Science for Complexity
Especially in human-related sciences, holding on to a Platonean ideal is insufficient for grappling with present-day challenges. We need new science to manage complexity.
A.I. can provide the necessary tools for this.
Science of medicine and psychosomatics
Until now, medical science has been based on a non-complex picture of the human being. This accords with only a minor part of the latter.
In psychosomatics, we encounter complexity to the max. This cannot be adequately managed with only ‘old hat science.’ An exclusive use of such may have the side effect of discarding the whole field as non-scientific. With science for complexity, the field can be drawn toward within the scientific world by broadening this world.
Intriguingly, it’s the discarding side that then becomes unscientific ― a modern Copernican revolution. As usual, several vested interests won’t like this. Nevertheless, reality and humanity demand it to go through.
Is this science replicable?
Sure, it’s replicable in bigger amounts of numbers. Moreover, since there is no need for extrapolation, there is also no need for being exactly replicable. The science is proper when the replications are well enough. Compare this with the reproducibility crisis of present-day psychotherapy.
With enough user input, replicability can be achieved in Lisa, for instance. Also, this way, Lisa science doesn’t have one endpoint but a whole landscape. Exemplars can be extracted from this landscape for reasons of communication.
Abstractly seen, in a list of bullet points:
- We have a well-established – though still evolving – science for the conceptual world.
- Reality is conceptual AND subconceptual.
- We need a science for complexity — a pending revolution in the scientific domain.
- Once accomplished, both sciences will be integrated into a ‘science for everything.’
- This will coincide with the advent of super-A.I. through the solving of the issue of abstracting patterns.
- Intriguingly, both directions start from different poles, but they will end up in the same synthesis.
Within the clash, of course, the implications for science itself are immense.
That can lead to people’s loss of faith in the scientific construct. We should think about the possible implications of this and how to mitigate them.
Gliding back to magical thinking is a real danger. Therefore, we should strive for more science, not less ― quite a universal challenge for universities!
More than healthcare
Of course, healthcare is explicitly an exciting domain for this because, among other things, it invites massive amounts of communication with many people.
Data and knowledge from this may kickstart science for complexity in other human-related domains (the so-called humanities) as well.
Let’s go for all this.
Let’s go for science with a heart.
Related Posts
The Confusing Confounding Factors in Science
‘Confounding factors’ sound like a technical nuisance, something to be corrected and forgotten. Yet in many areas of science, especially when humans are involved, this term quietly shapes what is deemed central and what is pushed aside. This blog explores how confounding can clarify — but also mislead when depth is mistaken for interference. Sometimes, Read the full article…
Why a ‘Good Mindset’ Doesn’t Work
A ‘good mindset’ sounds harmless — even admirable. But beneath its shiny optimism lies a dangerous misunderstanding of the mind itself. A ‘good mindset’ just isn’t good enough. In psychosomatics, a ‘good mindset’ is still frequently heralded as a panacea to ‘heal yourself.’ As the writer of a book with that same title in Dutch Read the full article…
Are You Ready for the Biggest Adventure of All Times?
For centuries, humanity has sailed forward — through wars, revolutions, disasters, and progress. The world changed, yet history moved on, always more or less the same. Technology has always been at our side, helping us repair, rebuild, and move forward. But now, something is different. On the horizon, a storm is forming — not just Read the full article…