Globally, governments are still in the early stages of exploring a transition to new non-fossil fuel economies. Currently the global economy including agriculture, and horticulture are heavily dependent on fossil fuels, and there is a very high risk that political compromise will delay the end of outmoded practices. The integral role that fossil fuels play in the current global economy cannot be overstated, and any significant reduction in their role will result in a total remodelling of economic indicators. What is more, the close correlation of economic growth, and the implicit assumptions relating to positive GDP data, are seriously problematic when seeking to mitigate anthropogenic climate change and environmental degradation.

Source : Stuart Scott https://twitter.com/StuartGaia/status/1191234081394020353

Given the urgency to reduce greenhouse gas emissions to limit self-reinforcing climate feedback loops, even a 2 or 3 year delay before embarking on a path of drastic emissions reductions may lead the climate into a territory where any attempts to limit the average temperature rise to 2°C, or less, become futile.

Source: Stuart Scott https://twitter.com/StuartGaia/status/1191234650116517890

In order to mitigate the risk that humanity will not move fast enough to avoid social and environmental crises, we must prepare ourselves by concentrating on our ability to adapt, which in turn is dependent on our ability to explore a broad range of potential climate change scenarios and a broad range of possible mitigation pathways.

From a scientific perspective, based on the data available and the observable trends, actions to de-carbonise the economy which are framed with a 2050 deadline are inadequate. Firstly, the time frame is not aggressive enough to prevent potentially catastrophic levels of warming, and secondly, given the complexity of the climate there is also an urgent need for actions based on the precautionary principle.

Scientific uncertainty is not a justification for government to take a light regulatory approach when voters and their entire ecosystem face such existential moral hazard. In the same way that no one would allow their children to board an airplane if the risk of a deadly crash would be 10% (or even 0.1%), we should not have blind confidence in our collective ability to de-carbonise the global economy in time to prevent severe climate changes.

Adaptation actions must consider scenarios of at least 4-6°C of warming by 2100 and the likely consequences of such levels of warming in terms of threats such as:

• sea level rise, ocean acidification, and the salination of freshwater aquifers,
• impact on agriculture and food production,
• the spread of diseases, and the human and animal health risk of temperature increases,
• increases in extreme / catastrophic weather events,
• limits to the ability of local communities to cope with these consequences.

Preparing for adaptation to severe climate change must seriously consider the risk of social collapse at local, regional, national, and even transnational levels. In a global economy, when a major climate-induced social collapse occurs, we can not assume smooth continued operation of local or global economic and financial systems. Furthermore any de-carbonisation initiatives that depend on concepts such as financialised emission trading schemes may turn out to be ineffective.

These risks underscore the need for a climate change modelling tool chain that assists domain experts from various disciplines, as well as policy designers, to systematically and with relative ease explore, and communicate a broad range of options to reduce the risk and to contain the impact.

At the moment, the way we respond and adapt to climate change impacts is not well coordinated or communicated. Many of the risks, impacts and actions to adapt are dealt with across a number of different legislative and regulatory regimes.

There are gaps in our information. We have some knowledge about the physical impact of sea-level rise on our coastlines and communities but we currently don’t know much about the impact that rising seas and temperatures will have on economic and ecological systems. We also do not know what the impact of ongoing extreme weather events would be on production in the primary sector. Together these impacts could seriously disrupt current geographical, geological and meteorological advantages enjoyed by certain economic sectors.

We do not fully understand the ecological interdependencies related to the acidification of the oceans and the potential collapse of the complex food chain dependent on phytoplankton, and the oxygenation of the seas and atmosphere. We do not know if we are approaching a tipping point in ocean temperatures brought about CO2 absorption and rising acidification. We do not fully understand the water cycle and how the eutrophication of oceans and the salination of waterways interact with freshwater aquifers, impacting water resources and land-based food capacity.

There is more work to do to understand the possible impacts on our health, biodiversity and culture beyond the traditional timescales projected by economists, statisticians and politicians. A new transdisciplinary approach to climate change mitigation is needed to take precautions against the worst impacts that could affect all aspects of human societies, both locally and globally.

Exploring climate change mitigation and adaptation

Economic assumptions are never neutral and this is especially true of GDP and growth expectations that can hide equity costs within pricing markets on 10, 50, and 100 year timescales. The assumptions made in any economic models must also be explicit about equity issues and the level of commitment to achieve specific equity targets.

An evidence-based approach must be based on known patterns of physical resource flows and resource demands, and on explicit assumptions about changes to these patterns due to the need for climate change mitigation, and will, therefore, promote well informed political debate.

Climate change mitigation and adaptation is a complex transdisciplinary challenge. Any potentially useful modelling tool chain must be able to take into account the following constraints and limitations:

1. The reality of human cognitive limits, including the limits of quantitative methods, the limits of qualitative methods, and the limits of language.
2. The influence of ideologies and cultural norms on human behaviour, in combination with cultural inertia.
3. Changes of government and potentially significant changes in climate change related policies every few years.
4. The growing likelihood of extreme weather events of new levels of severity and the effects on agricultural production, economic infrastructure, and human lives.
5. The potential failure to limit local and global temperature increase to 1.5ºC or 2ºC even within the next 20 years.
6. The potential breakdown of established economic ideology due to local and global climate disasters within the next 20 years.
7. The need to rapidly reduce the ecological and energy footprint of human civilisation, and the level of incompatibility of reduced resource consumption with the established economic ideology.
8. The human potential, creativity, and resilience that can be unlocked by trusted collaboration at human scale.
9. The potential need to replace established financial economic paradigm with a viable resource and waste based alternative on short notice, and the ability to iterate on economic paradigm in order to adapt to rapid climate change and to deal with acute ecological disasters.

A modelling and simulation tool chain that does not consider the above constraints and possibilities will be of very limited use for the exploration of climate change mitigation and adaptation pathways, and will not be able to assist policy designers and implementers.

The S23M team envisages a modelling framework and a tool chain design that assists modellers, policy designers, policy implementers, the public, and industry representatives from all economic sectors to incrementally learn from each other about the unfolding reality of climate change, the changing social and economic support needs of local communities, and the need to invest in new types of economic infrastructure that are of strategic importance for our collective ability to adapt to climate change.

Uncertainties around climate and social norms

Just as the world wars wreaked havoc on society and the environment, the climate crisis creates a similar disjuncture with the past. The future of human societies is going to be dominated by two broad trends that are already visible now.

1. Increasing numbers of climate related increasingly severe weather events (severe rainfalls and flooding, cyclones and coastal erosion, heat waves, droughts, etc.), and downstream effects on agricultural production and ecosystem functions. The inherent level of uncertainty around the rate at which global temperatures will continue to rise and the rates at which national economies will be able to rapidly reduce green house gas emissions leads to a corresponding level of uncertainty around the frequency and magnitude of future severe weather events.
2. Increasingly levels of climate change related anxiety in the population, which may rise to the surface following severe weather events or disasters, leading to rapid shifts in social norms (financial economic growth is no longer the main or only target of economic policy, etc.). Further changes in social norms are inevitable, but the timing is impossible to predict – leading to significant uncertainty about future climate change mitigation related goals and legislation.

This means that classical financial economic modelling techniques and metrics such as GDP are no longer useful for assessing the impact of climate change and for assessing the cost of climate change mitigation actions. Whilst we can’t predict the future, we do know that the future will not be a continuation of historic economic trends, and it may also not be influenceable in any adequate way via classical economic tools such as interest rates, tax rates (carbon tax, etc.) and market mechanisms (emissions trading schemes, etc.).

Instead, going forward, national and local governments are well advised to rely on the development of agent based models using the resources, events, and agents (REA) paradigm to combine:

1. available physical climate models,
2. available scientific data about local bioregions and microclimates,
3. available data on historic and current regional economic activities categorised by sectors and industries, measured in physical quantities of resources (kg) and goods (quantities of specific categories of goods),
4. with the tacit knowledge of subject matter experts and local practitioners in relevant disciplines.

REA models of resource flows and economic activity can be developed and validated incrementally by groups of subject matter experts, both at the macro level as well as at the regional (meso) level, and they can serve as a formal foundation for agent based simulations of economic activities in combination with a range of very different climate change and climate change mitigation scenarios.

This approach allows modellers to run simulations that take a precautionary approach in relation to the uncertainties around severe weather events and around shifts in social norms outlined above. The REA data resulting from the simulations can be translated from physical metrics into local monetary metrics based on the different assumptions about social norms and economic rules that underpin the various simulation runs.

The resulting portfolio of possible climate change mitigation scenarios, including formal representations of all the assumptions about future social norms and economic rules, provide policy designers with a tool box for educating politicians and the public about the available options and associated investments in specific climate change mitigation and adaptation activities.

A growing number of researchers and practitioners are working on resource based accounting methods, and some are already working on the development of regenerative economic ecosystems at a bioregional level that are specifically designed for resilience against climate change.

An economic ideology independent reasoning framework

Preparation for potentially severe climate change and economic disruption is only possible with the help of economic and ecological modelling and simulation tools that don’t make implicit (hard-coded) assumptions about the way economic systems work. In this context financial economic modelling techniques are at best inadequate if not useless.

Over a period of 30 years and longer significant shifts in economic ideology are inevitable in order to adapt effectively to changes in climate, to the effects of increasingly extreme weather events, and to related social challenges.

Governments need suitable multi-dimensional economic and ecological modelling tools for reasoning about human collaboration and resource flows at various levels of scale that can be configured on demand, to reflect emergent economic and ecological practices that may differ radically from current “best practice”.

The MODA + MODE human lens provides thirteen categories that are invariant across cultures, space, and time – it provides an economic ideology independent reasoning framework for transdisciplinary collaboration. The human lens allows us to make sense of the world and the natural environment from a human perspective, to evolve our value systems, and to structure and adapt human endeavours accordingly.

The human lens is a meta language that can be used to design multi-paradigm and multi-dimensional modelling and simulation tools for resource flows between economic agents as well as resource flows between ecological systems and economic systems.
The human lens is comprised of:

1. The system lens, to support the formalisation and visual representation of knowledge and resource flows in complex socio-technological systems based the three categories of resources, events, and agents (the REA paradigm, an accounting model developed by E.W. McCarthy in 1982 for representing activities in economic ecosystems). The system lens can be applied at all levels of organisational scale, resulting in fractal representations that reflect the available level of tacit knowledge about the modelled systems.
2. The semantic lens, to support the formalisation and visual representation of values and economic motivations of the agents identified in the systems lens. The semantic lens provides a configuration framework for articulating ethical, cultural, and economic value systems as well as a reasoning framework for evaluating socio-technological system design scenarios and research objectives with the help of the five categories of social, designed, symbolic, organic, and critical.
3. The logistic lens, to support the formalisation and visual representation of value creating activities and heuristics within socio-technological systems. The logistic lens provides five categories for describing value creating activities: grow (referring to the production of food and energy), make (referring to the design, engineering, and construction of systems), sustain (referring to the maintenance of production and system quality attributes), move (referring to the transportation of resources and flows of information and knowledge), and play (referring to creative experimentation and other social activities). The logistic lens can be used to model and understand feedback loops across levels of scale (from individuals, to teams, organisations, and economic ecosystems) and between agents (companies, regulatory bodies, local communities, research institutions, educational institutions, citizens, and governance institutions). The categories of the logistic lens assist in the identification of suitable quantitative metrics for evaluating performance against the value system articulated via a configuration of the semantic lens.

All 13 human lens concepts reflect foundational aspects of human cognition and the human capacity for symbolic thought within an ecological context, and are found in all cultures under various labels.

The human lens concepts are recognisable in all historic human cultures, and they will continue to be relevant in another 1,000 years – this is what is meant by “independent of economic ideology”. This is important because language is always a contentious topic in a transdisciplinary context, since each discipline uses a different language. The human lens can be used to model all aspects of the relationships between economic agents and all aspects of collaboration within economic agents.

Furthermore the fractal characteristic of the human lens allows the representation of groups of collaborating economic agents and the representation of abstract relationships between such groups.

The grow category in the logistic lens can be used to instantiate specific subcategories in the land use sector for forestry, horticulture, dairy farming etc. Additionally the base categories of the logistic lens provide a framework for the transport (move, referring to the transportation of resources and flows of information and knowledge), electricity (grow, referring to the production of food and energy), and industry sectors (make, referring to the design, engineering, and construction of systems). The base categories in the logistic lens are designed to encourage zero waste system designs, the sustain category (referring to the maintenance of production and system quality attributes) can be used to instantiate models that focus on maintenance, repair, and decomposition for reuse of economic resources and that explicitly indicate, and as needed, quantify, residual waste streams. Finally the play category (referring to creative experimentation and other social activities) can be used to instantiate models that focus on important cultural practices, on the education sector and on research and innovation).

A distinguishing feature of the MODA + MODE meta paradigm is that it allows for consistent formalisation of discipline specific paradigms and local domain specific languages, such that domain experts are able to continue to use their preferred paradigms and terminologies.

Agent based economic and ecological models can be created and populated with available data and assumptions (scenarios) about economic sectors and ecological practices at various levels of scale in time and space, and these models can then be used to:

1. Visualise qualitative and quantitative economic dependencies and resource flows, including but not limited to links from sectoral models to thoroughly understand the interactions between the energy and land use sectors.
2. Run agent based simulations of activities in the economic and ecological spheres to explore different scenarios and their implications.
3. Generate corresponding multi-dimensional economic and ecological accounting tools that can be used to coordinate human economic activities.

All the categories and semantic links between categories and instances in the example model above are easily made available for processing by software tools. The example shows concrete resources (orange), events and activities (blue), as well as agents (green) and their motivations (red).

The semantic lens allows us to create explicit models of different worldviews and paradigms, so that all relevant value systems and cultural differences are not only acknowledged, but become an integral part of the language used to describe economic activities and their purpose.

Visual semantic models can be used to trace motivations back over several levels to specific cultural or individual values. In this way assumptions and worldviews are made explicit, and cultural context can be integrated into economic and logistical models to any desired level of detail. In particular local knowledge and values can be reflected in the configuration of economic models, alongside scientific knowledge about the natural world and the climate, facilitating the co-design of mitigation and adaptation activities in collaboration with local populations.

The human lens in combination with an inclusive consultative and transdisciplinary approach provides results that are traceable to underlying datasets and economic assumptions and that can assist policy designers in answering important questions under a range of different climate change scenarios:

1. What emissions reductions are technically and economically feasible when factoring in the interactions between sectors and economy-wide constraints?
2. What are the economic consequences of different levels of emissions reductions, different types of policy interventions, and different scenarios of technological and economic change?
3. What distributional impact could emissions budgets or emissions policies have on different sectors, regions, generations and socio-economic groups?
4. What impact will domestic emissions policies have on the ability to meet global emission reduction targets?
   What impact will overseas markets and policies have on local emissions, production and trade?

In an increasingly unpredictable world that can easily be disrupted by severe climate related events, a modelling and simulation tool as described above may be essential for preventing or limiting social collapse, allowing local populations to rapidly explore the viability of new sequences of adaptive actions, before jointly agreeing on and committing to specific (and potentially radical) changes in economic and ecological practices.

Modelling and simulation tool chain design

A suitable modelling tool that supports the human lens and representations of both quantitative and qualitative / semantic models can be implemented with the help of category theory (which is the abstract “systems integration language of mathematics”) and with denotational semantics (to map formal models to concrete computational platforms and data storage technologies) .

A basic implementation of the human lens for qualitative modelling is achievable with a Unified Modeling Language (UML) modelling tool and via the configuration of a UML Profile that includes suitable UML stereotype definitions for the thirteen human lens concepts.

An even more basic implementation is afforded by markers and a whiteboard or by pencil and paper, but then of course the models can’t be used to drive automation and agent based simulation tools.

The full potential of the human lens can be harnessed with a tool like S23M’s Open Source Cell Platform that provides an unlimited multi-level instantiation capability and that enforces strict semantics for agent based modelling.

The Cell Platform provides a clean formalisation based on the axioms of category theory that is recursively bootstrapped from the structure of an ordered pair, without any spurious complexity induced by the underlying implementation technology (the Java Virtual Machine – JVM). Additionally the Cell Platform:

• Uses denotational semantics (a unique machine readable semantic identity for each concept) to completely separate the concern of naming from the concern of semantic modelling, allowing each agent to introduce preferred labels and symbols.
• Enables communication and collaboration between agents based on artefacts (information resources), and events which equates to native support for the REA paradigm.
• Provides an API in the language of category theory that exposes the recursive construction of models, and that hence allows extensions, restrictions, and other variations of all concepts.
• Allows agents to make selected models discoverable, to make selected models visible to other agents, and to declare semantic equivalences between concepts in different models that are then recognisable by the reasoning engine within the Cell Platform.
• Provides support for 4-state information quality logic (true, false, unknown, not applicable) to allow agents to easily process incomplete data and any structures they may find in the models from other agents – without resulting in ambiguous semantics.
  Supports logic and reasoning entirely within the abstract language of category theory, since semantic equivalences are defined between semantic identities rather than between human assigned labels.

The S23M team envisages a transdisciplinary modelling and simulation framework for climate change mitigation and adaptation scenarios that allows domain experts from various disciplines to contribute models of sectors of the economy and aspects of ecosystems within their preferred paradigm and in their preferred terminology into a modelling tool chain that includes explicit support for:

1. Managing and enforcing the limits of applicability of specific models.
2. Recording all assumptions that are associated with a model or specific scenario in a form that is accessible to software tools.
3. Reviewing and flagging inconsistencies between the assumptions associated with different models or aspects of the domain of interest.
4. Formal version and variant management for all models, data sets, and sets of assumptions that are associated with specific climate change mitigation pathways.
5. Formal traceability between sets of assumptions, and related models and results of agent based simulations.
6. The human lens meta language, to enable
   • Specification of suitable qualitative and quantitative goals in suitable metrics, including metrics for the quantification of resource flows and green house gas emissions in physical units, and chemical types/properties.
   • Modelling cultural norms and expected or potential shifts in cultural norms.
   • Modelling the economic ideology and expected or potential shifts in economic ideology.
   • Modelling cross-sector dependencies and resource flows at different levels of scale, including desirable shifts in such dependencies.
   • Modelling of concrete economic agents that are of strategic economic importance, including the dependencies between these agents – to provide a foundation for performing dynamic agent based simulations under a range of different assumptions.
   • Semantic integration between different aspect and sector models, including the specification of any required transformations of input and output data structures.
7. As needed, translating the results of agent based simulations back into traditional financial economic metrics, to assist experimental and iterative development of suitable policies and regulatory frameworks for achieving desired national and regional level outcomes.

The purpose of such a modelling and simulation tool chain is to allow rapid exploration and iterative refinement of different mitigation and adaptation scenarios. Policy makers and the wider population need to see “first hand” (as far as that is possible) that busyness as usual and related measures to “decarbonise” the economy via traditional economic tools within the framework of financial economics are inadequate for dealing with the challenge presented by the climate crisis.

Organisations are best thought of as cultural organisms. Groups of organisations with compatible operating models can be thought of as a cultural species. The human genus is the genus that includes all cultural species. Since the emergence of humans around two million years ago, evolution has produced many different cultural species within the human genus.

It is becoming clear (Dunbar) that only human scale organisations are understandable for individual humans and have the potential to provide psychologically safe and healthy environments for humans. A careful analysis of human history demonstrates that super-human scale organisations are inherently unsafe for individual humans, and that completely atomised societies are inconceivable, as they are apparently incompatible with human social needs.

Viewed from within the context of human evolution, the emergence of “civilised” (super-human scale) societies and the construction of empires is a social cancer that feeds on cultural species and has resulted in the destruction of cultural species and in a severe reduction in the number of healthy cultural species. Based on this understanding we can conclude that the human genus has been declining in adaptive fitness since the dawn of “civilisation” around 10,000 years ago.

The NeurodiVenture operating model is the social DNA of an emergent cultural species that has developed an immune system that enables it to survive and even thrive in three complementary contexts:

1. within super-human scale societies afflicted by terminal cancer
2. within social environments that contain a growing number of NeurodiVentures
3. within social environments that contain other human scale cultural species within the human genus

The minimalistic aspect of the NeurodiVenture operating model supports a huge diversity between cultural organisms and overall equips the NeurodiVenture cultural species with a level of resilience that differs markedly from the brittleness and pathological cultural inertia that characterises super-human scale societies.

The main difference between modern emergent human scale cultural species and prehistoric human scale cultural species lies in the language systems and communication technologies that are being used to coordinate activities and to record and transmit knowledge within cultural organisms, between cultural organisms, and between cultural species.

The main commonality between prehistoric societies and modern human scale cultural species is the critical importance of knowledge for survival, and a cultural appreciation for the value of knowledge and the value of trust based collaboration at eye level both within cultural organisms and between cultural organisms.

The main difference between all human scale cultural species and super-human scale “civilised” societies lies in the devaluation of knowledge and reliance on anonymous transactions and abstract monetary metrics, and in a corresponding devaluation of trust based collaboration at eye level.

The end of capital

Peter Thiel and Eric Weinstein, the manager of Thiel Capital, are two people who are not afraid to share their thoughts. It is interesting to see how they can spend 3 hours framing their quite astute observations on human society entirely within the box of capitalism and “meritocracy”, and how this frame prevents them from reaching deeper insights about human limitations and human creativity.

Human scale does not exist in Peter Thiel’s world. Instead Peter and Eric attempt to explain everything in terms of individuals, individual merit, organisations, growth, and progress in science and technology (without any attempt to delineate the boundary between science and technology). In the dialogue referenced above they both go to great lengths to complain about the extent to which virtually all organisations have become sociopathic, but they don’t realise how insisting on an individual talent or merit scale and a universal metric (capital) is the perfect breeding ground for the corruption that they complain about. It is as if they complain about all the hierarchical structures that differ from an envisaged ideal and universal “meritocratic” hierarchy that is defined by criteria stipulated by Peter Thiel & Co.

Whilst long, the above dialogue is highly recommended for all those who are still convinced that capital must be part of the furniture of all technologically advanced societies.

The dialogue between Peter Thiel and Eric Weinstein illustrates that some of the most fundamentalist capitalists question whether there has been any substantial technological progress at all over the last 40 years.

I concur with the diagnosis of stagnation in many areas of knowledge, but from my perspective economic growth and capital are counter-productive and dangerously misleading metrics going forward. Capital is a legacy technology that will need to be phased out if humans want to have any chance at avoiding the self-destructive pattern of civilisation building and collapse that has characterised the last 10,000 years.

We need to be clear about the remaining life expectancy of capital as a relevant metric at super-human scale. In the short term human scale employee owned companies and cooperatives can opportunistically work within a capital-driven world, but over the next 30 to 100 years the role of capital will likely be reduced to zero – it’s going to be an obsolete legacy technology just like the telegraph is a legacy technology today.

The interest in human scale employee owned companies is growing globally, as such companies are capable of thriving in a capitalist environment due to their collaborative advantage, but they are also ideally positioned to thrive in other emergent environments that are less toxic for the planet.

Domain-specific metrics that measure physical properties are going to become much more important than abstract metrics at super-human scale. Abstract metrics are only safe (low risk of corruption) for local resource distribution at human scale.

From economics to the web of life

If we want to avoid repeating the mistakes of human “civilisations”, the rules for coordinating at super-human scale will have to allow for and encourage a rich diversity of human scale organisations.

In a human scale social world, apart from the self-imposed constraint of human scale, there is no universally dominant organisational paradigm. In a super-human scale social world that is increasingly toxic for individual mental and physical health, a diversity of human scale paradigms will eventually crowd out the super-human [global/national/mega-city] scale paradigm that dominates today.

The resulting web of interdependencies can simply be thought of as the web of life rather than “civilisation 2.0”. We must not to again make the anthropocentric mistake of putting humans at the centre of the universe.

At human scale cultural evolution operates as follows:

1. On the relationships between cultural organisms and on the links between cultural species.
   Relationships can strengthen or weaken, new relationships can be established, and established relationships can be be discontinued or put on hold. At any point in time the relationship between two cultural organisms can be described in terms of the binary trust based relationships between specific individuals. The duration of relationships can last from months through to many decades and possibly longer.
2. By individuals who may chose to leave or join a cultural organism, travelling along the link to a related cultural organism of the same cultural species.
   From an individual’s perspective such a change in organisational membership is minor. The individual retains their individual competency network, and the change can be described as the emergence of new regular collaboration patterns within the individual’s competency network and the weakening of earlier regular collaboration patterns – it is very much comparable to a change in team membership within a cultural organism. From the perspective of the cultural organism involved the change reflects a desirable change or optimisation in the interaction patterns across the organisational boundary that is well received by most of the individuals involved – a new team is welcoming a new member and another team in the related cultural organism will reconfigure accordingly. The duration of organisational membership may last from months through to many decades or an entire lifetime.
3. By individuals who may chose to leave or join a cultural organism, travelling along the link to a related cultural organism of a different cultural species.
   Again, from an individual’s perspective such a change in organisational membership is relatively minor. The individual retains their individual competency network, and the change can be described as the emergence of new regular collaboration patterns within the individual’s competency network and the weakening of earlier regular collaboration patterns – but in this case the individual will need to integrate into a new culture. Often such a change will be motivated by the neurological disposition and specific talents and interests of the individual, who may have discovered via personal interactions across the organisational boundary that she or he would be more comfortable in the target culture. From the perspective of the cultural organisms involved the change reflects an opportunity for cultural cross pollination across the organisational boundary that may improve the collaboration patterns across the cultural species boundary. The average number of shifts between cultural species will be zero across a typical human life, and the number of shifts will likely be one or more for many neurodivergent individuals, who will feel compelled to search for a cultural environment that is well suited for their particular needs and cognitive lens.
4. By individuals who may chose to leave or join an unrelated cultural organism of the same cultural species.
   This scenario represents a mixture of scenarios 1 and 2 above. The individual will have had to establish a relationship to someone in a different cultural organism, and hence the change represents an emergent relationship between two cultural organisms. The duration of the new relationship may last from months through to many decades or possibly longer.
5. By individuals who may chose to leave or join an unrelated cultural organism of a different cultural species.
   This scenario represents a mixture of scenarios 1 and 3 above. The individual will have had to establish a relationship to someone in a different cultural organism of a different cultural species, and hence the change represents an emergent relationship between two cultural organisms. This scenario may be fairly rare, as it involves establishing a cross-species relationship between cultural organisms that had no prior contact. The resulting relationship may start off very much as an experiment or exploration with outcomes that are difficult to predict. It may result in the individual having found a more accommodating target culture in terms of their neurological disposition, and the link between the two cultural organism may only be short lived.

At human scale individuals enjoy a significant level of agency, with the ability to remain in a given cultural organism as long as they desire, and to move to a different cultural organism when this is aligned with individual neurological dispositions, talents and interests. All atomic changes in relationships and memberships leave an individual’s existing competency network intact and at all times the individual is part of a cultural organism that provides a livelihood for the individual.

Similarly cultural organisms enjoy a significant level of agency at human scale, as all individuals in the organism may create new relationships across the organisational boundary as needed, for example coordinated via a simple advice process and as needed via deliberation in Open Space. Cultural organisms that don’t operate an egalitarian culture will quickly find themselves at a disadvantage, as they are held back by cultural inertia. At some point their members may decide to join more egalitarian cultural organisms.

Agency at super-human scale is an emergent phenomenon that can not be attributed to any specific individual. Living within “civilisation” we are surrounded by super-human scale structures and it is difficult for most people to imagine collaboration at human scale without being embedded in some bigger hierarchical system.

Each human scale cultural organism represents an aggregation of agency that manifests itself in individual relationships and interactions across the organisational boundary. In a non-hierarchical cultural organism there is no single individual that “leads”, instead external representation and decision making of the cultural organism is distributed across all the individual relationships between the cultural organism and other cultural organisms.

Large sets of collaborating cultural organisms (some of which may be given labels for the purpose of communication and reasoning about them) without any hierarchical command and control are unattractive for sociopathic empire builders. The lack of hierarchical structure is a key element of the immune system against organisational cancer.

Visualising human collaboration

Human spoken and written languages are useful, but we need better [non-linear] languages systems for reasoning about collaboration beyond human scale.

The human lens is a meta language that can be used to construct better language systems.

The human lens can be used to model all aspects of the relationships between cultural organisms and all aspects of the relationships within cultural organisms. Furthermore the fractal characteristic of the human lens also allows the representation of groups of collaborating cultural organisms and the representation of abstract relationships between such groups.

When such structural and relational abstractions are agreed between cultural organisms, the result is a formal abstract framework that defines agreed collaboration patterns. Abstract collaboration frameworks can be worked out collaboratively in Open Space, and as needed choices between alternative approaches to specific details can be made via a democratic process involving all members from all cultural organisms that are involved. The focus of democratic governance at super-human scale completely shifts away from the selection of “leaders” to the selection of suitable collaboration frameworks for ecosystems of collaborating cultural organisms.

Below is a high level overview of  valuable resource flows represented with the help of the logistic lens within the human lens.

The represented abstract categories can be refined as needed in corresponding models of concrete instances of resources and agents.

In a simplistic capitalistic world such complex multi-dimensional collaborations patterns tend to be linearised into legal agreements that are dominated by a simplistic one-dimensional metric – capital.

We can use the same visual notation as above to create models of dysfunctional feedback loops (or negative “externalities” in the language of economics).

In a networked digital world agreed collaboration patterns can be formalised with the human lens, making use of physical metrics to quantify flows of resources and energy, without any need to resort to abstract metrics. The technologies for resource based accounting exist today.

Below is an example of a high level commonality and variability analysis of the agriculture sector represented using the categories of resources, events, and agents (the REA paradigm).

The visualised categories are the commonalities that characterise the sector. Corresponding representations of concrete instances of these categories with the help of the logistic lens and connections between these instances lead to models of value producing processes and activities that can be refined to any desirable level of detail.

Where we stand today

The only thing that stands in the way of phasing out the legacy technology of capital is cultural inertia and the ongoing indoctrination in outdated economic ideology delivered by our education systems.

In the coming decades metrics that measure physical properties (energy use, resource use, waste metrics) are going to become much more important than abstract monetary metrics. We will increasingly discover that abstract metrics (“currencies”) are only safe to use for resource distribution at a local human scale, and that at super-human scale the risk of corruption of abstract metrics simply becomes too large to be acceptable.

To comprehend where we currently stand it is useful to conduct a little thought experiment. What would happen if the global financial system collapses or if all the technology infrastructure underpinning the financial system collapses?

If everybody just continued with all their daily activities as usual as far as possible, irrespective of their ability to be paid or to pay, the following would happen:

• In the technologically “less advanced” parts of the world the impact would be minimal. People would continue to go about their lives, collaborate along the lines of trusted relationships, and as required come up with alternative no/low tech accounting systems at human scale.
• In the technologically “advanced” parts of the world the impact would be much larger. Many technological systems and complex automated supply chains that assume working connections to banking systems would be disrupted. Above and beyond the inability to purchase physical goods online, people would quickly run out of credit tokens on their phones and on public transport, preventing them from using such services. In general, all technologies that rely on embedded links to banking systems would become disabled, whilst all technologies without such links remain unaffected. People could continue to visit retail shops and pick up goods or deliver supplies – and just as in the technologically less advanced parts of the world people will likely quickly come up with low tech accounting systems at human scale.

The overall result of using alternative low tech local accounting systems would be a much reduced ability to rapidly shift abstract credit tokens around the world.

The main people who would get concerned would be all those who used to be able “to make a living” from speculation, from rent seeking, and from shifting abstract tokens around the world. Those same people will likely not have access to any of the trusted relationships at human scale that are essential for surviving in a non-financialised world. Similarly many of the people who used to have “second and third level” bullshit jobs (all those people in jobs involved in operating the technology that supports the financial system) may discover that they lack useful trusted relationships at human scale.

In a world where many global supply chains for physical goods are disrupted, and where technological failures refocus collaboration on local trusted relationships at human scale, resources and goods would flow at slower rates, and the flows that continue to take place would largely be local, focused on the absolute necessities of life. In some geographies food shortages would quickly become extreme, and the overall reduction in long distance transportation would significantly reduce energy consumption.

Interestingly renewable energy sources and connected electricity distribution networks and connected customers would only be disrupted in locations where they are deeply entangled with banking systems.

The outlined scenarios could very quickly result in civil unrest, especially in the “advanced” parts of the world that are further removed from trust based collaboration at human scale, but this observation can in no way be taken as a “proof” that a world without capital is inconceivable:

1. Dismissing a world without capital because we personally have never experienced world without global money is simply a case of ignorance and lack of imagination fuelled by fear of the unknown.
2. In prehistoric times humans survived and increasingly thrived without money for many hundred thousand years. People’s life expectancy may have been shorter than today, but prehistoric humans where highly capable in transmitting complex knowledge over many generations, allowing them to adapt to many different climate zones and to a huge range of different local ecological contexts.
3. A small number of technologically “backward” societies still share more characteristics with prehistoric cultures than with the WEIRD (Western Educated Industrialised Rich Democratic) cultures that dominate today.
4. With relatively minor adaptations many of the technologies we use today could be disconnected from the global financial system and could resume operations in a post-capital world. The magnitude of the changes required are in many ways comparable to the magnitude of the changes to remove Y2K limitations from our software systems – not trivial but far from impossible, and perfectly achievable within a few years. As part of this transformation our technologies could be wired up to resource based accounting technologies that track flows of resources and goods purely in terms of physical metrics. The result would be a global logistics infrastructure capable of tracking resource flows without the translating (liquefying) everything into an abstract 1-dimensional metric of capital that instantaneously disappears through conceptual wormholes to facilitate universal fungibility for everything under the sun – everything and everyone is for sale.
5. Some of the effects outlined above such as a reduction in global resource flows, a refocus on local flows of resources, and a reduction in energy consumption would be highly desirable in terms of reducing greenhouse gas emissions and a rapid transition to a zero carbon economy. A transition towards resource based accounting as outlined above would allow us to re-enable global resource flows under a completely new regime of governance: we would be able to plan and budget in terms of resource needs and we would be able to very easily monitor agreed limits of energy and resource consumption in raw physical units without any distortions.

Considering all of the above, we can conclude that we are already much closer to a world without capital than capitalists would like us to believe. In many ways such a new world is much more desirable for most of us than the delusional world of infinite “growth” that we are still being sold.

Standardisation is a double-edged sword. Compliance with standards is best restricted to those standards that really make a difference in a specific context.

Even innocent standardisation attempts such as enforcing a shared terminology across an organisation can be counter-productive, as it can lead to the illusion of shared understanding, whereas in practice each organisational silo associates different meanings with the terminology.

There is no simplistic rule of thumb, but the following picture can help to gain a sense of perspective and to avoid the dreaded death zone of standardisation.

Death by Standardisation