Thanks Andrew for queuing up some compelling considerations and discussion in your paper.
I’m curious what other’s thoughts are on vulnerability assessment reports like the REACH Vulnerability and Essential Needs Assessments that were conducted at various refugee settlements in Uganda. These reports attempt to capture differences in settlement and demographic level elements of vulnerability (economic, protection and sector-specific) to identify unmet needs and resolve humanitarian-sector targeting. What aspects of these usually one-off reports can be extended upon to class or stratify vulnerability and what is still missing from reports like these to better target those who are most vulnerable?
Your comment about the inclusion of socio-economic and particularly population datasets to ease risk informed decision making as a more approachable framework for decision making is interesting. In situations where population data is unavailable or noted with high uncertainty, how does that uncertainty reinforce comfort in risk-based decision making or act as a deterrent? In situations where large populations are being resettled to a refugee settlement in a short amount of time and the total population shifts dramatically over short time periods, how does fluctuating population totals influence the use and confidence of risk informed approaches?
Your paper already scopes out the challenges around these very thorny issue so these questions are mostly food for thought. Thanks again for your contribution to the seminar!
Thank you for your comments. To start, I am glad you highlighted uncertainty and comfort as key elements. Below I address your questions, and also pose a few others for the group to consider.
From my experience, including the case studies in the talk, presentation and integration of uncertainty can potentially lead to improvements in various steps in the process from data production, dissemination and integration into decision making - however an improvement is far from a guarantee and it is important to acknowledge that any intervention could lead to unforeseen challenges, such as an increase in the risk sought to be reduced.
Related, there are various elements to note related to communication of uncertainty - including various representations of uncertainty - especially when a decision maker may not have a baseline to peg any level of uncertainty to in relation to data that would add value to their decision making process. (See Padilla et al. 2020 for more on this, especially related to cognition and visualization).
Further, one question to consider is: To what degree is it irresponsible to communicate a level of uncertainty if the decision makers receiving this information may perceive it to be too high, and thus perceive it as untrustworthy and possibly un-actionable?
In addressing this question, one can reflect on the implied responsibility of the data scientist (data producer) to each 1. Understand the level of uncertainty in the data, 2. Understand the degree to which the receiver of that information (either ‘end user’ decision maker, or potentially an intermediary/translator) has the appropriate level of understanding to process/propagate said information and 3. Understand appropriate methods for communicating. While I argue these responsibilities should be, to some degree, present in disaster risk reduction within any context, it is increasingly important in resource (human, time, cognitive, emotional) -scarce and complex settings such as refugee camp management.
To elaborate, #3 reminds me of situations working alongside humanitarian organizations when they are requesting information to make decisions in anticipation of and potentially preparing for a natural hazard driven disaster. As a data developer, in a privileged position of being trusted by decision makers, my words matter, and will likely lead to deviations in actions that would have been taken, or at the least lead to critical resources being used up to consider the information that I share.
Taking a step back, I appreciate your use of ‘comfort’ in the question. While many decision makers, including those in complex settings such as refugee camp management, may seek a sufficient level of comfort (maybe driven by a sense of perceived trust/confidence) in both their final decision as well as within the process to get there, in some contexts a ‘sufficient’ comfort level may not be possible. If so, then does the value of including uncertainty in statements related to DRR increase or decrease?
In summary, as a geophysical scientist working in an applied space, I have found it valuable to reflect on how simply sharing with decision makers that there is in fact uncertainty present in both the geophysical and non-geophysical elements of the ‘disaster’ being considered impacts comfort and trust. Inquiring about uncertainty is unfortunately not part of most standard operating procedures for humanitarian decision makers, however this could be a valuable first step (or even as a step 0) when presented with any data. This does lead to a increasingly non-linear process requiring more discussion (and time demands, and patience, on the data provider side), however ultimately I personally find this to be a small cost in moving towards the overarching, and shared, goal of more appropriate integration of data, especially data with uncertainty, within decision making related to disasters.
The UN OCHA Inter Agency Standing Committee (IASC) recently published guidance, Data Responsibility in Humanitarian Action, related to some of these themes:
Thanks again for the thoughts and comments and glad to elaborate further. Also looking forward to thoughts and reactions from the community.
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Senior Staff Associate Researcher, International Research Institute for Climate and Society &
Faculty Lecturer, M.A. Climate + Society, Earth Institute, Columbia UniversityScience Adviser, Red Cross Red Crescent Climate Centre