ELSI: Cross-Domain Effects Part 2

Connectivity Connectivity is the level at which the nodes or agents in a system are connected to one another. It’s a very basic network property. The characteristics and consequences of Connectivity are usually easy to figure out; counting your friends is easy, and if you have more friends, you have higher chances of people coming to your birthday party. If there’s more roads between cities, travel times will be shorter overall, and possibly more efficient. Of course, each connection comes at a cost, and depending on the cost, the Connectivity property of a system may reduce or increase Efficiency, and thus Resilience and finally Sustainability. High or Low? In most cases you want a system to have a high level of Connectivity. If connection cost (and management) is not a limiting factor, it’s usually best to have as many connections as possible. The quality of these connections, of course, also matters, which is covered in the other indicators. Diversity Diversity indicates the different types and connections the network has. Diversity is often important to have a system withstand changes in environment, have a level of self-resolution and increase inventiveness. Diversity is leveraged on both the types of nodes, and the types of relations between each node. High or Low? Diversity is often a desired property in a system. Especially larger systems suffer when the Diversity is too low. Diversity is often a property that wants to be balanced: not too high, not too low, but in a comfortable middle, possibly err on the side of more than less. Imagine a warehouse filled with a single product: if the demand for that one product goes down, the company that owns it suffers quickly. If the warehouse had a lot of different products, its risks would have been spread, but its management would be more complex. Similarly with people in an organization: more diverse people increase the ability of an organization to respond to challenges, and have a broader platform of experience and perspective. Too much Diversity may lead to fragmentation and poor cohesion of a system, as well as low Efficiency. Complexity Complexity is a network parameter combining the amount of nodes, the amount of connections and the network’s Diversity. In that sense, it is a compound indicator, but its qualities are so fundamental that we’ve included in as a base indicator for networks. Network Complexity governs a wide range of effects that are important in virtually all cases. Complexity is also an emergent property of systems in general, one which is paired with the law of diminishing marginal returns. This important network effect, described by Joseph Tainter in his book The Collapse of Complex Societies (1988), has proven to be a major reason for human societies to collapse. This leads us to adopt a general strategy of ‘decomplexification’. Since other network properties such as Redundancy and Connectivity tend to drive up Complexity, this parameter can explicitly serve as a check and balance element, much like the Efficiency parameter. High or Low? For a given outcome, it’s desirable for the network complexity to be low. A high Complexity usually makes a system fragile, especially if the complexity rises above the beneficial limits of the size of the system (diminishing marginal returns). This means that there’s usually an optimum of system Complexity that lies somewhere in between its minimum and maximum properties. Flexibility Flexibility determines the ability of the network to form new connections, and to reroute or ‘bend’ existing connections. It’s a measure of the ‘elasticity’ of the network, with an important time component: how quickly can connections be (re)established, and at what cost? How far outside of the required parameters can a system operate before it fails? Flexibility is dependent on time. A system may be able to form new connections easily, but how long does it take to do this? High or Low? Generally speaking, Flexibility is a good thing. It’s one of the important supporters of system resiliency and allows faster changes. A flexible system can more easily move itself into an optimal position. Awareness is necessary for a system to change when it is needed though, therefore Flexibility is often dependent on other system qualities such as Awareness and Transparency. Flexibility is also often related to Redundancy and Diversity. For example, if there’s a low Diversity in disciplines in a company, the company can’t be very flexible on its delivery performance on a certain task, because it doesn’t have the know-how and expertise. Similarly, a city can’t house a new generation of people with different living requirements if its housing stock is limited in Diversity, and cannot be converted quickly, where Flexibility relates to the convertability of the stock. Redundancy Redundancy is a straightforward indicator that measures the level of repetition of nodes and relationships in the network. In societal systems, there’s always a redundancy present. In technical systems, Redundancy is often built in to increase reliability. High or Low? Low Redundancy leads to a fragile system, which can easily fail due to the breaking of a single critical component or connection. High Redundancy has a positive influence on Resilience, but also reduces the Efficiency of a system, increases Complexity, and may affect other parameters as well. Efficiency is usually not a goal in itself, but rather a means to an end. Therefore, if a system is sustainable it does not matter what its Efficiency is, and it’s preferred to have higher Resiliency than Efficiency. It follows that a certain degree of Redundancy is usually a good thing. Redundancy in itself is rarely a goal, but its effect on the Resilience system indicator is large. For example, combined with a low score on the Centrality indicator, Redundancy is a major driving force behind decentralized power generation. Combined with Diversity Redundancy supports Flexibility. Centrality Centrality measures the extent with which a system is reliant on particular critical node(s) within the network. In other words, it gauges the structure of a network and gauges what form it has, from a star-shaped form with high Centrality, or a flat hierarchy organic shape with a low Centrality. It is a highly influential aspect that can change the behavior of a system radically. In any network, Centrality plays a role on some level. Much has been written on Centralized vs. Decentralized systems, and many mathematical models exist to evaluate networks on their Centrality, and their consequences. High or Low? Centrality is interesting, because its effects shift quite radically depending on the size of the network. For small networks, a highly Centralized system is often efficient, fast, and reasonably reliable. That is, if the central nodes are Redundant and Flexible enough. But, when scaling up the system Centralized networks become brittle, have low resiliency, and are not efficient anymore: they lose most of their beneficial properties. This already measurably happens on the scale of small to medium sized organizations. Small organizations, from one person up to 50 or so, stand to benefit from some from of Centralization and hierarchy in the node structure. Beyond this, it quickly becomes rewarding to adopt a less hierarchical, and less centralized organizational structure. Awareness Awareness measures the reach of information between nodes within the system. A node may be in total oblivion (a complete disconnect), or it may be aware of only the information its own surrounding nodes have, its own sub-networks, or it may have a complete awareness of the entire system, and so on. Note that Awareness may be high even while Validity is very low, as in the case of propaganda. Awareness often relates to Transparency whilst Validity refers to truth. High or Low? A system with a high level of Awareness is able to respond faster to events in the system. Entities in the system can respond sooner when they are more aware. The third braking light in cars is an easy example. This light can be seen through the windshields of other cars, and alerts drivers further down the road sooner. Higher Awareness in social and cultural networks can foster greater innovative capacity within the system. In another example, low Awareness negatively impacts the Resilience of a system, since those agents that do not know about the best ways to respond to critical events may make uninformed decisions and make the situation worse. An example is what happened at the Chernobyl nuclear disaster. Even the highest officers at the facility were not aware that the emergency stop procedure could make a situation worse, and cause a meltdown. This is what happened eventually. Transparency Transparency is a measure of the connection speed between nodes in a network. Speed may be affected by layers of transmission and/or opacity. For example, hierarchies require clearance from each subsequent level for information to filter down the chain, hence hampering speed. In the case of opacity, a bureaucrat may deliberately prevent civilians from gaining insight into governance. High or Low? Low Transparency within a system implies difficult information transmission between nodes. Systems with low Transparency therefore have a slower reaction time than a high Transparency system. High Transparency seems beneficial across the board. In technological systems, the network throughput speed is often a limiting factor for the performance of the entire system. In governance, social, and cultural domains, Transparency also directly impacts the network parameter harmony. Take for example a corrupt government that takes advantage of lack of transparency to cause division between groups of people. Using propaganda to create fear for immigrants, for example, has an adverse impact on Harmony. Validity Validity is the truthfulness of information transmitted in a network as reflected on the objective observations of all of the nodes in the system. Measuring Validity may provide a pivotal insight into a system or society’s health. Validity plays an important role in societal systems where Transparency and Awareness also interact to interchange information. In technical systems, validity will be analogous to the reliability of information transfer, or subsequent corruption of information. Another interesting use of Validity is in the form of ‘true costing’. This is the practice of determining a monetary value for all externalized factors, in order to make a more ‘truthfully’ weighted economic decision. Natural Capital and True Pricing are forms of this. An economic or financial decision is less valid if some factors have not been considered. High or Low? In most cases one would want the Validity of a system to be high. This means that the information that’s passed on from one agent to another is ‘true’ according to the evaluation of their peers, as well as uncorrupted from its originating source. A small amount of corruption of information may be healthy in any system, however, to keep the error-checking systems healthy, active, and alive. Resilience Parameter Variations There are other useful indicators to analyze Resilience. Most of these have something to do with a spatial or temporal mapping of the network, and could be captured in an accurate mapping of the above indicators in space and time. For instance, the indicator ‘Reach’ is used often in existing research on system dynamics. Reach can be effectively covered in SiD’s system by mapping a combination of Awareness and Connectivity parameters in space. An indicator such as ‘Transmission speed’ can be captured by mapping the Transparency indicator in time. Otherwise, specific indicators can be used for specialized network analysis situations. Examples of other parameters we have used are: Coherence Accessibility Sensitivity/Responsiveness Entropy Rigidity/Sturdiness Usually, these aspects can be found in a combination of the CRAFTDCCV parameters, but it may be useful to add or replace parameters where the need arises. the autonomy network parameters sscne autonomy network: SSCNE in Detail The system indicator of Autonomy is naturally more associated with the physical, such as the availability of power and the recycling of resources. As with all the system and network parameters, these influence each other across the board. E.g. a more decentralized system affects Resilience greatly, but may also affect Autonomy. The following parameters are useful to evaluate Autonomy, in addition to those for Resilience. Self-sufficiency The measure to which the system can fulfill its own basic needs and beyond Self-governance The measure to which the constituents of a system can govern themselves Circularity The measure to which resources in the system are, and can be re-used, in a closed loop Network support The system’s ability to support neighboring systems in case of calamity Efficiency The amount of agents and assets contributing positively to the system in relation to their cost. Self-Sufficiency The most important indicator of autonomy is self-sufficiency. Self-sufficiency relates to the self-production of elements that are vital to a system’s operation. For example, when talking about a town, we refer to elements such as drinking water, the required power for essential operations, food, and so on. A system is self-sufficient if it produces these in large enough quantities that when supply from the outside world is cut off, it can continue to operate. There may be a term limit to this. It’s possible to measure self-sufficiency in time. For example, if a town can survive with its resources for one year before its grain or water storage is depleted, its self sufficiency is that one year. While that may be a great achievement in our current society, one year can be considered reasonably low in light of things we might be facing, in terms of drought, crop failure, storm flooding, etc. As noted before, Autonomy and Resilience can bite each other. Too high of a level of Autonomy may impact connectivity, flexibility, or other network parameters and thus undermine Resilience. For human communities, in order for that not to be the case, self-sufficiency should focus on the essential required resources. These are not just water, food, and power. These also include, for example, the capacity for managing waste, public order, basic health treatments, basic economic operations including work and value exchanges, communications, and essential public transport, as well as cultural expression and social connectivity. And, of course, the capacity to maintain and service these elements, and provide training for their continued operation. The other extreme, of things that are not part of it, are those that are not vital to operations or are of such complexity that their decentralized distribution would lead to large resource losses. For example, while having transport vehicles is of high value to a town, and a repair station for them may be considered an essential item for self-sufficiency, every town having its own vehicle factory is excessive in terms of resource utilization. It helps to conceptualize self-sufficiency in light of unexpected calamities. The autonomy of a town should be high enough to support its own basic operations indefinitely in case of most unexpected calamities. The network of towns could then support the non-essential elements. A country, conceptualized as a network of towns and settlements, increases what are ‘basic requirements’ to all essential operations of a country. For example, while a single town may not need a university as an essential basic service to continue to operate (people can go to another town for it), a country as a whole certainly does (there needs to be one for all the town to be able to get to). Therefore, the self-sufficiency of a resource or a system is intricately bound to an understanding of its scale and its relation to the network. Scope of self-sufficiency It is often helpful to define a scope and the degree with which self sufficiency should be reached. This scope determines which services are included in the set of basic resources. This then determines the living standard in times of need. Again here, the scope should not be in excess, to avoid ostracizing the community. A scope that is too low though may threaten self-sufficiency, or the capacity for network support. The degree of self-sufficiency has to do with how long, or to what extent items in the scope are self-sufficient. For example, when making a plan for a self-sufficient housing neighborhood in the Netherlands, we decided that food, electricity, heating, water, and waste were in the scope. For food self-sufficiency, we determined that its degree of self-sufficiency was to provide the essential need for basic nutrient intake for all its inhabitants in case of total disconnect from the rest of society for a period of at least 3 weeks. Self-Governance This is the ability of agents within a system to determine their own actions, especially concerning the basic resources that make up its self-sufficiency set. For example, the ability of a town’s local population to be able to make their own decisions concerning their water supply, power, food production, etcetera. For a company, this may relate to employees having the authority to make their own working environment workable, and to have a say in the basic resources and parameters of production. Self-governance has a strong relation with Harmony’s ‘Power balance’ and ‘Equity’ parameters. Self-Governance focusses on forces of control from outside that may be acting on the system. The parameters inside Harmony focus on the interrelations of the agents inside the system. Circularity A system’s Circularity is the degree with which its (essential and non-essential) resources are reused within the system. A system whose resources retain its value and quality when reused requires less replenishment from outside its system. Consequently, the system becomes self-reliant and efficient. Circularity is a panacea for imminent material shortages, pollution generation, and waste production. Circularity is measured against the degree to which resources are, and potentially can be used in a circular way. Circularity seeks a healthy balance, because not all resources can be re-used, and it is not always desirable for all materials to be reused. Circularity also encompasses value retention or transition that resources undergo during their life cycle. Consider a town that recycles its drinking water (from its water fountain) into grey water. This is a case of down-cycling, as the water by means of its transformation, deteriorated in value. On the other hand, value retention is evident in the case of toner cartridges that are designed to be disassembled, refilled, and returned to the store shelf. The same goes for products. If a product-life cycle recycles a piece of plastic only as throwaway plastic bags, it is degrading the value level of the resource, and while it’s recycling, it’s not actually all that circular of a system. Circularity is a factor that has received much attention in northwestern Europe, under the approach called the ‘Circular Economy’. Because of this attention, more existing tools are available for circularity than for other parameters. See the tools section for more explanation on the Circular Economy. levels of circularity Circularity is expressed in lower or higher levels of preference, as can be seen in the SiD Rocket diagram on the right. They are categorized from the best to the worst: Super-use Direct re-use Refurbishing Remanufacturing Recycling Waste This same idea can be found in other frameworks used in the field of Circularity, such as the Waste Hierarchy / Ladder of Lansink (diagram below), and its counterpart, the more popular Circularity mantra of Reduce, Reuse, Recycle. While circularity commonly applies to the lower ELSI stack tiers (energy & materials), it is equally relevant to the higher ELSI stack domains (life, society, individual). In fact, interesting connections can be established with the upper ELSI stack domains. For example, household waste used as a building block for a local vegetable garden improves food production awareness, and the community’s wellbeing by means of better nutrition and biophilic exposure. Measuring circularity There is a variety of tools available to measure circularity, for example the ‘Material Circularity Indicator’ of the Ellen MacArthur Foundation. This basic formula uses the following inputs: Input in the production process: How much input is coming from virgin and recycled materials and reused components? Utility during use phase: How long and intensely is the product used compared to an industry average product of similar type? This takes into account increased durability of products, but also repair/ maintenance and shared consumption business models. Destination after use: How much material goes into landfill (or energy recovery), how much is collected for recycling, which components are collected for reuse? Efficiency of recycling: How efficient are the recycling processes used to produce recycled input and to recycle material after use? For more information on developing specific indicators for material Circularity, see the free publication CIRCULARITY INDICATORS, An Approach to Measuring Circularity”, Ellen MacArthur Foundation, 2015. Please note that these standardized indicators do not (yet) take into account the full spectrum of ELSI’s categories. Network Support Network support measures to what degree the system can provide support to external systems in times of need. In a sense, it is a sister indicator to the Redundancy network parameter. It measures the ability of the system’s resources covered by the self-sufficiency scope to be delivered to neighboring systems to support shortfalls in their operation. We’ll get to specific system dynamics later, but it’s good to note here that the system dynamic Law of Decreasing Marginal Returns is strong in this one. As a network of systems starts to break down, each individual system’s capacity to support failing neighboring systems goes down with it, until the entire network becomes brittle and collapses. A high rate of Network support in a system is therefore not just nice to have as friendly neighbors, but a primary sign of a healthy system. This can then also be seen as a feeder of Resilience to external systems. A Network support capacity of zero shows that the system can only take care of itself, which usually means it is at the brink of its own capacity to survive. If Self-sufficiency is low, Network support can become negative. Then, the system relies on external systems for the supply of critical goods and services, and burdens those systems around it. Efficiency Efficiency is a measure of how well a network is servicing its intended goal compared to the resources it needs to achieve this performance. Efficiency in itself is not a goal, but when comparing systems, this parameter is useful for finding optimization strategies. Note that a highly efficient network may not be a resilient one, and Efficiency and Resilience may be opposed at times. Typically, you want Efficiency to be high as high as possible until it starts interfering with the other parameters that help to establish a high Resilience. It’s often easy to improve Efficiency by reducing parameters such as Redundancy and Connectivity, but that usually reduces Resilience. A focus on Efficiency can therefore be dangerous, especially when it has been made into a goal, which it should never be. Efficiency in itself should never be a goal for a sustainable system. SiD Rocket This diagram is a generic representation of the stages of an object’s life cycle through a system. It shows the main steps of the object’s life cycle in the blue arrows, and the required inputs and impacts at each step. When investigating a life cycle, each of these is detailed to make an assessment of the costs, impacts and benefits of the cycle as a whole. It’s helpful in establishing the necessary autonomy for various services and indexing impacts of an object within its system, and to observe the different stages of circularity. ““We can’t surge forward with certainty into a world of no surprises, but we can expect surprises, learn from them, and even ‘profit’ from them. We can’t impose our will upon a system. We can listen to what the system tells us, and discover how its properties and our values can work together to bring forth something much better than could ever be produced by our will alone.”

• Donella Meadows, 2008n

the harmony network parameters PEAIE harmony network: PEAIE in Detail Harmony is a measure of internal tension in a network. It takes into consideration social justice, as well as the rights of not just humans but also of other organisms. Below, the five Harmony network parameters are listed, followed by some frameworks to help evaluate them. Power Balance Who controls what happens, and influences decision making? Including distribution of assets; who controls the resources and wealth. Expression Who can talk, who is heard, and what can be said openly? Including freedom of expression and/or repression of perspective or opinion, commitment to transparency and voluntary free flow of information. Access Who can access important information, resources, education, etc., and to what extent? Inclusion To what extent are people and all other life considered valuable in relation to each other? Including civil and political rights, economic, social and cultural rights, gender and race equality. Equity To what degree do those that have specific needs have those needs met equitably? Justice and Human Rights Frameworks In 1949 the UN department of Realization of Economic, Social and Cultural Rights suggested to use a set of indicators to measure and track progress for human rights goals for the first time. If you work on projects where human rights and/or equity are important, such as national policy or corporate strategy, you can use the below frameworks to help inform the Harmony para­meters. A few of these are: Universal Declaration of Human Rights (UDHR). The basic 30 articles, fitting on one sheet of paper, that was adopted in 1946 by the 56 nations in the United Nations. A minimum baseline. UN 2012 Human Rights Indicators: A Guide to Measurement and Implementation. A comprehensive and freely available framework for the evaluation of human rights. Useful for evaluating nations, regions, governments, and large organizations and their supply chains. Natural Capital A body of thought, work, frameworks and indicators attempting to quantify value of natural resources and ecosystem services, to protect and expand them. Human Spaces Report A way to measure and implement nature’s inclusion into the workplace. EU Social Justice Index 28 quantitative and eight qualitative indicators, distributed across the sections of poverty prevention, equitable education, labor market access, social cohesion and non-discrimination, health, and intergenerational justice. Power balance Power balance reflects on how the resources that give agents power to act, over themselves and over other agents, are distributed. When applied to the ELSI stack, you’ll see that these resources can be numerous, including physical resources such as water, energy, and land, but also nonmaterial things such as information, decision-making agency, capital, and in some cases, other agents (slavery, farming for plants and animals). Power balance has a large influence on the tension within a system, and thus, on Harmony. For example, an oppressed population revolting to overthrow their despots triggering strife, death, and destruction, which consequently result in the collapse of that society. Power balance is often dynamic and shifts over time. The preeminence of access to food and natural resources as the main currency of Power balance has been overtaken by access to and control of information. In this day and age, developed societies prize information not just merely for survival but also for superiority. Few people in the developed world can function anymore without internet. Typical areas of interest to investigate here include forms of government, voting rights, wealth and asset distribution, and agent’s decision making power over themselves and others. Expression Expression is about how agents can and do communicate with one another. The resilience parameters of Transparency and Awareness deal with an important part of this equation of the network as a whole, and Expression allows deeper investigation on issues such as freedom of speech, repression of particular issues or groups of agents, and commitment to Transparency and voluntary free flow of information. A high degree of Expression is important for a good Harmony in a system. This means that most means to purposefully curtail Expression, either in form or content, will likely harm a system. Not just the level of basic Expression (which agents can talk freely, what subjects are restricted) is important, but also the reception of Expression (who or what is actually heard). This also may be related to the ‘Validity’ resilience network parameter: if there is full freedom of Expression, but Validity is low, a system will have tension. But, with high Expression, the system may find ways to correct this low validity itself. If Expression is high, and Access is low, there may be a bias in who actually gets to benefit, use and reap the benefits of Expression, and also give rise to tension. Access Access focusses on the level with which agents in a system can access critical assets, information, resources, education, etc. In societal terms, this may also include the ability for agents to travel to other places (power of passport), and physical Access to places of (free) education and information exchange. For instance, a person who has official access to higher education may be financially prohibited from pursuing it. In this case, it can be said that Access to higher education is low. Access therefore is defined in terms of participation rights and/or capacity (being able to participate if willing). Restricted Access to valuable resources for large groups of agents may produce tension and destabilize a system. Circling back to the education example, the effects of educational deprivation may be evident only in the next generation. Similarly, correcting Access issues may take at least one generation. inclusion Inclusion is a measure with which agents in a system are included in the general set of laws, regulation, or cultural habits to which rules of ethics apply. This reflects on slavery as well as discrimination, and more broadly about all living things, the rights of organisms beyond human society. To exemplify this, we can look at the development of society over the centuries. In the Old World, only men of good standing were included in the so-called ‘ethical set’. Women, children, slave men, and all other living things outside of man, were considered possessions that a man of good standing could do with as he pleased. Murder was considered with gravity only when men of good standing were implicated. Over time, more agents were included in the ethical set. In ancient Egypt for example, infanticide came to be outlawed. However, it was legal to keep children as slaves. Through the thousands of years that followed, women, children, and to some degree animals, have gained more inclusion into the ethical set, although the degree of inclusion is unevenly distributed around the world. While slavery is now officially illegal in all countries of the world, prison slavery is still allowed even in some states of the USA, and practices akin to slavery are still widely present. Inclusion can also be used as a measure of fairness within organizations, for example, to see what rules apply to what agents in an organization. Equity Equity measures to what degree agents within a system have their needs met, according to their ability. This is different from equality, which distributes equal amounts to each agent. Equity is about fairness in distribution, not equality. Consider the mundane matter of access to buildings. While provision for disabled persons (handicap ramps, etc.) typically cost more than provision for able-bodied persons, it is nevertheless important for disabled persons to have equal access. Equal access here points to the usage rights of buildings and its relative facility for users with different needs. Literally, creating a level playing field. Equity is a fundamental property of any society. Equity as a parameter serves to evaluate distribution of power and resources, freedom of speech, access to resources, and inclusion. Ethical considerations matter significantly in Equity. “Faced by the magnitude of the unknown, we are lead to the limit of what analysis can do, and then point beyond– to what can and must be done by the human spirit.”

• Donella Meadows, 2008n