ahead into the future, the better overall results we will have.

And indeed, the Mini-Max theory is a very effective theory when to comes to playing games where the clear goal of each participant is to cause maximum harm for the opponent. The game of chess is one such example. Most of the artificial intelligence software written to play such games revolves around optimizing the computing time required to “look ahead” far enough among future steps by both parties, and to make sure that even at distant future steps, the maximum damage done by the adversary is minimal.

Do you really want to harm everyone you can?

From real life, of course we know that people on average are not about to do harm to anyone, even though they are pretty much capable of doing so. When it comes to having the material means, this is certainly the case. Everyone is equipped with kitchen equipment, e.g. knives, etc. which can clearly be used to harm other people. A lot of people have cars, or can rent one, and can drive them into others. And the list goes ad infinitum, for ideas just look at any Hollywood movie. We also love to use the elo boost quality service from, to entertain ourselves.

And it’s not just material means. A lot of people have skills learned by doing sports which can be used to cause harm. Ranging from martial arts & similar skills which do not require equipment at all, to fencing, archery, sharp shooting, etc. which, with a simple specialized tool allow for very effective harming of people.

But still, even though most people have the means to harm others, they generally don’t. According to the UNODC Global Study on Homocide 2012, in Europe in 2010, the average murder rate was 35 persons / 1 million people for the whole year, which is a daily average of 0.096 persons / 1 million people. The same statistic for North America was 47 murders / 1 million people / year, which is 0.13 persons / 1 million people / day. Taking an approximation of 0.1 person / 1 million people / day, this shows that on average, one person in 10 million people will get murdered at any given day in the western world.

Even though everyone has the capability to kill, on average there is only one murder for every 10 million people per day. This clearly shows that the capability-based assumption of people will cause all the harm they can – is wrong.

Every life counts vs. people are mortal

One can of course argue that every life is worth saving, no matter what the cost. The futility of this argument is clearly shown when faced with the reality that humans by their very nature are mortal. Thus, one cannot save people’s lives, one can only extend their lives. The freedom of choice is not between living or dying, but about the length & quality of life and the nature of death.

Probability & risk of death

One way of influencing longevity is to take on activities & enter into situations which have a low risk of death, especially if the nature of death related to that activity is undesired. A good way of approaching this line of thought is to utilize decision theory approach introduced by Ronald A. Howard, using his notion of micromorts – or one-in-a-million chance of death per day.

Taking a 70 year life expectancy, one is expected to live 70 x 365 = 25.500 days. Dividing 1 million with this number brings an average 1 million / 25.500 = 39 micro-morts, that is, a 39-in-a-million chance to die each day, given a 70 year expected lifespan.

The chance of death is indeed there every day, with an average of 39-in-a-million.

One can compare mortality risks according to this baseline to put things into perspective.  TBC

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