We have compiled a list of resources which are relevant and helpful for ethical humanitarian data science. If you have any further resources to add, please get in touch.

Humanitarian Data Science Ethics encompasses four distinct yet  complementing topics: Humanitarian Principles and Standards, Data Responsibility, Humanitarian Innovation and AI Ethics and Principles.

In our timeline below, we have documented the main resources relevant for each of these themes.

Blue: Humanitarian Principles
Green: Data Responsibility Guidelines
Yellow: Humanitarian Innovation
Pink: AI Ethics and Guidelines
Purple: Other/combination

DSEG Timeline 6.png


Harvard Berkman Klein Center for Internet and Society

This white paper and its associated data visualization compare the contents of thirty-six prominent AI principles documents side-by-side.

Algorithm Watch

Algorithm Watch have attempted to map the landscape of ethical AI frameworks. They warn that the list is not (and cannot be) complete, but is a good starting point.

Alan Turing Institute

This report is the most comprehensive guidance on the topic of AI ethics and safety in the public sector to date. It identifies the potential harms caused by AI systems and proposes concrete, operationalisable measures to counteract them.

High-Level Expert Group on Artificial Intelligence (European Commission)

These Guidelines put forward a human-centric approach on AI and list 7 key requirements that AI systems should meet in order to be trustworthy.


Elhra - Humanitarian Innovation Fund

The Humanitarian Innovation Guide is a growing online resource to help individuals and organisations find their starting point and navigate the humanitarian innovation journey. It is particularly helpful for navigating the "will AI help with my problem?" question.

UNDP and Global Pulse

This guide provides practical guidance in designing a data innovation project. It is designed for development practitioners and encourages partnership with external data experts


International Committee of the Red Cross

This handbook seeks to raise awareness and assist humanitarian organizations in ensuring that they comply with personal data protection standards when carrying out humanitarian activities, by providing specific guidance on the interpretation of data protection principles for humanitarian action, particularly when new technologies are employed. It does not seek to replace organizations’ own data protection guidelines, nor data protection laws.

International Organisation for Migration

This manual is in three parts: the first part outlines the IOM data protection principles as informed by relevant international standards; the second part includes comprehensive guidelines on each principle, consideration boxes and practical examples; and the third part provides generic templates and checklists to ensure that data protection is taken into account when collecting and processing personal data. Although the content of this publication was developed for IOM use, it can be used as a resource tool by other organizations engaging in similar operations.

The Centre for Humanitarian Data, UN-OCHA

These guidelines offer a set of principles, processes and tools that support the safe, ethical and effective management of data in humanitarian response. They are designed for OCHA staff but can be used beyond. They concentrate on sensitive yet non-personal data.


Humanitarian Charter and Minimum Standards in Humanitarian Response

The Sphere Handbook is the oldest initiative in the field of humanitarian standards. With a clear, rights-based framework, the Handbook builds on the legal and ethical foundations of humanitarianism with pragmatic guidance, global good practice and compiled evidence to support humanitarian staff wherever they work.


The Core Humanitarian Standard on Quality and Accountability sets out Nine Commitments that organisations and individuals involved in humanitarian response can use to improve the quality and effectiveness of the assistance they provide.

International Committee of the Red Cross

This code seeks to safeguard high standards of behaviour and maintain independence and effectiveness in disaster relief.



This document aims to inform and empower those who may have limited technical experience as they navigate an emerging ML/AI landscape in developing countries.

The International Development Innovation Alliance

This document is designed to provide an accessible and concise entry point for actors working in international development who are interested in how Artificial Intelligence (AI) technologies can or will impact their work.


IBM Research

This extensible open source toolkit can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle. Containing over 70 fairness metrics and 10 state-of-the-art bias mitigation algorithms developed by the research community, it is designed to translate algorithmic research from the lab into the actual practice of domains as wide-ranging as finance, human capital management, healthcare, and education.


Nethope Solutions Center

This toolkit includes ‘AI Workshop for Nonprofits’ Facilitators Guide and Master Deck, and AI Suitability Framework.
The workshop and accompanying materials are designed to provide participants with an introductory overview of AI / ML capabilities and how to evaluate suitability of AI/ML for their programs and projects.

Humanitarian Data Science and Ethics Group.