Social construction of neuronormative reality

Many medical doctors, engineers of all stripes, economists – and all other professions that serve the established social order, as well as celebrities, are co-opted into the cult of individual busyness, where they all defer the most important decisions to power drunk “leaders” in industry and government.

I have yet to see any design initiative from a larger organisation that does not have the primary objective (often unspoken) of maintaining and strengthening established power gradients. The unspoken ‘universal law of social design’: Institutional power must be reinforced. The discipline of design has been co-opted to perpetuate and strengthen established oppressive systems of power.

This is why it so-called diversity, equity, and inclusion initiatives fail.

This is why Autistic perspectives are marginalised in autism research.

This is why government strategies to deal with existential threats are based on incrementalism and on kicking the can down the road.

People engage in magical thinking when they believe they contribute to genuine change by making things a bit less bad within a small silo within an established system of power that optimises for profit and material growth. Less growth is still growth. Less unsustainable is still unsustainable. And no level of incrementalism within the system will ever lead to a reduction in the overall ecological and material footprint of humans. It is common practice to obscure the universal law of social design by relabelling institutions, changing reporting structures – known as reorganising, but nothing ever changes for those at the receiving end of institutional power.

William C. Rees does an excellent job of describing how the construction of social “reality” has completely decoupled from the physical and biological world – humans are animals, and this decoupling is having massive health impacts. Most of W. C. Rees’ observations are spot-on, but he underestimates the long-term multi-generational perspective that is baked into some if not many indigenous cultures. Internalised social norms can either amplify the short-term thinking, or they can maximise the human capacity for long-term thinking within the constraints of human cognitive limits.

My understanding of individual human cognitive limits, social dynamics, and collective human capabilities is informed by what I have observed in many different small team environments that are embedded in larger institutional settings, in the context of what I refer to as ‘knowledge archaeology’. I have seen and measured several fold reductions in spurious cultural complexity that become possible in small high trust de-powered (i.e. safe) social environments.

In our industrialised world knowledge archaeology extends into the domain of software and data intensive systems. Having used tools to analyse and visualise the dependencies between millions of lines of code, and having seen how engineers naively (ab)use abstract mathematics to cobble together so-called machine learning systems, has equipped me with with a high level of techo-scepticism. It is very easy for those who have not waded through the mud of big junk data to get sucked into magical thinking about technological options going forward. Fully open and transparent science, and establishing a global knowledge commons are very important, but such efforts are crippled in a hyper-competitive, i.e. learning disabled world of exponentially growing junk data.

I empathise with much of what Daniel Schmachtenberger talks about, and the way he is looking for ways to protect humans from our own stupidity, but in doing so, at times I feel he over-estimates (a) the potential and usefulness of digital technologies and (b) our ability to understand the world beyond human scale – by definition we can’t. Being able to think in abstract terms about super human scale systems does not equate to a deeper understanding of such systems, it does not give us additional predictive powers, but it can alert us to super human scale phenomena that we should be monitoring and measuring. It comes down to how low or how high we want to set the bar for what we consider “understanding”. You can listen to the following interview with Walid Saba on the state of the art of human language processing and then think about how this fits together with André Spicer‘s observations on institutionalised and sanctified BS and genuine concerns about big junk data.

In much of the W.E.I.R.D. world BS is the only thing that still “sells”. The entire economy is a game of perception management, there is no substance left underneath. The evidence is now everywhere. If you attempt to sell anything that is not largely BS, something that actually delivers or contributes towards valuable services to people at the grassroots level, by definition you are not advancing the perception management game, and hence none of those who attempt to secure their position within the established system will buy from you.

Life is too short for BS. The competitive corporate way of life is not healthy for anyone. Most people are trapped by the culture that surrounds them, they are prisoners. In contrast, the few Autistic and otherwise neurodivergent people who focus entirely on what they consider ethical and genuinely valuable, who grow their competency network this way, co-create initiatives with the people they deeply appreciate and genuinely trust, and ultimately that’s what matters.

The institutional crisis, especially in W.E.I.R.D. countries, is very real. The disease is terminal. In the Autistic community we are open about this and about the harm this causes in terms of mental and physical health. More “culturally well adjusted” people are likely having similar experiences, only they don’t talk about it nearly as openly and honestly in a society that is built entirely around “success” and “growth”.

In this interview Nate Hagans is chatting with Berry Liberman in Australia, who is beginning to get her head around the extent to which “investment” is broken. Money as we know it is a legacy technology. Less “developed” countries are a big step ahead. Their populations are used to not being able to rely on institutions, and this gives them a much better grasp on reality. I agree with Indrajit Samarajiva, science will not “save” us. To feel alive, we need healthy lifetime relationships with a few trustworthy people, to feel comfortable in our skin, stop betraying ourselves, and we need to engage with the physical and biological world on a daily basis.

High fidelity conceptual models of our rich internal worlds

The atoms of thought

Human mental models have been around for much longer than human language. To understand the core mechanisms of human reasoning and thinking, and to appreciate the dangerous limitations of human language, we need to step back in time and look at how language evolved from a biological perspective.

Here is a synopsis of thinking tools that predate human language:

1. Humans and a some other animals are capable of shared attention. I can look at something and detect that another animal is looking at the same thing, and I understand that we are both seeing the same thing, whilst realising that we may have wildly different perspectives on the thing (associations with past experiences) that we see. Someone who has never seen or heard of a gun may not know that it can kill. I can also observe two people who are looking at some object, and I understand that their minds are focused on that object.
2. Beyond awareness of shared attention humans have evolved limbs that allow us to point to things, to further disambiguate and make it more obvious what we are focusing on.
3. Humans and other animals create mental representations (= models) of the things we interact with.
4. Furthermore humans and some animals can identify commonalities between things (abstract/generalise) and create mental models of groups of similar things (= categories).
   • … and can identify spatial relationships between things (containment and connectors) and create mental models of these relationships (= graphs).
   • … and can identify changes over time (movement of things) and create mental models of patterns of movements (= operations).
5. Humans and perhaps also some animals can apply their pattern recognition and abstraction abilities to operations, leading to mental representations that contain abstract operations.
6. Humans and perhaps also some animals rely on their mental models to conduct extensive simulations to predict events and arrive at decisions. In some domains this happens subconsciously and very fast, and in other domains we are capable of slower and deliberate conscious simulations.

We and other animals can do all of these things without talking. No spoken or written language is required. Mental models and reasoning clearly came first. Human language came second.

I have gained extensive experience simply by living with fairly severe autism for my lifetime. Difference can be wonderful, and autism shouldn’t be tampered with, or altered. Autistic people shouldn’t be changed…

The autistic individual certainly has a right to this special home within. It is not a dream world as some dictionaries imply. It’s not a spot in the mind filled with hallucinations. Rather the person sees what is around him with extra-acute sight…

An autistic experiencing the outside world experiences it as surreal, not as a made-up work of art in the mind. You can’t judge the world of another as inferior, because you don’t live in that world…

The autistic world is comfortable. It is a safe place to ground oneself in. Autistic children can keep their inner sanctuaries, as well as grow and learn, and become educated…

It is a very bad idea to force one’s way into an autistic’s world. That is a grave threat to the autistic person. … All things coming from the outside must be gentle, sometimes devoid of emotion, so as to not overwhelm…

Jasmine Lee O’Neill. Through the Eyes of Aliens – A Book About Autistic People. 1999.

Autistic artistic expression

The arts, and music, and mathematics are human scale tools for communicating the essence of complex patterns of mental states (knowledge, feelings, and awareness of agency and motivations) that don’t survive simplistic attempts of serialisation and de-serialisation via stories. The outputs of the arts, music, and mathematics are highly generative, they can’t be described in any simple story. Instead they open up and invite a multitude of complementary interpretations.

The arts and music are essential communication and exploration tools for feelings, agency, and motivations, and the application of mathematical theories has become a critical part of a growing number of knowledge intensive disciplines. The essence of the scientific method is the combination of the atoms of thought with the technique of validation via instantiation.

The art of explanation

Paul Lockhart (2002) describes mathematics as the art of explanation. He is correct. Mathematical proofs are the one type of storytelling that is committed to being entirely open regarding all assumptions and to the systematically exploring all the possible implications of specific sets of assumptions. Foundational mathematical assumptions are usually referred to as axioms.

Formal proofs are parametrised formal stories (sequences of reasoning steps) that explore the possibilities of entire families of stories and their implications. Mathematical beauty is achieved when a complex family of stories can be described by a small elegant formal statement. Complexity does not melt away accidentally. It is distilled down to the its essence by finding a natural language (or model) for the problem space represented by a family of formal stories.

A useful model encapsulates all relevant commonalities of the problem space – it provides an explanation that is understandable for anyone who is able to follow the reasoning steps leading to the model.

Explaining the language of symbolic thought

As humans we are familiar with spoken human language, and with written human language, encoded in one of the established symbol systems (or alphabets) that predate the invention of modern computers. Additionally, humans have developed specialised symbol systems for recording definitions of music, for expressing mathematics, for traffic signs and signals, electronic circuit designs, etc. – all these symbol systems are considered as languages in the mathematical discipline of model theory. In fact, symbol systems predate humans by billions of years; the genetic code is clearly a language in the model theoretic sense – and even pheromones constitute a language.

Without delving into the formal mathematical details, the significance of model theory is best appreciated intuitively by considering the following observations:

1. Linguistics as pioneered by Noam Chomsky in the 1950s and 1960s as well as the work on generative semantics and metaphors by George Lakoff can be formalised via model theory.
2. The work of model theorists goes back to the beginning of the 20th century, and was motivated by mathematicians who were concerned about potential logical inconsistencies in the mathematical symbol system and the conventions governing its use.
3. The resulting introspective research into symbol systems has led to a mathematical theory that can be used to formalise any symbol system, not limited to the languages invented by humans, and including the genetic code.
4. All non-linear symbolic diagramming notations can easily be formalised mathematically.

The desire to understand and be understood

Human minds are the tools that connect the physical dimension of our existence to other living creatures, and to a rich internal world, which integrates our own perceptions into a seemingly coherent representation of the external world around us. Human minds can develop amazing capabilities, but at the same time, our cognitive capacities are limited. To ensure we understand each other, we must know our limits, and we must co-create safe spaces for engaging in de-powered dialogue.

As soon as spoken language entered our world, initially as a serialisation format for communicating simple references to things within our local context, things started to get messy. We started to reference abstract things, references to references, and experiences that occurred many years ago. From that time onwards I suspect the number of misunderstandings in communication grew exponentially.

Language allows us to create rough and speculative models of what might go on in another mind. But since people can not visit the past of other people, this lead us down the path of extensive social delusion, where we started to assume that we understand each other much better than we actually do.

Validation of shared understanding by instantiation of abstractions with concrete examples usually only comes into play when harsh reality points people to concrete misunderstandings. In many contexts something like the 80 / 20 rule is good enough for language to be a useful and viable tool. Making correct assumptions 80% of the time is good enough for many day to day life scenarios for the majority of people.

With the evolution of the human capacity for language, the seeds for storytelling had been sowed. The first human hive minds emerged. Written language made things even worse in terms of the scope of the social delusion, it gave people opportunities to “read” large volumes of information out of context in space and time. Many of the written words of old and distant texts seem familiar – as needed with the help of a translator (another source of potential misunderstandings), and people end up importing many thousands of references to very unfamiliar abstractions into their mental models on top of their first hand experiences.

We all know that human imagination knows few limits, but at the same time we like to believe that we “understand” what others have written, without necessarily realising the contradiction. The human tendency to believe in the validity of our imagination after hearing or reading a story allowed storytelling and belief systems to rise to new heights.

With language, human culture increasingly became defined by myths residing within hive minds. At that stage a few people started scratching their heads about weird human social behaviours and associated rituals and beliefs. In today’s society, within the pathology paradigm of Western medicine, such people would be labelled Autistic.

Being hypersensitive in a hyper-normative world

Autistic people easily get depressed and develop physical health conditions when having to survive in social environments that deny Autistic authenticity and that continuously expect Autistic people to conform to neuronormative cultural rituals. Sooner or later, unless the Autist is able to shift or change the environmental context, recurring traumatic experiences result in chronic depression and Autistic burnout.

Autistic and other hypersensitive people are traumatised by being punished for being authentic, for example by asking clarifying questions or for being honest about our feelings or our knowledge, or alternatively, by the cognitive dissonance of attempting to conform to toxic social expectations.

Autistic people are mostly made to suffer for being authentic. If we attempt to conform, due to our limited capacity for cognitive dissonance, we experience existential depression at a very young age, often as children, and without any agency to construct or retreat to a safe environment, without access to Autistic community. We grow our compassion and mutual understanding by de-powering all our Autistic dialogues, which is the only path for healing in a hyper-competitive deceptive world.

In the industrial era human scale ecologies of care have been systematically replaced by atomised families and super human scale abstract group identities (brands, nationalities, parties, sports teams, professional identities, etc.), thereby crippling people’s ecological understanding, their basic understanding of what it means to be alive, including their ability to trust themselves and each other at human scale.

The ability to extend trust to oneself and others depends on, and can only be (re)learned through the lived experience of being embedded in an ecology of care over an extended period. Prolonged absence of a healthy ecology of care can lead to self-hatred and related chronic health problems.

The relational understanding of groups

In order to feel safe, Autistic people need access to authentic Autistic culture and opportunities to develop Autistic relationships.

We can reframe the notion of social group, to highlight the relational aspect of social groups as the main characteristic of culture.

A cultural organism : the set of all the relationships of a core set of people, including all the relationships that these people have with people beyond the core set, i.e. a cultural organism always includes a boundary layer that connects the organism to the outside world.

This reflects the complexity and diversity of the world we live in, and it also reflects on the fact that within a group everyone is surrounded by a unique ecology of care – the relationships that each individual maintains. Our ecology of care should be a safe place for Autistic dialogues, where Autistic openness, honesty, and curiosity is appreciated, and where our strong aversion to coercive pressures and all forms of social hierarchies is respected. Autistic culture evolves via Autistic dialogues within a human scale cultural organism:

• We discover semantic equivalences between shared mental models
• We discover differences in mental models and lived experiences
• We consciously agree on the level of shared understanding
• We consciously acknowledge differences in lived experiences
• We feel seen and understood
• We (re)learn to extend trust and be trusted
• We develop unique and deep Autistic relationships
• We co-create and collaborate as part of unique neurodivergent competency networks

Numerical scientific models that are fitted to observable data

The scientific revolution and the application of numerical mathematical techniques undoubtedly led to a better understanding of some aspects of the world we live in, enabling humans to create more and more complex technologies. But it also created new levels of ignorance about externalities that went hand in hand with the development of new technologies, fuelled by specific economic beliefs about efficiency and abstractions such as money and markets.

In the early days of the industrial revolution modelling was concerned with understanding and mastering the physical world, resulting in progress in engineering and manufacturing. Over the last century formal model building was found to be useful in more and more disciplines, across all the natural sciences, and increasingly as well in medicine and the social sciences, especially in economics.

With 20/20 hindsight it becomes clear that there is a significant lag between model building and the identification of externalities that are created by systematically applying models to accelerate the development and roll-out of new technologies.

Humans are biased to thinking they understand more than they actually do, and this effect is further amplified by technologies such as the Internet, which connects us to an exponentially growing pool of information. New knowledge is being produced faster than ever whilst the time available to independently validate each new nugget of “knowledge” is shrinking, and whilst the human ability to learn new knowledge at best remains unchanged – if it is not compromised by information overload.

Those who engage in model building face the challenge of either diving deep into a narrow silo, to ensure and adequate level of understanding of a particular niche domain, or to restrict their activity to an attempt of modelling the dependencies between subdomains, and to coordinating the model building of domain experts across a number of silos. As a result:

• Many models are only understandable for their creators and a very small circle of collaborators.
• Each model integrator can only be effective at bridging a very limited number of silos.
• The assumptions associated with each model are only known understood locally, some of the assumptions remain tacit knowledge, and assumptions may vary significantly between the models produced by different teams.
• Many externalities escape early detection, as there is hardly anyone or any technology continuously looking for unexpected results and correlations across deep chains of dependencies between subdomains.

When the translation of new models into new applications and technologies is not adequately constrained by the level to which models can be independently validated and by application of the precautionary principle, potentially catastrophic surprises are inevitable.

Numerical models in the natural sciences

The usefulness of numerical, statistical, and probabilistic models rests on the assumption that there is an objective reality out there that can be approximated by a set of abstract numerical parameters and formal relationships between these parameters in a way that provides us some level of predictive capability and thereby a deeper understanding of a particular aspect of reality.

This approach has led to impressive results in the natural sciences, in particular in physics, physical chemistry, and computational biology, including techniques for modelling and better understanding some aspects of complex and chaotic systems.

The more parameters and relationships between parameters come into play, the more difficult it typically is to uncover cognitively simple models that shed new light onto a particular problem space and the underlying assumptions. If a particular set of formal assumptions is found to have a correspondence in the physical or living world, the potential for positive and negative technological innovation can be profound. Whether the positive or negative potential prevails is determined by the motivations, political moves, and stories told by those who claim credit for innovation.

Statistical models in the social sciences

Psychology and other social sciences differ from the natural sciences in that they are dealing with humans, i.e. with conscious agents that have rich internal worlds and unique lived experiences on the one hand, and that are heavily influenced by the culture they are embedded in on the other hand.

The application of numerical techniques in this context inevitably involves over-simplifying assumptions about human individual and collective behaviour.

Often specific ideological assumptions are deliberately introduced to allow specific people and institutions to benefit economically from the output of specific predictive models and algorithms.

In the ideology of the invisible hand that applies the industrial factory metaphor to society, the only things that count in are things that can be measured. It is no coincidence that scientific management (Taylorism) was conceived in the wake of the invention of the steam engine and machine assisted manufacturing, to complement the the laws of physics that governed the mechanics and the productivity of the machines on the factory floor. The discipline of economics allowed the scientific approach to managing humans to be extended to the scale of nation states – as a conceptual building block for organising human activities in industrialised societies.

There are a number of parallels between the impact of the development of economic theories on human society and the social impact of the development of the Internet. Neither the Internet nor economics draw directly on an evidence based understanding of physics, biology, and human cognitive diversity.

Both the Internet and economic theories are best understood as prescriptive rather than observational tools – as language systems that are based on specific European/North American cultural conventions that are assumed to be “sensible” (common sense) or “obvious” (self-evident).

With these language systems in place you can measure data flows and economic performance, but only in terms of the scope and the preconceived categories afforded by the formal protocols and languages. The introduction of a formal economic language system and the introduction of formal protocols for digital communication have shaped human culture around the social ideologies espoused by early industrialists and early information technology entrepreneurs.

Over course of the last two centuries governments have become increasingly dependent on economists and information technology entrepreneurs in order to understand and engage with society, and also to understand what what technological possibilities are appearing on the horizon. In this process anything that lies beyond the scope of economic doctrine is discounted as non-essential or unproductive.

The ideological bias in the disciplines of psychology and psychiatry is no less concerning. Psychologists are only starting to acknowledge the scale of the immense harm and the many deaths caused by dehumanising cultural bias and inappropriate use of over-simplified statistical models.

The interview below is a good example of the depth of the ideological bias that has shaped the field over the course of the last 150 years. From an Autistic perspective the persistent behaviourist attempts to impose cultural expectations from the outside, and the level of ignorance about the relevance of rich inner worlds and individually unique mental models remains disturbing.

Many Autistic people have suffered some form of abuse throughout their childhood from their caregivers. Broken trust is at the core of Autistic trauma. We are not equipped for life in industrialised societies that are all about perception management, where even “education” of small children in primary school is focused on topics such as persuasive writing. What is completely lacking in the neuronormative world around us is a culture that appreciates the open dialogues necessary to nurture and deepen shared understanding, and to discover and openly acknowledge the boundaries of shared understanding at each stage of the journey.

Conceptual models vs narratives

Whenever storytelling and related tools of persuasion are used to transmit and replicate beliefs, as is usually the case in politics and marketing, critical validation becomes essential to minimise misunderstandings and attempts at deception. If we value the creation of cultures of thinking, then the risks of deceptive storytelling need to be acknowledged, and exploration and critical validation of knowledge, feelings, agency, and motivations must be encouraged.

The art of storytelling is linked to the rise of marketing and persuasive writing. Edward Bernays was one of the original shapers of the logic of marketing:

Bernays’ vision was of a utopian society in which individuals’ dangerous libidinal energies, the psychic and emotional energy associated with instinctual biological drives that Bernays viewed as inherently dangerous given his observation of societies like the Germans under Hitler, could be harnessed and channelled by a corporate elite for economic benefit. Through the use of mass production, big business could fulfil the cravings of what Bernays saw as the inherently irrational and desire-driven masses, simultaneously securing the niche of a mass production economy (even in peacetime), as well as sating what he considered to be dangerous animal urges that threatened to tear society apart if left unquelled.

Bernays touted the idea that the “masses” are driven by factors outside their conscious understanding, and therefore that their minds can and should be manipulated by the capable few. “Intelligent men must realize that propaganda is the modern instrument by which they can fight for productive ends and help to bring order out of chaos.”

The conscious and intelligent manipulation of the organized habits and opinions of the masses is an important element in democratic society. Those who manipulate this unseen mechanism of society constitute an invisible government which is the true ruling power of our country. …In almost every act of our daily lives, whether in the sphere of politics or business, in our social conduct or our ethical thinking, we are dominated by the relatively small number of persons…who understand the mental processes and social patterns of the masses. It is they who pull the wires which control the public mind.

Propaganda was portrayed as the only alternative to chaos.

The purpose of storytelling is the propagation of beliefs and emotions. Stories are appealing and hold persuasive potential because of their role in cultural transmission is the result of gene-culture co-evolution in tandem with the human capability for symbolic thought and spoken language. In human culture stories are involved in two functions:

1. Transmission of beliefs that are useful for the members of a group. Shared beliefs are the catalyst for improved collaboration.
2. Deception in order to protect or gain social status within a group or between groups. In the framework of contemporary competitive economic ideology deception is often referred to as marketing.

Storytelling thus is a key element of cultural evolution. Unfortunately cultural evolution fuelled by storytelling is a terribly slow form of learning for societies, even though storytelling is an impressively fast way for transmitting beliefs to other individuals. Not entirely surprisingly some studies find the prevalence of psychopathic traits in the upper echelons of the corporate world to be between 3% and 21%, much higher than the 1% prevalence in the general population.

Storytelling with the intent of deception enables individuals to reap short-term benefits for themselves to the longer-term detriment of society. The extent to which deceptive storytelling is tolerated is influenced by cultural norms, by the effectiveness of institutions and technologies entrusted with the enforcement of cultural norms, and the level of social inequality within a society. The work of the disciples of Edward Bernays ensured that deceptive storytelling has become a highly respected and valued skill.

However, simply focusing on minimising deception is no fix for all the weaknesses of storytelling. When a society with highly effective norm enforcement insists on rules and behavioural patterns that create environmental or social externalities, some of which may be invisible from within the cultural framework, deception can become a vital tool for those who suffer as a result of the externalities.

Furthermore, even in the absence of intentional deception, the maintenance, transmission, and uncritical adoption of beliefs via storytelling can easily become problematic if beliefs held in relation to the physical and living world are simply wrong. For example some people continue to hold scientifically untenable beliefs about the causes of specific diseases.

Attempts of global narrative development are fraught with difficulties, misunderstandings, and perceived and genuine social power dynamics. Our civilisation needs palliative care for its dying institutions and compassionate exit paths for the inmates, including guidance on locally relevant wisdom and systems of knowing.

All scientists, engineers, and technologists are familiar with a language that is more expressive and less ambiguous than spoken and written language. The language of concept graphs with highly domain and context-specific iconography regularly appears on white boards whenever two or more people from different disciplines engage in collaborative problem solving. Such languages can easily be formalised mathematically and can be used in conjunction with rigorous validation by example / experiments.