The Limits of Crowdsourcing Crisis Information and The Promise of Advanced Computing

First, I want to express my sincere gratitude to the dozen or so iRevolution readers who recently contacted me. I have indeed not been blogging for the past few weeks but this does not mean I have decided to stop blogging altogether. I’ve simply been ridiculously busy (and still am!). But I truly, truly appreciate the kind encouragement to continue blogging, so thanks again to all of you who wrote in.

Now, despite the (catchy?) title of this blog post, I am not bashing crowd-sourcing or worshipping on the alter of technology. My purpose here is simply to suggest that the crowdsourcing of crisis information is an approach that does not scale very well. I have lost count of the number of humanitarian organizations who said they simply didn’t have hundreds of volunteers available to manually monitor social media and create a live crisis map. Hence my interest in advanced computing solutions.

The past few months at the Qatar Computing Research Institute (QCRI) have made it clear to me that developing and applying advanced computing solutions to address major humanitarian challenges is anything but trivial. I have learned heaps about social computing, machine learning and big data analytics. So I am now more aware of the hurdles but am even more excited than before about the promise that advanced computing holds for the development of next-generation humanitarian technology.

The way forward combines both crowdsourcing and advanced computing. The next generation of humanitarian technologies will take a hybrid approach—at times prioritizing “smart crowdsourcing” and at other times leading with automated algorithms. I shall explain what I mean by smart crowdsourcing in a future post. In the meantime, the video above from my recent talk at TEDxSendai expands on the themes I have just described.

6 responses to “The Limits of Crowdsourcing Crisis Information and The Promise of Advanced Computing

  1. Really like the puzzle piece visual to explain the importance of interdependence in crowdsourcing. Smart crowdsourcing is definitely important- a hybrid approach is a key to the gaps that I am passionate about bridging.

  2. Very interested to see where you are going with QCRI Patrick, I am sure you are working on something big.

    My thinking about crowdsourcing has changed over the years as well, but I have become bit more pessimistic about the idea of increasing technological influence in disaster response — I feel that we have reached a plateau of how much can be done with automation in this area, because of a “social bottleneck” caused by fundamental lack of disaster awareness and preparation.

    In this sense I have a persistent concern about the influence of automation, which often seems to have a dampening effect on community development. Algorithms often seem to ultimately help us avoid the hard long-term work of human-to-human relationships.

    If we imagine disaster response without digital technology — what kind of work might we be able to do without computers? How might we better coordinate with our neighbors? What basic political and development policies might we advocate? To me these questions point to big low-hanging fruit. But for some reason we find it very difficult to engage with our neighbors and politicians. There seem to be very strong behavioral-psychological barriers to community emergency preparation. For example we even find it difficult to prepare simple evacuation plans, even with tools that might help us automate this task.

    At any rate, I would never want to preserve inefficiencies in disaster response and I don’t wish for a techology-less world — I just wonder if more automation will fill the fundamental gaps in civil society.

    And I like your perspective that the databases and maps are a highly-visible “platform for collaboration.” I do still think that technolgy can help get us out of some of these behavioral problems. I absolutely look forward to more innovation in analytic tools for the post-disaster context. Perhaps these tools can put the problem in our face enough that we are actually motivated to fix the social bottleneck. Any thoughts on this connection?

    To be more specific, I suppose my question is: can how might technology help strengthen civil society to *prepare* for future disasters rather than react? Can we design some algorithmic affordance for making lessons “stick” across disasters?

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