Via positiva / Via negativa

Via positiva         -     Via negativa
Is                         -      Is not
Ideal                     -     Real
Future                  -     Past
Closed                 -      Open

[...] reasoning has not evolved in the ways that we think it has – as a process of ratiocination that is intended independently to figure out the world. Instead, it has evolved as a social capacity – as a means to justify ourselves to others.

We want something to be so, and we use our reasoning capacity to figure out plausible seeming reasons to convince others that it should be so. However, together with our capacity to generate plausible sounding rationales, we have a decent capacity to detect when others are bullshitting us.

In combination, these mean that we are more likely to be closer to the truth when we are trying to figure out why others may be wrong, than when we are trying to figure out why we ourselves are right.

This superficially looks to resemble the ‘overcoming bias’/’not wrong’ approaches to self-improvement that are popular on the Internet. But it ends up going in a very different direction: collective processes of improvement rather than individual efforts to remedy the irremediable.

The ideal of the individual seeking to eliminate all sources of bias so that he (it is, usually, a he) can calmly consider everything from a neutral and dispassionate perspective is replaced by a Humean recognition that reason cannot readily be separated from the desires of the reasoner.

We need negative criticisms from others, since they lead us to understand weaknesses in our arguments that we are incapable of coming at ourselves, without them being pointed out to us.

we likely radically underestimate the importance of the invisible and non-individually lucrative contributions that people make to the collective benefit by improving others’ ideas.

[Henry Farrell]
'In praise of negativity'

There are many things without words, matters that we know and can act on but cannot describe directly, cannot capture in human language or within the narrow human concepts that are available to us. Almost anything around us of significance is hard to grasp linguistically - and in fact that more powerful, the more incomplete our linguistic grasp.

But if we cannot express what something is exactly, we can say something about what it is not - the indirect rather than the direct expression. The “apophatic” focuses on what cannot be said directly in words, from the Greek apophasis (saying no, or mentioning without mentioning).

The method began as an avoidance of direct description, leading to a focus on negative description, what is called in Latin via negativa, the negative way […] Via negativa does not try to express what God is - leave that to the primitive brand of contemporary thinkers and philophasters with scientistic tendencies. It just lists what God is not and proceeds by the process of elimination.

The greatest - and most robust - contribution to knowledge consists in removing what we think is wrong - subtractive epistemology […] we know a lot more what is wrong than what is right, or, phrased according to the fragile/robust classification, negative knowledge (what is wrong, what does not work) is more robust to error than positive knowledge (what is right, what works).

So knowledge grows by subtraction much more than by addition - given that what we know today might turn out to be wrong but what we know to be wrong cannot turn out to be right, at least not easily.

[…] since one small observation can disprove a statement, while millions can hardly confirm it, disconfirmation is more rigorous than conformation.

[Nassim Nicholas Taleb]
Antifragile, p.301, 303

The Via Negativa (also called the Apophatic Way) focuses on explaining the nature of God by focusing on what God is not (‘apophatic’ comes from the Greek term ‘to deny’).

The via negativa is based on the fundamental belief that ‘God’ is beyond human understanding and description – ‘He’ is completely ineffable. This belief in the ineffability of God is derived from the Neoplatonists (later interpreters of Plato), such as Plotinus and Augustine. The Via Negativa itself is found particularly in the writings of Pseudo-Dionysius and Moses Maimonides.

Any attempt to use human language to describe God is anthropomorphic. He saw it as necessary for the less intelligent, but it was still a ‘second-best’ approach as “the sun is hidden to eyes that are too weak to comprehend it.”

[Amy Trumpeter]
‘What is the Via Negativa?’

Related posts:


Order                  -          Chaos
Closed                -          Open
Efficiency           -          Evolvability

Metastable: poised, ready to react.

Myths and stories are good for criticality because they allow a degree of wiggle-room. Theories have a tendency to coagulate into paradigms, or strong attractors, which can only be escaped when their proponents die off.

In physics, metastability is a stable state of a dynamical system other than the system's state of least energy.

A ball resting in a hollow on a slope is a simple example of metastability. If the ball is only slightly pushed, it will settle back into its hollow, but a stronger push may start the ball rolling down the slope.


You can have something that’s very fragile but stays for a very long time.

In phase transitions - between gaseous, liquid, and solid forms - there is a thing called a metastable state. The material is already at the right temperature for, say, water to start boiling, but because there is no disturbance to it, it stays in the previous transition. If you then drop a little speck into this kettle of metastable water, it will instantly start boiling.

I think societies when they become stabilised or inactive in this way, they’re in a metastable state. And they can last there for centuries. It’s very similar to a dry forest.

[Samo Burja]
Live Players w/ Samo Burja (June 18, 2020)

[…] many composite systems naturally evolve to a critical state in which a minor event starts a chain reaction that can affect any number of elements in the system.

Although composite systems produce more minor events than catastrophes, chain reactions of all sizes are an integral part of the dynamics. According to the theory, the mechanism that leads to minor events is the same one that leads to major events.

Furthermore, composite systems never reach equilibrium but instead evolve from one meta-stable state to the next.

When a number of trajectories lead towards a point (or area) in state-space, that point (or area) is an 'attractor', and represents a stable state of the system. When trajectories all lead away from a point, that point is unstable - a 'repellor'. A point that has trajectories leading towards it as well as away from it is known as 'meta-stable'.

[…] In a very stable system there will be one, or only a few strong attractors. The system will quickly come to rest in one of these, and will not move to another one easily. The resulting behaviour of the system is not very interesting. On the other hand, in a very unstable system, there will be no strong attractors, and the system will just jump around chaotically.

The theory of self-organised criticality tells us the following. A self-organising system will try to balance itself at a critical point between rigid order and chaos. It will try to optimise the number of attractors without becoming unstable.

[Paul Cilliers]
Complexity and Postmodernism, p.96-7

[…] empirical evidence has proliferated that living systems might operate at criticality - i.e. at the border-line between order and disorder - with examples ranging from spontaneous brain behavior to gene expression patterns, cell growth, morphogenesis, bacterial clustering, and flock dynamics.

[…] why is a living system fitter when it is critical? Living systems need to perceive and respond to environmental cues and to interact with other similar entities. Indeed, biological systems constantly try to encapsulate the essential features of the huge variety of detailed information from their surrounding complex and changing environment into manageable internal representations, and they use these as a basis for their actions and responses.

The successful construction of these representations, which extract, summarize, and integrate relevant information, provides a crucial competitive advantage, which can eventually make the difference between survival and extinction.

[…] criticality is an optimal strategy to effectively represent the intrinsically complex and variable external world in a parsimonious manner.

This is in line with the hypothesis that living systems benefit from having attributes akin to criticality - either statistical or dynamical - such as a large repertoire of dynamical responses, optimal transmission and storage of information, and exquisite sensitivity to environmental changes.

As conjectured long ago, the capability to perform complex computations, which turns out to be the fingerprint of living systems, is enhanced in “machines” operating near a critical point, i.e., at the border between two distinct phases: a disordered phase, in which perturbations and noise propagate unboundedly - thereby corrupting information transmission and storage - and an ordered phase where changes are rapidly erased, hindering flexibility and plasticity.

The marginal, critical situation provides a delicate compromise between these two impractical tendencies, an excellent tradeoff between reproducibility and flexibility and, on larger time scales, between robustness and evolvability.

Any given genetic regulatory network, formed by the genes (nodes) and their interactions (edges), can be tightly controlled to robustly converge to a fixed almost-deterministic attractor - i.e. a fixed “phenotype” - or it can be configured to be highly sensitive to tiny fluctuations in input signals, leading to many different attractors, i.e., to large phenotypic variability.

These two situations correspond to the ordered and disordered phases, respectively. The optimal way for genetic regulatory networks to reconcile controllability and sensitivity to environmental cues is to operate somewhere in between the two limiting and impractical limits alluded to above.

Under the mild assumption that living systems need to construct good although approximate internal representations of the outer complex world and that such representations are encoded in terms of probability distributions, we have shown - by using concepts from statistical mechanics and information theory - that the encoding probability distributions do necessarily lie where the generalized susceptibility or Fisher information exhibits a peak, i.e., in the vicinity of a critical point, providing the best possible compromise to accommodate both regular and noisy signals.

[Hidalgo, Grilli, Zuweist, Muñoz, Banavar, & Maritan]
‘Information-based fitness and the emergence of criticality in living systems’

[…] this is what basically is going on in relevance realization. You can see it in your attention: 'default mode' and 'task centre'. ‘Default’ is making your mind wander and introduce variation, and then task focus selects. You kill off most of the variations, but some of them come in because your mind wandered enough.

You give people a problem and they're impassing - they can't solve it - and you just introduce a little bit of entropy into the system - you put some static on the computer screen or you shake it - then they'll have the insight because it puts in enough criticality.

They stop this unidimensional task focused attention and it allows the spread of activation. Then they reselect and they evolve a new way of framing the problem.

[John Vervaeke]
‘A Conversation So Intense It Might Transcend Time and Space | John Vervaeke | EP 321, YouTube

Vervaeke: […] you get a system simultaneously differentiating and integrating […] a system that is complexifying. If it's done right, because of adaptive fittedness its complexification is increasingly conforming to the complexity of the world.

Peterson: That's the scientific enterprise in some sense, right? Calibration against real world patterns.

Vervaeke: If it has good synoptic integration, it has self organising criticality. When it fires in self-organizing criticality, it tends to create a small world network wiring. It’s mostly organized, but when it breaks apart it opens up the possibility of one of these long distance connections. If a system starts to wire as a small world network, it has mostly regular connections keeping you in the norm, but with a few long distance connections that can suddenly snap you out.

Peterson: That's like the balance between conservatism and liberalism.

Vervaeke: If it fires at self-organizing criticality, it tends to wire as a small world network. And if it wires as a small world network, it tends to fire as self-organizing criticality. So these two things can mutually inform each other.

The self-organizing criticality theory of insight - you have to break out of an inappropriate frame, that's the criticality, and it reorganizes into the better frame. You do that evolution.

Peterson: And ‘better’ would be something like, both efficient and capable of performing a broader range of action. That was like a Piagetian description of what constituted a better theory. A better theory allows you to do everything the previous theory allowed you to do, plus something more, hopefully with a gain of efficiency.

Vervaeke: A good theory is efficient in that sense, but a good theory is also generative. You're always trying to optimize between efficiency and evolvability. You don't just do compression - that's epilepsy. You've just locked the system down and it has no capacity to adaptively refit itself to the world.

I think of this as mapping on to Piaget’s notion of assimilation and accommodation. Assimilation is compression, making everything integrated; accommodation is how you introduce [variety]; and then the calibration is this dynamical, constantly trading between them.

You don't come to any kind of stable thing. You're constantly evolving. You don't find the final theory - you're constantly moving to a theory that grabs more differences and yet brings them into an integration.

[Jordan B. Peterson & John Vervaeke]
‘A Conversation So Intense It Might Transcend Time and Space | John Vervaeke | EP 321, Jordan B. Peterson, YouTube

Related posts:

The Adjacent Possible

The concept of the adjacent possible originates from Stuart Kauffman and his work on biological evolution.

Kauffman was particularly interested in the origins of order and the mechanisms that drive self-organization. His findings are broadly applicable to any complex adaptive system, be it natural like the biosphere, or human-made like cities, the economy, or technology.

Kaufman investigates how the actual expands into the adjacent possible. The actual describes the system under investigation in its current state, with all its components and interconnections. The adjacent possible contains all the elements outside but near that system; those represent the opportunities for the current system to expand by building new connections and turning those elements into system components.

[...] expanding any realm always requires leaving its current boundaries in order to explore ‘the possibilities out there‘. But rather than chasing the most extreme or distant possibilities, successful exploration focuses on the immediate vicinity of the current boundaries: Expansion can then occur by naturally ingesting nearby possibilities, by a short stretch of the realm’s new boundaries.

Therefore, the adjacent possible is the target of successful exploration and expansion.

Innovation is no exception from that general observation. To expand the realm of what we can do, innovation explores the wellspring of novelty in the adjacent possible. This concept of the adjacent possible could therefore help us frame our evolving understanding of innovation and gain new insights.

[Ulf Ehlert]
'Exploring the adjacent possible – The origin of good ideas'

So how do you change a system which is entrained around perverse behaviour?

And this applies to culture change in organisations as much as it does to wider society change [...] From my anthro-complex perspective the following stages are necessary:

1. Map the current dispositional state of the system.  What are the attractors in play, how stable are they?

2. Within those maps identify what Kauffmann [termed] the adjacent possible, patterns of behaviour adjacent to the present but in a more desirable position.  Radical change is hard and may have unintended consequences, smaller shifts are easier to achieve.

3. If there are no adjacent possibles, or the nature of system is such that the energy cost of escape is too great, then you need to take actions that disrupt or perturb the existing attractor mechanisms to allow the adjacent possible to emerge.  Until that happens change is very difficult.

[Dave Snowden]
'The adjacent possible'

The zone of proximal development, often abbreviated as ZPD [...], is best understood as the zone of the closest, most immediate psychological development of the children that includes a wide range of their emotional, cognitive, and volitional psychological processes. 

In contemporary educational research and practice, though, it is often interpreted as the distance between what a learner can do without help, and what they can do with support from someone with more knowledge or expertise ("more knowledgeable other").

The concept was introduced, but not fully developed, by psychologist Lev Vygotsky during the last three years of his life. Vygotsky argued that a child gets involved in a dialogue with the "more knowledgeable other" such as a peer or an adult and gradually, through social interaction and sense-making, develops the ability to solve problems independently and do certain tasks without help.

Following Vygotsky, some educators believe that the role of education is to give children experiences that are within their zones of proximal development, thereby encouraging and advancing their individual learning such as skills and strategies.

'Zone of proximal development'

"I spent years trying to get my early things published,” Rosch recalls. “Journals would send them back, finding fussy little things wrong with them, and saying, ‘Everyone knows this isn’t true.’”

Why did they balk?

“If something is going to be new, it has to be exactly in the right degree of difference from what’s going on for people to say, ‘That’s interesting,’” she says. “If it’s too new, it isn’t understood.”

[Daniel McNeill & Paul Freiberger]
Fuzzy Logic, p.88