Co-designing Algorithms for Governance: Ensuring Responsible and Accountable Algorithmic Management of Refugee Camp Supplies

The concept of algorithmic governance expresses that that algorithms fundamentally change the ways in which governments function. However, there is increasing criticism on the use of big data and algorithms to support public sector decision-making and public service delivery. Research has revealed inherent biases and a lack of scrutiny. Public administration scholars have called for more algorithmic transparency and regulation. These are useful, but ex post solutions in which the development of algorithms remains a rather autonomous process that tends to outpace governance. This paper argues that co-design of algorithms between data analysts and practitioners is another means to achieve fair and accountable algorithms that is currently overlooked in the literature. We present a case study of the development of an algorithmic model to estimate the populations of refugee camps to manage the delivery of emergency supplies. This case study demonstrates how in different stages of development of the model – data selection and pre-processing, training of the algorithm and post-processing and adoption – inclusion of knowledge from the field in the design improves responsible and accountable algorithmization. Co-design not only contributes to the accuracy of the model, it also opens the algorithm up to scrutiny and ensures ethical use. We discuss under what conditions co-design of algorithms can achieve these results and offer suggestions on how co-design can be extended for responsible and accountable algorithmic governance.