Category: systemic risk

How to generate relational information to inform a systemic perspective on risk?

How to generate relational information to inform a systemic perspective on risk?

This is the seventh in a series of eight articles co-authored by Marc Gordon (@Marc4D_risk), UNDRR and Scott Williams (@Scott42195), building off the chapter on ‘Systemic Risk, the Sendai Framework and the 2030 Agenda’ included in the Global Assessment Report on Disaster Risk Reduction 2019. These articles explore the systemic nature of risk made visible by the COVID-19 global pandemic, what needs to change and how we can make the paradigm shift from managing disasters to managing risks. 

“A lightness in the way we hold thoughts gives us room to learn, to shift perspective, and to keep a rigorous humility in confusion”, Nora Bateson

Complexity vexes the traditional problem-solving model, which separates problems into singularly defined parts and solves the symptoms. The COVID-19 pandemic or the climate and ecological crises are pressuring policymakers to try new approaches to meet today’s challenges. But none of these “wicked problems” can be understood with reductionist approaches alone.

In other words, the deliberate simplification of a problem and its causes – by removing it from its contexts – renders the understanding and ensuing policy responses or solution either incomplete or obsolete. The issues raised by the COVID-19 pandemic are wrapped in contextual interdependencies that require an entirely different approach in assessment and action.

Most current scientific research tools and methodologies pull “subjects” from their contexts to derive detailed, specialized, quantifiable information. We need a wider practice of science to also use information derived from interrelationships and interdependencies within and across systems. For now, the cultural habit of de-contextualizing information, or reductionism, is the standardized, authorized and empirical norm.

To make more appropriate assessments of risks – arising out of multi-causal circumstances – we need observations that can address this complexity. The decisions on what actions to take, by whom and with what resources, are decisions based upon information about the situation or event. If that information cannot hold the appropriate complexity, these decisions will rely on inadequate knowledge, resulting in greater loss and damage – economic, human and ecological.

Transcontextual responses

Risk creation and its realization in complex systems do not remain in one sector at one time. Yet current institutional structures mitigate these complex issues by attending only to what is within their specific jurisdiction. Health crises remain in the realm of health ministries, while economic issues are under the separate attention of ministries of finance or employment. Likewise, ecological risks overlapping with cultural or political risks are still, in most cases, considered in parallel within the ministry of environment. Yet, as evidenced by the COVID-19 pandemic, we must research and better understand the relational interdependence of these phenomena.

We need research bridges and increased communication across societal systems. This is particularly true of public service systems. Lack of communication and contextual perspective (among systems such as education, health, transportation and communication) can increase community-level vulnerability during complex, dynamic systemic risk events. Connection and increased contact between such sectors will make communities more robust and resilient to long-term risks and sudden onset emergencies. The development of relational information approaches can cultivate the relationships among sectors. This strengthens inter-system interaction and collaboration, both within and across countries.

Relational information

‘Relational information’ describes how parts of a complex system (for example, members of a family, organisms in an ocean reef system, departments of an organization or institutions in a society) come together to give vitality to that system.

Relational information describes the interplay and vital relationships of the parts of a system in context. Other information will describe only the parts. For example, to understand a family, it is not enough to understand each family member. You must also understand the relationships between each of them. This is the relational information. This relational information (also known as ‘warm data’) helps to better understand interdependencies and improve responses to issues located in relational ways to each other within complex systems.

This is particularly important in understanding the realisation of a complex systemic risk such as the COVID-19 pandemic. Because such an event includes multiple systemic risks across many living systems and contexts – in health, ecological, economic, and education systems and many more. Attempting to suppress complexity (or de-contextualizing) gives specific information that can generate mistakes. In contrast, relational information gives a more coherent understanding of the complex nature of the systems.

Systemic consequences (and consequences of consequences) are easily disconnected from their networks of causation. In so doing, the importance of the relationships among contexts can disappear. Context includes the relational processes that come together to produce a given situation. In fact, most complex situations or systems are ‘transcontextual’, meaning there is more than one context in play. Transcontextual, relational information brings together multiple forms of observation, from multiple perspectives.

In recognition that information comes in many forms, a relational information lab (or warm data lab) brings together on-the-ground “wisdom” from locals, art and culture, personal stories and the voices of many generations in a series of transcontextual conversations and exchanges. The task of generating relational information is not only to incorporate details and data points, but also to highlight relationships among the details as well, at many scales simultaneously.

Around the world, researchers, governments, and public service professionals already use contextual or relational information in the form of warm data.  This is particularly helpful to assess complex situations and identify preventive approaches or responses to complex community (or health) crises requiring expertise that spans a breadth of contextual conditions.

When applied to specific local contexts and fields, scenarios using warm data can be useful to involve local stakeholders and decision makers in a transdisciplinary environment – a collaborative laboratory or “collaboratory”. The approach allows the production of alternative futures that are robust to all the relevant uncertainties and complexities. A set of scenario exercises can help to identify stakeholder preferences, motivations, scale-specific trends and drivers, and most importantly, add the local contexts needed for the modelling exercises to formulate appropriate, timely and proportionate policy responses and solutions.

Changing patterns of interaction at local levels using transcontextual knowledge processes

The natural extension of the above process is bridge-building across systems, across silos. This is a step towards forming collaborative decision-making bodies at local levels. This can bring together people from different, but interdependent fields to explore and energize or regenerate local community vitality. As these community groups form and exchange knowledge, new communication patterns begin to emerge, linking otherwise separated sectors of experience.

The place-based solutions that emerge from the collaborative development of contextual warm data lend themselves to self-organizing around actions that are co-created, with local ownership of data, risks and solutions. By providing context, warm data is a metashift that generates connection, communication and action. It unlocks new ways to address complexity through a systemic perspective, not a siloed perspective. Drawing from collective intelligence and engaging in mutual learning can quickly increase local capacity to deal with even the most complex, dynamic systemic risk challenges

When human interaction occurs in this way, across contexts, the interdependency becomes plain. For example, food cannot be separated from economic, nor even political, systems. Neither can it be separated from culture, nor health, nor identity. The solutions in complex systems lie in the recognition of a collective response. No single response is enough to address a complex problem like the COVID-19 pandemic.

Warm data is the overlap across systems and is produced by groups of people, either in-person or online, with enquiry practised in crossing contextual frames, sense-making and finding patterns. The lens of contextual enquiry and transcontextual research not only brings disciplines together but also many other forms of knowledge – including the place-based wisdom of local practitioners, as well as cultural and indigenous sensitivities.

We need structures and approaches that can bring forward relational information that presents the contextual interlinking of the potential impacts of disasters such as the COVID-19 pandemic as they are felt at the individual level within wider global contexts. 

When superficial solutions are implemented to provide answers to problems in complex systems, the problems proliferate. Developing the capability for transcontextual understanding and decision-making from a systemic perspective is far more effective. The benefits are then felt across multiple sectors simultaneously, including at municipal and national levels of government.

The next and final article in this series (#8 of 8) introduces the United Nations response to the need for improved understanding and management of the systemic nature of risk incorporating collective intelligence and relational information. The Global Risk Assessment Framework (GRAF) aims to work across all scales and all typologies of risk. Including complex, systemic risk events such as the COVID-19 pandemic. It is in service of the needs of people across the world to engage with complex systems. And to support them to make better decisions both in the short- and the long-term.

Cover photo by Martin Sanchez on Unsplash.
How important is building collective intelligence to better manage systemic risks?

How important is building collective intelligence to better manage systemic risks?

This is the sixth in a series of eight articles co-authored by Marc Gordon (@Marc4D_risk), UNDRR and Scott Williams (@Scott42195), building off the chapter on ‘Systemic Risk, the Sendai Framework and the 2030 Agenda’ included in the Global Assessment Report on Disaster Risk Reduction 2019. These articles explore the systemic nature of risk made visible by the COVID-19 global pandemic, what needs to change and how we can make the paradigm shift from managing disasters to managing risks. 

“Never doubt that a small group of thoughtful, committed people can change the world. Indeed it is the only thing that ever has.”, Margaret Mead

Risk is a human construct. It is created in language and meaning to describe the felt or feared volatility and uncertainty of human life. In other words, it describes the experience of complexity and of complex systemic effects. Humans in many societies have become accustomed and attached to the illusion of control that the construct of risk has given us. But as the COVID-19 pandemic develops, it becomes clear that the effects of interdependent, globally connected systems and vulnerabilities may be beyond accurate human measurement or effective management. We must acknowledge the limits of that illusion and the limits of present systems of governance and organization of human knowledge.

This requires a new paradigm for understanding and living with uncertainty and complexity. One that activates the power of human, social and contextual intelligence, and where possible, leverages it through appropriately designed artificial intelligence. This is at the core of systemic risk governance.

Developing the capability for contextual understanding and decision-making is a far more effective way of dealing with uncertainty and complexity than the present reliance on extrinsic frames of reference and categorical technical expertise, siloed into disciplines. In part, such capability is built using a lifelong learning approach to grow an aware, internalized ability to notice the relevance of context and the role of self, and in doing so, to recognize and anticipate interdependencies and nonlinear effects. That is demonstrably not wide-spread across populations affected by the COVID-19 pandemic.

Human decision-making is emotional, not rational. It is thus more successfully activated by mental models based on meaning attached to values and beliefs. Over time, the use of narrative and meaning to negotiate the changing relationship between identity and context has proven to be an effective mechanism to build resilience and to enable rapid sensing, understanding and sensemaking. In this way, collective intelligence becomes possible as an essential precondition for collective responsibility. Collaboration with and through that intelligence holds the key to building systemic resilience to challenging, complex and dynamic risk events such as the COVID-19 pandemic.

Collective intelligence

‘Collective intelligence’ is the powerful combination of human intelligence, artificial or machine intelligence and processing capacity.

Building resilience is necessary to reduce risks and prevent disasters, and when necessary, adequately respond. Resilience requires:

  • Planning and preparation based on assessments to avoid or minimize risk creation and reduce the existing stock of risk;
  • The development of capacity to restore functions in the face of disruptions; and,
  • The capacity to adapt and change after a shock.

By addressing these complex systems challenges, every individual, organization or group involved in resilience building could thrive by tapping into a “bigger mind” through collective intelligence. This could be by drawing on the brain power of other people with diverse cultural experience, age, education or occupation and gender, combined with the processing power of machines.

While needed for processing big data about the functioning of complex systems, machine learning and artificial intelligence do not help people to solve more complex coordination and governance problems – like physical distancing – that need trust between people. They cannot decide on how people want to live human lives, for example in densely populated cities. This is a complex human dynamic problem, solvable only by humans making decisions and taking action.

Truly global collective intelligence is a long way short of being able to solve global problems. It is now important to assemble new combinations of tools that can help the world think and act at pace, as well as at the scale commensurate with the complex problems we are currently facing, including the COVID-19 pandemic and the climate and ecological crises.

In too many fields, the most important data and knowledge remain flawed, fragmented or closed. They lack the context and organization required for them to be accessible and useful for decisions. As yet, no-one has the means or capacity to bring them all together into a universal, pluralistic data ecosystem, let alone into a dynamic three-dimensional topographical map of risk through time. 

The critical interdependence among human health and well-being, ecology and technology is highly complex. The complexity lies both in the dynamic nature of connections and in responses in time and space. To effectively manage and govern a complex risk event like the COVID-19 pandemic, we need an improved understanding of human–ecological–technological system interactions. This is starting to be achieved in some fields through the application of new types of sophisticated multi-layered computer modelling.

Thanks to this revolution in systems modelling, it is now possible to begin modelling the interlinkages and interdependencies among the economic (values), societal (health, welfare and productivity) and environmental impacts of decisions and investments driven by the live interactions between weather, Earth crust shifts, soils, land, and ocean ecology and human activity. Geodata at many scales support this approach to better understand the interactive nature of the drivers of risk and for long-term risk reduction. But its practical application remains limited for complex, systemic risk events. As evidenced by the COVID-19 pandemic, this needs to change, and change quickly.

Technology-based solutions to coordination problems need to be combined with human-based solutions, made by or involving humans for solutions at a human scale. Unlike machines, which need to operate with probabilities, humans – within a social network of trust – can make decisions under radical uncertainty by attaching values to decisions. This ability in healthy human beings is due to emotional responses to highly complex decision situations. In such situations there are no solutions from purely calculative and value-free accounting or analysis of costs and benefits.

Under conditions of extreme, systemic risk – such as the COVID-19 pandemic – humans can (and should) decide on changing deeply embedded values that define higher level rules, and shape attitude, choices and behaviour.

We are now living a critical time calling for fundamental reflections on the impacts and consequences of individual and collective choices, and the accountability for those impacts and consequences. Otherwise, societies may continue to create financial and economic wealth at the expense of human health and the declining ecological life support functions in a positive spiralling feedback loop. This will further create systemic risks with cascading effects making overarching economic, ecological and social systems increasingly susceptible to collapse.

The next article (#7 of 8) in this series discusses the challenges and opportunities of generating relational information to inform a systemic perspective. It explores how to help decision makers, including government officials, to be more sensitive to interdependencies and the dynamic nature of risks and to ultimately improve whole-of-society outcomes during and after complex systemic risk events, like the COVID-19 pandemic.

This article was originally posted on PreventionWeb.
Cover photo by Gabe Pierce on Unsplash
Can systemic risks ever be effectively governed?

Can systemic risks ever be effectively governed?

This is the fifth in a series of eight articles co-authored by Marc Gordon (@Marc4D_risk), UNDRR and Scott Williams (@Scott42195), building off the chapter on ‘Systemic Risk, the Sendai Framework and the 2030 Agenda’ included in the Global Assessment Report on Disaster Risk Reduction 2019. These articles explore the systemic nature of risk made visible by the COVID-19 global pandemic, what needs to change and how we can make the paradigm shift from managing disasters to managing risks.

Governance generally refers to actions, processes, traditions and institutions (formal and informal) to reach and implement collective decisions. Risk governance is “the totality of actors, rules, conventions, processes and mechanisms concerned with how relevant risk information is collected, analysed and communicated and how management decisions are taken.” Risk governance is usually associated with the question of how to enable societies to benefit from change, so-called “upside risk”, or opportunity, while also minimizing downside risk, or losses. In contrast, systemic risk is usually seen as downside risk.

As illustrated by COVID-19, the realization of systemic risk by definition leads to a breakdown, or at least a major dysfunction, of the system as a whole. Assessing, communicating and managing – in short, governing – systemic risk is compounded by the potential for losses to cascade across interconnected socioeconomic systems. Losses can cross political borders (including municipal and national boundaries), can irreversibly breach system boundaries and can impose intolerable burdens on entire countries. Systemic risk governance is also confounded by almost intractable difficulties in identifying causal agents and in assigning or attributing liability.

What needs to be set up so that institutions can govern systemic risk? Like any emerging phenomena, systemic risk cannot be measured by quantifying each of the contributing parts. This means that effective governance must consider the interconnected elements and interdependencies among individual risks, within and across systems.

For this purpose, a network perspective, with attention to interconnected nodes or agents, is useful. Individual and institutional decision makers also need greater accountability and responsibility, for example, through the establishment of the principle of collective responsibility.

Systemic risk governance requires new institutional structures. This was recognized after the global financial crisis in 2008. Prior to that, early warning systems (EWSs) were in place to identify precursor signals and anomalies in the overall performance of the complex financial system. Yet they failed to detect what are now understood to be clear signals. In 2007, the estimated probability of a financial crisis occurring was between 0.6% and 3.4%.

Financial systems operate in a siloed fashion. Constituents operate from their perspective and within their mandates. Yet such systems often become corrupted. Or they behave in a way that is suboptimal or pro-cyclical at a systems level, thus reinforcing underlying dynamics. Few organizations have the wherewithal to investigate at a system level, let alone a system-of-systems level. Consequently, ownership of the problem is often lost.

The global financial crisis prompted the development of new – or the reshaping of old – institutions and mechanisms to identify, and ideally prevent, future systemic risks in the financial system. But, post-crisis governance structures remain insufficient to prevent a further financial crisis – or the realisation of other systemic risks, such as the current COVID-19 pandemic.

The financial crisis focused attention on global interdependencies and cascading risks with potentially catastrophic consequences. But there are a worrying number of other potential triggers. These include, amongst others, extreme climate events, armed conflict, forced migration, food system disruptions, food and water shortages, unregulated digitalization, loss of biodiversity and zoonotic pandemics such as COVID-19. The climate crisis is a systemic risk with potentially catastrophic impacts cascading through financial, ecological and social systems. Climate change also has one of the most developed global governance regimes.

Neither the governance of the financial system nor the climate system can claim full success. But both have raised awareness of the necessity, and spatio-temporal complexity, of governance regimes to address systemic risks at the global scale. Moreover, the financial and climate governance regimes have brought attention to the complex web of challenges. One major challenge is establishing causal attribution of systemic losses as the basis for assigning accountabilities and responsibilities. This is essential for risk governance.

Attribution in relation to systemic risk is generally unclear, in particular where large uncertainties exist in determining the causal effects across complex geospatial regions, across stakeholders, and across sectors. For example, experts generally agree climate change amplifies the risk of extreme droughts and floods in some regions. Yet attributing losses from any event to human-induced climate change is still unachievable. As we observe in the COVID-19 pandemic, attribution is further complicated as systemic risk can evolve up to the global macroscopic scale, through disruptions at the microscopic scale; so-called “scale-free properties”, or through behaviour that is not directly linked to the disruption it causes in a specific system.

So, the difficulty of attributing accountability bounds the solution space for the reduction of systemic risks. It also hampers the urgent development of a joint vision defining clear approaches to management and the development of much needed policy responses at appropriate scales.

Another challenge, although not unique to systemic risk, is the often deep uncertainty surrounding the triggers, exposure and cascading consequences. Adopting a systems approach that takes account of network dynamics and social processes can form a basis for designing risk governance approaches in this context.

Beyond uncertainty, the lack of understanding of the systemic nature of many risk contexts poses a more daunting challenge. One suggestion taken from the climate risk community is to use a triple-loop learning process. from reacting to reframing and finally to transformation. This is also in line with suggestions made towards an adaptive risk management framework with a focus on solutions with multiple benefits.

The need for inclusive stakeholder expert processes is at the core of any risk governance framework, including systemic risk governance. These are important for co-designing and co-generating information, evidence and responses or solutions. While the importance of stakeholder buy-in has become clear, there are special challenges for systemic risks. For one, the cascading and uncertain nature of the losses means that stakeholder communities are ill-defined and often span political borders. Because of the uncertainty, the issues are characterized by varied perspectives on the nature of the problem and its solution, as well as different “risk constructs” on the part of the stakeholder communities.

For the “realists”, the risks can be objectively assessed in terms of their likelihood and impact. Whereas for the “constructivists”, the existence and nature of risk derives from its political, historical and social context. That is, it is constructed.

The two divergent views can have a significant impact for policy implementation. Modernity reflexively relies on increasing complexity to manage the very risks it creates. These in turn cause disasters that are often embedded in the construction of social organizations and institutions. Consequently, iterative approaches are better able to determine potential conflicts and possible solutions by identifying precursor signals or anomalies in system performance at the earliest possible moment.

Human agency may play a less-important role in some systemic risk considerations (for example, in supply chain risks) than in others (for example, a pandemic like COVID-19). This is important to consider for the corresponding governance approaches. The question is related to the optimal complexity to govern systemic risk. That is, how detailed the approach should be, given that there are always limited resources.

In the case of complex systems and systemic risks, current measures and approaches represent a collection of failed attempts. Nevertheless, the approaches are raising awareness and addressing challenges. These can shed light onto critical aspects of what is itself a complex issue – systemic risk governance.

Emerging approaches (for example, the International Risk Governance Center (IRGC) systemic risk governance guidelines) seek to address the difficult problem of assessing or measuring systemic risk, of modelling cascading consequences, of applying different management instruments, and of implementing participatory processes.

Successful implementation of such systemic risk governance approaches assumes flexibility and (continuous) adaptation to context (that is, adopting an iterative process). It is contingent upon strong leadership (with mid- to long-term focus), to prove the willingness to adapt or revise often non-linear, non-sequential processes, and the willingness to accept and resolve trade-offs. Applying insights from more conventional risk analysis, risk communication and risk management to connect systemic risk with more traditional risk governance approaches can speed up the transition from managing disasters to managing risks.

The next article in the series (#6 of 8) builds off this exploration of some of the necessary elements to consider for systemic risk governance. It focuses on the importance of building collective intelligence to understand how parts of systems are related. It also explores the implications for improving both direct and indirect policy responses in challenging, dynamic systemic risk contexts, such as the COVID-19 pandemic.

Photo by Marco Oriolesi on Unsplash
Direct virus lessons we can learn as we go

Direct virus lessons we can learn as we go

By Alex Kirby

What history knows as the 1918 ‘flu pandemic infected about a quarter of the world’s population at the time – around 500 million people – and left virus lessons for this generation, whether or not it’s learned them.

Thankfully, the 2020 coronavirus outbreak shows no sign yet of matching last century’s virulence. There are growing calls, though, for the world not just to get back to normal, but to turn this global horror into an opportunity to rebuild by finding a better normal to reclaim.

In late 2018 the Rapid Transition Alliance was launched with the intention of building a community to learn from moments of sudden change and to apply those lessons to the climate emergency.

Changes in the biosphere are happening faster than changes in human behaviour, so the question the Alliance asks is this: how do we match the speed and scale of social and economic change with the science – and what it is telling us to do?

It is now working with two other British organisations, the original Green New Deal group and Compass, the campaign that builds support for new ideas among social movements, decision-makers and political parties.

In the first of several digital meetings the three have begun to sketch out a framework for how society can “learn as we go” from unprecedented events. They have identified five principles for a just recovery, which say in essence:

  • Health is the top priority, for all people, with no exceptions. That means resourcing health services everywhere and ensuring access for all.
  • Providing economic relief directly to the people is vital, particularly those marginalised in existing systems. Concentrate on people and workers and on short-term needs and long-term conditions.
  • Assistance directed at specific industries must be channelled to rescuing communities and workers, not shareholders or corporate executives, and never to corporations whose actions worsen the climate crisis.
  • The world needs to create resilience for future crises by creating millions of decent jobs that will help power a just transition for workers and communities to the zero-carbon future we need.
  • We must build solidarity and community across borders: do not empower authoritarians, do not use the crisis as an excuse to trample on human rights, civil liberties, and democracy.

An indication of the degree of international support for the five principles is available here.

Making things happen

The principles are already accepted by millions of people, but are no closer to reality, for all that. If they were, the climate crisis would be almost over. What can the three groups offer to make them happen?

The coordinator of the Rapid Transition Alliance is Andrew Simms, author of a summary of what the discussions have agreed so far. He told the Climate News Network: “Nobody can guarantee that things will turn out any certain way.

“But once people have seen what it is possible for a nation to do, and how fast it can do it, it is much harder for those in power to justify inaction, or wrong action.

“The current pandemic crisis is wreaking havoc on families, communities and whole economies. But it is also changing our ideas about what really matters to people and also what it is possible to do as a nation when faced with a great challenge.

“There is a new appreciation of key workers who provide the goods and services that a society really relies on – like health services and those in the food supply chain – but who typically lack recognition or are poorly paid.

Good-bye to inertia

“One of the greatest enemies in overcoming the climate emergency has been the sheer inertia of business-as-usual. Now there is a great sense of people taking stock of what is truly important.

“Vitally, when there is a fundamental threat to society, we have seen that financial resources can be mobilised. Fundamental change cannot happen without there being a consensus that it is both desirable and possible.

“The last few weeks have made visible underlying cracks in society, but also our ability to fix them. Once people have seen that, they are unlikely to settle for less.”

This first meeting spent some time talking practicalities, including how to protect wages and income. One example was the call by a member of Parliament for the introduction of a basic income scheme. Globally, the pandemic has prompted the United Nations to call for a worldwide ceasefire.

Overall, the summary says, greater consensus is emerging on how our economy and way of life relies on public not private interests, from health services to community aid groups, and that both local and national government have a vital enabling role on the need to improve the resilience of the economy at a national and local level.

Broadband before wheels

A radical reappraisal of transport came days after the meeting from the president of the UK’s Automobile Association (AA), Edmund King, who predicted a major shift in behaviour after the pandemic.

“People travelling up and down motorways just to hold meetings is inefficient, expensive and not good for the environment”, he said. “I think the use of road and rail and indeed bus will be reduced after this crisis.”

The AA, seen for years as a stalwart member of the roads lobby, said government funds for new transport infrastructure, including roads, might be better spent on improving broadband access to support home working.

The meeting agreed that the UK economy lacks a supportive town centre retail banking infrastructure with the capacity to administer a support scheme.

The build-up to the 2007-2008 financial crisis saw the evacuation of local banking services from the high street, and now the pandemic was making clear that the withering of local financial infrastructure in the UK must be reversed.

Universal and more mutual banking services are needed to build more resilient local economies, the three groups agreed. More progressive business models like social enterprises, which have direct community links, and the co-operative movement may help to provide answers.

This article was originally posted on the Climate News Network.
Cover photo by G-R Mottez on Unsplash.
Are there fundamental characteristics of systemic risks?

Are there fundamental characteristics of systemic risks?

This is the fourth in a series of eight articles co-authored by Marc Gordon (@Marc4D_risk), UNDRR and Scott Williams (@Scott42195), building off the chapter on ‘Systemic Risk, the Sendai Framework and the 2030 Agenda’ included in the Global Assessment Report on Disaster Risk Reduction 2019. These articles explore the systemic nature of risk made visible by the COVID-19 global pandemic, what needs to change and how we can make the paradigm shift from managing disasters to managing risks. 

This is a deeper, more technical dive into important recent work predicated on the concepts discussed in the last article in this series (#3 of 8). They suggest that the shape of risk is similar in very different systems. The ‘homomorphism’ of systemic risks in different domains suggests that as attempts are made to understand the effects of endogenous triggers and critical transitions, there will be more patterns apparent in different domains. This will allow the development of a consistent understanding of the fundamental characteristics of systemic risk.

An apparently stable macro-configuration of a complex system – like the global aviation system – will break down, and will be re-shaped by amplifications of a series of micro-events (like restrictions of flights to and from just a small number of countries) until a new, stable macro-configuration emerges. To apprehend these critical aspects and to disseminate new approaches for decision makers at various scales (in a relatively simple-to-understand format), we need a more comprehensive understanding of the spatio-temporal dimensions of complex, systemic risks and the differentiated nature of ‘complicated’ and ‘complex’ systems.

To characterize systemic risks, which involves dealing with information gaps or ambiguity, it helps to capture the random patterns of possible disasters such as the COVID-19 pandemic on maps of values describing the vulnerability of people, infrastructure, economies and activities. A resulting systemic risk model will then allow for a quantification of mutually dependent losses in space and time. This will allow for the use of stochastic risk management models. Stochastic systemic risk assessment tools recognize complexity and the inherent unpredictability and chaos in complex systems.

These models do not try to simplify things to make calculations easier. They represent how complex components – such as interactions and interdependencies between disease spread vectors, human behaviour, health system infrastructure and other economic activities – are distributed across systems. And even if the probability is low, they encompass extreme events. This is known as distributional heterogeneity and additivity of extreme events. The global COVID-19 pandemic is an example of a low probability, extreme event. Such systemic risk tools are thus difficult to establish. The approach differs from multi-hazard modelling which relies on “regularity assumptions”. These attempt to make reality less complex and disorderly to ease calculation.

Scenario analyses and stochastic simulations are in use in many applications in the financial sector, including in the insurance industry. Their purpose in the insurance sector is to identify and evaluate risks and to examine possible interconnections and amplifications among them. For example, in the area of natural hazards, they simulate earthquake strength and possible hurricane paths, they define impact scenarios and they analyse potential losses. The findings are then used for pricing, internal guidelines, public policy and management of a portfolio of insured assets.

To focus the attention of analysts and decision makers on the indicators that best capture the character of systemic risk, the impending phase transitions and regime changes of the underlying complex systems, we need new approaches to modelling and understanding of the nature of systemic risks.

If appropriately co-produced, systemic risk modelling will uncover the incentives driving policymaker resistance to going beyond conventional views of risk and those allowing salient early warnings from systemic risk indicators to be ignored or rejected.

The adoption of a multi-agent system in assessments subject to systemic risk is an emerging approach. But it is becoming more and more important, particularly in the context of the COVID-19 pandemic. This approach represents network effects and considers the random nature of human behaviour and (emotional) decision making. A multi-agent system is a loosely coupled network of software agents. These interact to solve problems beyond the individual capacities or knowledge of each problem solver. Certain agents may pose a deliberate threat such as delaying restrictions of movement of populations already experiencing the early stages of exponential cases of infection. People being unaware of the exponential effect of not practicing distancing may pose an unintentional threat. In such cases, systemic risk management requires other agents across all interconnected and interdependent subsystems to take countermeasures to maintain the integrity of the entire system. The application of multi-agent systems research is appropriate and appealing as a way of providing decision friendly scenarios and options to policy makers attempting to manage complex, systemic risk events such as the COVID-19 pandemic.

As is now understood in country after country, systemic risks might be easy to mitigate early. Yet failure (or even intentional ignorance) to appreciate the role of underlying drivers of systemic risk will allow small, manageable risks to grow into major whole-of-society problems. Failed interventions and missed opportunities will increase both economic and human losses. Developing and implementing multi-disciplinary and transcontextual approaches to identify and act on precursor signals and systems anomalies is critical to reduce or avoid discontinuities in critical interdependent complex systems.

To date, assessment and management methodologies for systemic risks are still in early gestation. They are not yet part of the current operations of twenty-first century risk management institutions. Nonetheless, with the onset of the COVID-19 pandemic, there is a growing sense of urgency for a paradigm shift. This is hitting every major twentieth century risk management institution, from governments to insurers. The limitations of the linear constructs of that era are now revealed, with the occurrence and prospect of massive failures across and between systems.

Now is the time to experiment, to explore and invest in developing new approaches, to try to understand the fundamental characteristics of systemic risks. These should be applied, assessed and finessed in managing the COVID-19 pandemic. This may then, by extension, be applied to the potential specificities limiting vulnerabilities of other complex, systemic risks, such as the climate and ecological crises.

Building off this discussion of the characteristics of systemic risk, the next article in this series (#5 of 8) explores the need to improve decision making capabilities, in particular during complex, cascading risk events such as the COVID-19 pandemic. It will also explore opportunities to renovate governance approaches to be able to better focus on the systemic nature of risk.

Cover photo by Chloe Evans on Unsplash
What is the difference between complicated and complex systems… and why is it important in understanding the systemic nature of risk?

What is the difference between complicated and complex systems… and why is it important in understanding the systemic nature of risk?

This is the third in a series of eight articles co-authored by Marc Gordon (@Marc4D_risk), UNDRR and Scott Williams (@Scott42195), building off the chapter on ‘Systemic Risk, the Sendai Framework and the 2030 Agenda’ included in the Global Assessment Report on Disaster Risk Reduction 2019. These articles explore the systemic nature of risk made visible by the COVID-19 global pandemic, what needs to change and how we can make the paradigm shift from managing disasters to managing risks. 

We need to clarify the distinction between a ‘complicated’ and a ‘complex’ system. A complicated system can be (dis-)assembled and understood as the sum of its parts. Just as a car is assembled from thousands of well-understood parts, which when combined allow for simpler and safer driving. Multi-hazard risk models allow for the aggregation of risks into well-behaved, manageable or insurable risk products.

By contrast, a complex system exhibits emergent properties that arise from interactions among its constituent parts in which relational information is of critical importance to integrate the complex system. Understanding a complex system is not enough to know the parts. It is necessary to understand the dynamic nature of the relationships between each of the parts. In a complex system, it is impossible to know all the parts at any point in time. The human body, a city traffic system, or a national public health system are examples of complex systems.

The priorities for action of the Sendai Framework spur a new understanding of risk. They reinforce the obvious value of discerning the true nature and behaviour of systems, rather than thinking of systems as a collection of discrete elements. Risk management models, as well as economic models and related policymaking, have tended to treat systems as complicated. With this method, simplified stylized models are often applied to single entities or particular channels of interaction to first define and then label the risk phenomena. Methods are then negotiated by stakeholders to quantify or otherwise objectively reflect, the risk in question and then to generalize it again to make policy choices.

Most prevailing risk management tools assume that underlying systems are ‘complicated’. Rather than ‘complex’. In fact, these tools are often designed to suppress complexity and uncertainty. This approach is out-dated, and potentially very harmful – not least in the context of the developing COVID-19 pandemic. And is likely to produce results that fail to capture the rising complexity and need to navigate the full topography of risks.

Risk and uncertainty are measures of deviation from ‘normal’. Risk is the part of the unexpected quantified by the calculation of probabilities. Uncertainty is the other part of the unexpected. Where information may exist, it may not be available, not recognized as relevant, or unknowable. In a complex system, which is inherently unpredictable, probabilities for uncertainties cannot be reliably measured in a manner currently acceptable to the global risk management community, including governments. Converting uncertainty into acceptable risk quantities that essentially emanate from the dynamic, relational nature of complex system behaviour is currently very difficult, even impossible. Some uncertainties in any complex system will always remain unmeasurable.

Understanding sensitivities to change and system reverberations is far more important and more challenging in the context of complex systems. Particularly when dealing with very large human, economic and ecological loss and damage across the planet – as is the case with the COVID-19 pandemic. Simulations of such systems show that very small changes can produce almost unnoticeable but still identifiable initial ripples. These are then amplified by non-linear effects and associated path dependencies, causing changes that lead to significant, and potentially irreversible, consequences. This is what the world is experiencing now with the highly infectious COVID-19 outbreak. Country after country impose lockdowns and strict restrictions on human interactions, as individuals do not fully appreciate that a single infected (and possibly asymptomatic) person can provoke tens of thousands of cases of infection within weeks.

Risk is everyone’s business. Almost everyone across the world is starting to understand this, with physical distancing fast becoming the global norm. We must now review how our relationship with behaviour and choice transfers to individual and collective accountability for risk creation and amplification, or for risk reduction. This understanding must translate into action.

Increasing complexity in a networked world of complex, tightly coupled human systems (economic-political-technical-infrastructure-health) within nature can create instability and move beyond control. It may not be possible to understand this ahead of time (that is, ex ante). This inability to understand and manage systemic risk is an important challenge for current risk assessments, including in the context of the response to the COVID-19 pandemic, the wider context of the Sendai Framework and the achievement of the 2030 Agenda on Sustainable Development.

To allow humankind to embark on a development trajectory which is, at the very least, manageable, and at best sustainable and regenerative, consistent with the 2030 Agenda on Sustainable Development, a fundamental rethink and redesign of how to deal with systemic risk is essential; starting with a shift in mindset from ‘complicated’ to ‘complex’.

We must improve our understanding of the interdependencies between system components, including precursor signals and anomalies, systems reverberations, feedback loops and sensitivities to change. Ultimately, the choices made right now in respect of risk and resilience to favour sustaining human health in the face of the COVID-19 pandemic will determine progress towards the goals of the 2030 Agenda and beyond.

The next article in this series will explore some of the recent efforts to better understand the fundamental characteristics of systemic risks and the implications for policy and investment decision making at all scales.

Cover photo by Victor He on Unsplash
Why does understanding the systemic nature of risk matter in the midst of COVID-19?

Why does understanding the systemic nature of risk matter in the midst of COVID-19?

This is the first in a series of eight articles co-authored by Marc Gordon (@Marc4D_risk), UNDRR and Scott Williams (@Scott42195), building off the chapter on ‘Systemic Risk, the Sendai Framework and the 2030 Agenda’ included in the Global Assessment Report on Disaster Risk Reduction 2019. These articles explore the systemic nature of risk made visible by the COVID-19 global pandemic, what needs to change and how we can make the paradigm shift from managing disasters to managing risks. 

There are profound implications in making the shift to a holistic understanding of risk as a dynamic three-dimensional topography that is constantly changing through time. This series of articles will elaborate on current and emerging approaches to assessing and analysing systemic risks; the fundamental characteristics of systemic risks; some of the possible approaches to governance of systemic risks; the importance of building collective intelligence and generating relational information to improve our ability to be sensitive to interdependencies and to ensure responses to systemic risks are informed by a systemic perspective; and finally, introduce the Global Risk Assessment Framework (GRAF), which is an open and collaborative global initiative to help the world better understand and manage the systemic nature of risk as embodied in the COVID-19 pandemic.

The preamble to the 2030 Agenda on Sustainable Development states that the Sustainable Development Goals (SDGs) are integrated and indivisible, balancing the three dimensions of sustainable development: economic, social and environmental. This century is likely to be dominated by the emergence of large-scale dynamic risks, like the COVID-19 global pandemic, that inherently cut across these three dimensions. The Sendai Framework for Disaster Risk Reduction 2015-2030 (the Sendai Framework) reflects the certainty that in an ever more populous, networked and globalizing society, the very nature and scale of risk has changed and continues to change, to such a degree that it surpasses established risk management institutions and approaches. The systemic nature of recent events arising since the initial COVID-19 outbreak at the end of 2019 carries the potential to generate diverse types of damage and destruction simultaneously, even to the life support systems of very large parts of societies and economies. Systemic risk is a critical lens to guide action now, and in the future.

With non-linear changes in hazard intensity and frequency – a reality now increasingly well understood by citizens and policymakers across the world – the imperative for greater ambition and accelerated systemic action is clear. COVID-19 compels new conceptual and analytical approaches to improve understanding and management of risk dynamics and complex, cascading risk drivers at a range of spatial and temporal scales. Understanding the dynamic and interactive nature – of zoonotic pandemics and other systemic risks – requires us to pay attention to the interactions and interdependencies between physical, technological, social and environmental hazards, and a heightened attention to “anthropogenic metabolism”.

Technical communities have used and continue to use models to better “see” risk in the present or near future, and so the view of risk is inherently shaped by the tools used to describe it. Most models have been based on historical data and observations, assuming that the past is areasonable guide to the present and the future. However, the COVID-19 global pandemic has made that assumption obsolete on almost every frontier: by the sheer number of human beings in almost every nation on Earth now infected, and by the dynamic and global connectedness of biological and physical worlds, individuals and communities.

The certainty of near-term non-linear changes calls us to revisit the critical assumption of the relationship between past and future risk. The Sendai Framework adopted almost exactly five years ago, defines a new era for the classification, description and management of risk. It stipulated that the global community must come to terms with a new understanding of the dynamic nature of systemic risks, establish new structures to govern risk in complex, adaptive systems and develop new tools for risk-informed decision-making and investments that allow human societies to live in, and with, uncertainty. The COVID-19 global pandemic has made visible the absence of significant efforts by countries and cities across the world to come to terms with the limitations of a hazard-by-hazard, siloed, fragmented view of risk management. Now is the time for the multi-stakeholder dialogue and action necessary to refine, extend and enhance the ability to understand and manage systemic risks unleashed by COVID-19. But do we have the courage to trust each other? How can we build that trust? What does that look like in an era of physical distancing requiring almost all human interactions to be online?

As has become apparent so far in 2020, today’s environmental, health, food, transportation and financial systems, supply chains, information and communication systems are complex, tightly coupled, fragile and clearly vulnerable. They also create vulnerability on multiple spatial scales (from local to global) and across different timescales (from immediate to weekly to monthly to decadal and beyond). They are challenged by, and are causal drivers of, disruptive influences such as infectious disease outbreaks, food shortages, social unrest, political instability, financial instability and increasing inequality.

The COVID-19 global pandemic is a complex manifestation of systemic risk. It includes elements of surprise and non-linearity. As with all complex risk events, significant underlying drivers – either unknown or underestimated – are exacerbating immediate and prolonged impacts. These include background conditions and contexts related to critical infrastructure placement, known but ignored vulnerabilities within and across key systems (including consumption drivers of high risk practices, for example in animal husbandry and ‘wet’ markets), and lack of redundancy in the quantity of limited systems (such as number of ventilators, number of ICU beds, number of ICU nurses and physicians).

In today’s globalized economic system, networks of communication and trade have generated highly interdependent social, technical and biological systems. These networks are built on, and have built-in, incentives to be highly efficient and to generate economic gains. This narrow focus requires the elimination of contexts and means there are very often undetected fragilities that produce an array of changing systemic risks.

In effect, through global interconnectedness, human civilization has become a “super-organism”, changing the environment from which it evolved, and inducing new hazards with no analogue – such as the COVID-19 global pandemic. Despite technical and analytical capabilities and the vast webs of information about social and Earth systems, human society is increasingly unable to manage the risks which we create at the scale of COVID-19; even understanding is challenging.

Many of those in positions of influence and with decision making authority have also been slow to realize that the degradation of the Earth’s natural systems is becoming a source of large-scale, even existential, threat affecting fragile social systems at local, national, regional and global scales. Far-reaching changes to the structure and function of the Earth’s natural systems represent a growing threat to human health. While global economic integration continues to strengthen resilience to smaller shocks through trade adjustments and other measures, increasingly integrated network structures are creating expanding vulnerabilities to novel systemic risks like COVID-19.

The behaviour of these integrated and interdependent networks defines the quality of life possible for billions of people and shapes the dynamic interactions across the Sendai Framework, the 2030 Agenda, the Paris Agreement, the New Urban Agenda, the Convention on Biological Diversity and the Agenda for Humanity among other major intergovernmental agreements and processes.

Ultimately, the behaviour of these systems of systems determines the contexts of exposure and vulnerability of people, economies, and ecologies at all scales. The regenerative potential of the social and natural systems envisaged in the aligned intergovernmental agendas will be better understood, and progress will be accelerated towards risk-informed sustainable development and regeneration, by incorporating systemic risk and systemic opportunity into the design of policies and investments across all scales.

The next article in this series explores the way systemic risks are embedded in the complex networks of an increasingly interconnected and interdependent world and why current approaches to understanding and managing risks require a fundamental rethink and redesign in the age of systemic risks.

This article was originally posted on Prevention Web.
Cover photo by Macau Photo Agency on Unsplash.