Article | Open Access
The Changing Face of Accountability in Humanitarianism: Using Artificial Intelligence for Anticipatory Action
Abstract: Over the past two decades, humanitarian conduct has been drifting away from the classical paradigm. This drift is caused by the blurring of boundaries between development aid and humanitarianism and the increasing reliance on digital technologies and data. New humanitarianism, especially in the form of disaster risk reduction, involved government authorities in plans to strengthen their capacity to deal with disasters. Digital humanitarianism now enrolls remote data analytics: GIS capacity, local data and information management experts, and digital volunteers. It harnesses the power of artificial intelligence to strengthen humanitarian agencies and governments’ capacity to anticipate and cope better with crises. In this article, we first trace how the meaning of accountability changed from classical to new and finally to digital humanitarianism. We then describe a recent empirical case of anticipatory humanitarian action in the Philippines. The Red Cross Red Crescent movement designed an artificial intelligence algorithm to trigger the release of funds typically used for humanitarian response in advance of an impending typhoon to start up early actions to mitigate its potential impact. We highlight emerging actors and fora in the accountability relationship of anticipatory humanitarian action as well as the consequences arising from actors’ (mis)conduct. Finally, we reflect on the implications of this new form of algorithmic accountability for classical humanitarianism.
Keywords: algorithm; big data; disaster risk governance; humanitarianism; machine learning; Philippines; politics of disaster; public accountability; predictive analytics
© Marc J. C. van den Homberg, Caroline M. Gevaert, Yola Georgiadou. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.