Data Science and Ethics Group

Data Science and Ethics Group

Jul 22 2019 Resource

Group Summary
Building on recent work and attention on ethical humanitarian data science, the Data Science and Ethics Group (hence referred as “the group”) gathers key actors involved in data science and ethics to address the juncture between principles and practice. This group, initiated in June 2018, aims to bring key theoretical and practical actors to address the ethical issues behind humanitarian data science, and to establish practical frameworks with both technical and ethical considerations for the application of data science methods for humanitarian purposes.
This group was established to focus on the more practical issues related to the application and communication of advanced data science methods and better understanding the unidentified and unintended risks that may come with the good intended application of these methods that may go awry. Even though, there are significant knowledge gaps regarding the international community’s understanding of the nature and characteristics of threats, harms, and risks at the intersection of cyberspace and conventional humanitarian emergency situations, this is not the main focus of this group.
 
Background
With increasing amounts of humanitarian data collected, the efforts for standard compliance, openness and public access, is excellent progress for the humanitarian community. It enables greater interoperability between datasets allowing for data minimization, better and more efficient information management and enhanced transparency, while creating an environment conducive for more progressive data science applications for humanitarian purposes. 
However, with this amplified data availability, access, interoperability, and quality comes heightened risks and potentially greater unintended consequences. Therefore, it is imperative that humanitarian stakeholders who collect, process, and disseminate data to consider and examine these potential dangers associated with using advanced data science methods to guide decision making.
As identified in a recently published UNHCR article , in general, humanitarian and data experts do not speak the same language; they do not share a common vocabulary or context, and often cannot align their goals. Also, one of the identified factors contributing to the slow institutional uptake of big data and advance analytics within the humanitarian sector is a lack of knowledge and capacity to apply these instruments in operational settings . Therefore, by including operational service delivery actors in the group, as well as data scientists, data collectors, and ethic advocates, it should allow for a grounded discussion whilst allowing innovative ideas to still be shared among stakeholders whilst ensuring that potential risks stemming from these ideas are considered and sufficiently analysed. 

Objectives
To coordinate and collaboratively identify the potential benefits and risks of advanced data science applications for the humanitarian sector and to establish and strengthen existing ethical frameworks and standards behind the use of these methods specific for humanitarian purposes.

Documents

Meeting 3 Data Science and Ethics Summary Notes 12022019

Meeting 2 Data Science and Ethics Summary Notes 07082018

Meeting 1 Data Science and Ethics Summary Notes 31072018

Data driven humanitarian response


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