Authors: Perrine Hamel, Robert Soden, Karen Barns, David Lallemant, Sneha Krishnan, Dane Carlson, Martin Demaria

Critical perspectives on technical work in the field of disaster risk management and climate adaptation are important: they can help discover “unknown unknowns”. This article presents some lessons learnt in a working group on Responsible Engineering, Science & Technology for Disaster Risk Management.

What’s in a flood?

Floods affect rural and urban communities all around the world – and will increasingly do so given our changing climate. How do we, as a society, attempt to reduce flood risk? Ask an engineer and s/he may work on three components of risk: reducing hazards (why flood water accumulates), reducing exposure (physical assets or populations located in flood-prone areas), and reducing vulnerability (how exposed assets and population might cope with a flood event). 

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One conception of risk common in engineering and disaster risk management

This simple framework is taught in engineering schools around the world and has its merits, perhaps most importantly to provide a starting point to design a flood risk mitigation intervention. Technical experts can map hazard and exposure (where inundation is likely to occur), assess vulnerability based on socio-demographic criteria (e.g., populations without access to early warning systems) then design a more resilient system – one where the intersection of these three dimensions is minimized. 

This sounds good… or does it? As it becomes increasingly clear, applying this framework comes with a lot of implicit decisions. For example, decisions about what counts as hazard and exposure (is 10 cm of water considered a flood?), what qualifies as vulnerability (should people over 65 be considered as vulnerable?), and what do we measure as flood impact (is $ value lost the only meaningful measure?). Importantly, in using this framework, one defines what is considered as risk in a (inherently narrow) quantitative way. How about mapping social networks? Individual stories and contradictory perceptions of floods based on different viewpoints? How about using art to better understand what is at stake, beyond the physical process of inundation?

These questions are starting to emerge in disaster risk management (DRM) and resilience research and practice, where practitioners acknowledge that technical decisions are not neutral but political. Resettlement projects designed on the basis of technical (presumably “value-free”) risk analyses, for example, have received increased attention from the DRM community. Researchers have also challenged traditional risk perceptions by considering and visualizing alternative ways of knowing: for example, in the WhyDAR project researchers and local communities have used qualitative GIS mapping, in the form of geolocalized recordings and social networks, to enrich the definition of flood resilience.

Such participatory mapping approaches can help expand a traditionally narrow understanding of risk. Importantly, they provide legitimacy for new risk reducing interventions to be implemented. Yet, practitioners also need to understand how the approaches they use (e.g. how we design a participatory process) and the tools and data we use (e.g. framing risk as the intersection of hazard, exposure, and vulnerability) shape the answers we give – and ultimately the decisions we influence. 

Not only these decisions have short-term implications for social justice, they also have long term repercussions for development as they may perpetuate inequalities or misallocate long-term investments. Despite some of these socio-technical linkages being now acknowledged, how do we start to discover other linkages, the unknown unknowns of DRM practice?

A critical technical practice for DRM

Scholars in the field of science and technology studies have examined ethical issues related to various epistemological frameworks and in fact there’s a niche area of research, called critical technical practice (CTP), whose work could provide excellent insights for DRM practice.The underlying idea behind CTP is to keep “one foot in critique, one foot in practice”, drawing on critical literature to help one understand the possible implications of their modeling frameworks. (Here we use the term “modeling” in a broad sense, encompassing mental models – the way one perceives and analyses information – and scientific tools – or “formalisms” – aimed at synthesizing and translating knowledge.) 

Originally applied to the field of artificial intelligence, CTP proposes to identify key “metaphors” in a scientific field and uncover what is lost, or marginalized when using these metaphors. In our flood example, the metaphor may be that risk is at the intersection of hazard, exposure, and vulnerability. Using this metaphor, a critical technical practitioner could ask: what if risk was outside this intersection, in a (physical or non-physical) location where the flood hazard doesn’t overlap with exposed assets? This would force him/her to challenge the idea of an asset, or what it means to be exposed, perhaps leading him/her to consider alternative mapping and participatory methods to answer these questions. 

One characteristic of CTP is that it can take myriad forms, as it is defined more by its principles, the path of inquiry and critical examination of one’s field, than its methods. We propose that one way to start applying these principles is to find like-minded people and start scrutinizing a project through different lenses. A non-exhaustive list of methods for such critical work, drawn from the literature on critical thinking, includes: historical research, design methods (e.g. speculative design, design justice), ethnography, journaling, participatory action research, philosophical inquiry.  

Conceptual representation of Critical Technical Practice: There are distinct, sometimes overlapping, communities studying and practicing DRM: one comprising mostly scholars in disaster studies and related fields, the other one comprising engineers, scientists, technicians practicing DRM on the ground. Critical Technical Practices (CTP) have the potential to bridge these interdisciplinary gaps. [Credit: Rachel Ooi]. 

We have experimented with this idea over the summer of 2020. With the COVID-19 pandemic affecting our personal and professional lives, the challenges of starting an online working group were huge. Yet, over four months from May to September 2020, we met with about 20 “critical technical practitioners” in a virtual space to understand how methods that promote self-reflexivity and criticality could be implemented in practice. 

The Responsible Engineering, Science, Technology for Disaster Risk Management experiment

Participants were recruited through an online call. The only requirements for participation were to engage with other participants (in the virtual space Slack) throughout the project, and to have an ongoing DRM project that they could use as a case study. Most participants were freelance consultants and academics. We organized monthly webinars and facilitated the formation of online working group meetings, self-organized around topics of interest, which could be methods (e.g. historical research, participatory approaches, speculative design) or themes (e.g. feminism, nature-based solutions).

Despite the challenges of engagement for participants (including organizers), this experiment taught us three main lessons. First, the loosely structured, interdisciplinary, and voluntary nature of the initiative was conducive to unique conversations. The working group meetings allowed participants to discuss their work and challenges from the lens of specific themes (e.g. environmental history, feminism, landscape architecture), giving them fresh perspectives one rarely gets from collaborators. For some of us, the experiment helped realize that different technical backgrounds do not tend to sort out cultural diversity. Thus, socializing every week on Zoom was key to build the necessary bridges to reach mutual understanding, and a reminder of the value of carving time for deep thinking in the midst of busy professional lives. The working group sessions were also a time to find support in a difficult period when the COVID-19 pandemic disturbed about every aspect of our lives. 

Second, we found that developing a CTP requires commitment and an open mindset. When starting the project, we set on a path with unclear milestones. Almost by definition, the process of discovering the “metaphors” and their implications is largely unknown at the beginning, which requires commitment. A few working groups produced tangible outcomes, such as academic articles (e.g. an annotated bibliography, a draft of a polyvocal journal article), speculative design (a novel flood early warning system highlighting specific perspectives on disaster), and a grant proposal. For the majority of the participants, however, the main outcome was the ability to engage with stimulating conversations, outside their day to day work, with people from various backgrounds. Engaging with such conversation requires one to be open to unclear “rewards”, without a predetermined plan, a mindset that is not usual in engineering and science.

Third, the discussions helped broaden the horizons of disaster imagination. Thinking about challenges collectively, and to face those uncertainties as a group, was found to be a very supportive and safe way to “take that step towards new imaginaries”. Sharing our own disaster imaginaries was already enlightening. Yet, thinking and working around speculative design proved to be an approach as helpful as intriguing, and maybe a great technique to transform our ontological positions the way modelling does as well.

Finally, the concept of CTP itself often seems abstruse at first. Because it relies on different levels of cognitions (the abstract world of ‘critical ideas” and the “practice”), and because most of the existing documentation of CTP remains academic, we found articulating and vulgarizing the concept to be challenging, especially for an online group. Clear examples helped but extrapolating and replicating the approaches in different projects proved challenging. Relatedly, because CTP relies on a range of methods, it was difficult to know beforehand which ones were best suited to each participant. We invited all participants to keep a diary as one simple way to reflect on their progress and mindset. More facilitation and feedback on the diary could help CTP practitioners, and if we were to redo the experiments we would probably ask participants to be more intentional in their goals and methods. 

Based on this experiment, we feel encouraged to develop more avenues to facilitate the adoption of CTP practices in DRM. These could take the form of general education materials in plain language, but also seeds of exploration in traditional curricula (e.g. engineering or urban planning). As technical decisions are not (merely) technical, DRM researchers and practitioners should be better equipped to understand and unravel the implications of their work, and propose alternatives that meet social justice and long term development goals. CTP, originally applied to the field of AI, has a useful history and provides useful resources for practitioners interested in starting this reflective journey.

Last month I spent a week in Nepal setting up an exciting project with collaborators at Kathmandu Living Labs. The project is funded through a “Collaborative Data Innovations for Sustainable Development” award by the World Bank and Global Partnership for Sustainable Development Data. Our proposal focused on better understanding the ways in which disaster impact is currently measured, and how it could be improved to foster more effective and equitable disaster recovery. There are two main aspects to this: (1) improving the statistical accuracy of post-disaster impact assessment using more and better data (e.g. remote-sensing, crowd-sourcing, rapid field surveys) and better statistical modeling; and (2) defining better metrics of disaster-induced vulnerability and need.

We focus on metrics because the specific ways in which we measure the impact of disasters shapes the way that response and recovery are orchestrated. In numerous large-scale disasters including the 2015 earthquake in Nepal, we witnessed that early damage assessments often fall short in properly describing the scale and geographic distribution of damage. More importantly, we saw that the way that disaster impact is measured is in itself problematic.

By describing impact purely as a measure of damage and loss to physical assets (e.g. number of houses and bridges destroyed, etc), this focuses attention (and funding) on communities that have lost the most, but not necessarily those that need the most. Seen another way, measuring impact in terms of counting assets that have been damaged focuses attention away from those who had lost little simply because they had few assets to lose (typically the poorest and most vulnerable). In this way we saw that disasters not only reflect inequality (since the poor tend to live in more precarious conditions), but disaster recovery can often deepen inequality further.

This does not arise from malicious intent from anyone involved, but simply as an outcome of the way we measure and build our databases of disaster impact. So to correct this, we’d like to change the way we measure disaster impacts: shifting from disaster-induced damage to disaster-induced vulnerability and need.

This latest trip was my first time back to Nepal since immediately following the April 2015 earthquake. Following the earthquake I was working with the World Bank to support various Nepali government agencies on developing the early plans for recovery, and organising the housing sector analysis for the Post-Disaster Needs Assessment (PDNA). In part, this new projects aims at addressing some of the limitations of the work I had done then. I won’t attempt to comment on the reconstruction progress three years later. I spent the entire week in Kathmandu while most of the earthquake damage was in the rural areas, and even so one week is much too short to say anything beyond generalizations. So I’ll save that for some future post.

For now I just wanted to share my excitement for this project and working on it with the team at Kathmandu Living Labs. Spending time with the team was quite inspiring. They are a incredibly dynamic group, passionate about improving the society they live in by combining data, people and technology. They are building Open Government platforms to increase effectiveness and transparency of local government; developing citizen-engagement apps to promote citizen-government collaboration and deliberation; mapping hazards and risks of municipalities to promote their resilience; training government surveyors on housing reconstruction monitoring; etc. What better people to partner with on this project?

The project includes other eminent collaborators. Led by the Earth Observatory of Singapore (my academic home), the project also brings together engineers from the Stanford Urban Resilience Initiative, disaster informatics experts from GFDRR (Robert Soden), data scientists from the World Bank Big Data Program, humanitarian data specialists from the Humanitarian OpenStreetMap Team, and remote sensing experts from NASA-JPL.

Stay tuned for more as the project evolves.