The KISS Principle is a design principle that stems from the 1960. It originated in engineering and its view point is that most systems work best if they are kept simple rather than made complicated; therefore, simplicity should be a key goal in design, and unnecessary complexity should be avoided.
And that’s entirely true.
Complex engineering systems are difficult to build, typically error prone, and even more difficult to fix and/or maintain.
But what about complex systems such as nature?
And the interlocking equally complex societal and economic systems humanity has built to use and abuse natural and societal systems?
The challenge of complexity is that complex interlocked mechanisms – such as nature, such as societal mores, such as unwrapping a failed economic system to savage the few genuinely good bits about it – have become complex for a reason: they need to full-fill thousandandone purposes, options and outcomes.
The beauty of complexity on the other hand is – and our worldly society and most of its functionality is a monumental testament to that – that we can hide a lot of ugly things in the weeds of complexity.
Things that benefit a few, but not society at large.
Things that marginalise, abuse, favour (s)elected individuals and groups.
And things that are considered ‘free’ but in reality are not. Such as natural resources.
Complexity allows to hide the ugly reality that there are some amongst us that are treated and presumed to be more equal than others.
Engineering approach to outdated and overly complex systems: Analyse, specific – and rebuild
In engineering the last resort – reluctantly, but nonetheless practised – is a re-engineering effort. To understand
- – what the existing system really does, does well, does not, and does badly/incorrectly.
- compare it with the original intent, or specification, and/or the specification as it ‘should be’.
- and then resort to (expensively) rebuilding the whole thing from scratch in the hope that the lessons of the past were learned.
Simplification would help to understand better what we have.
And to compare to what we intended to have or should be having.
It is no doubt desirable also in the context of distributing natural resources fairly.
Untangling economic operating principles from inbuilt unequal policies and principles.
And to get rid of built-in incentives that trigger undesired and destructive behaviour. Whether that is at system level (e.g. trade subsidies, or the absence of real costing for resources such as freshwater) or at local level (e.g. agricultural subsidies, or the public strategy for urbanisation that make away with green lungs around cities).
So far the philosophical aspect.
But how simple can we go before oversimplification results in incomplete, or biased data?
Before absence of consideration of relevant factors inherently lead to regrettable substitutions?
And before we willingly accept that there will be collateral damages to a decision, without knowing (or wanting to know) of what nature and in what order of magnitude these may be?
A (not always great) example in Oversimplification: Swiss referenda
In Switzerland – where I live – we have the luxury to give our political opinion via the referendum mechanism. On all sorts of things. Every quarter (3 times a year: March, June, and around October) key policy topics are brought before the citizens of this country, to be accept or reject.
In the upcoming June 2021 referendum round, two such issue will be (link in DE, FR and IT only):
- Shall we, or not, prohibit synthetic pesticides in agriculture?
- And: shall we, or not, continue to give subsidies that encourage the (abundant) use of pesticides in agriculture, as well as the prophylactic use of antibiotics in the raising of farm animals for human consumption?
I purposely use these two topics as evidently they are extremely aligned with many of the sustainability related discussion that exist in the realm of various industries: in metal and mining; in textiles; in plastics, and of course in FMCG and food.
Both of the mentioned referendum points are linked to challenges that various Swiss geographies encounter, or have encountered, in regards to the quality of their freshwater supply (in this country this typically means: groundwater).
The referenda have come into existence since a sufficient large percentage of the country’s voting population was in favour of changing the status quo and signed the respective petitions.
Sadly, the (over)simplification of the argument cuts both ways:
- those in favour of changing the status quo tend to vilify all use of pesticides for example, and threaten the whole population with the prospects of a long-winded death trough poisoning.
- those against changing the status quo tend to elevate our farming community to sainthood, threatening again the whole population with the prospects of certain starvation (through absence of produce) or poverty(through monumental price rises).
It goes without saying that neither scenario is correct in this simplified form. Both simplifications do neither justice to the topics at hand, nor to the common sense and good judgement of the voting population.
What would be needed here is a long-winded, nuanced, but also more than anything objective discussion.
And that is precisely the challenge: simplification can easily re-inforce and emphasise individual and subjective interest and affliction, rather than objective data and rational pathways.
Not always, and not invariably. But the risk is evident, and always existent.
In Conclusion
Simplification can be a good thing: it adds clarity about precisely the lobbying agenda as opposed to the scientific view. It does separate the wheat from the chaff.
Yet oversimplification leads to hyper-emotional and increasingly extreme contrasts.
To ‘either [this] or [that]’ views.
And with that to an escalation of already entrenched ‘wicked’ problems, views and approaches.
To add insult to ininjury: Oversimplification can divert the focus on what needs to be achieved, the outcome.
And mistakenly encourages to focus on the HOW (pathway) to a goal, not the goal itself.
Nothing could be more damaging and unfortunate. Because as Einstein well said:
We can’t solve problems by using the same kind of thinking we used when we created them.
Albert Einstein
Funnily enough: the actually required solution pathway may well lay entirely outside this continuum of existing ‘either, or’ solution space …
