Novel digital data sources and tools like machine learning (ML) and artificial intelligence (AI) have the potential to revolutionize data about development and can contribute to monitoring and mitigating humanitarian problems. The potential of applying novel technologies to solving some of humanity's most pressing issues has garnered interest outside the traditional disciplines studying and working on international development. Today, scientific communities in fields like Computational Social Science, Network Science, Complex Systems, Human Computer Interaction, Machine Learning, and the broader AI field are increasingly starting to pay attention to these pressing issues. However, are sophisticated data driven tools ready to be used for solving real-world problems with imperfect data and of staggering complexity? We outline the current state-of-the-art and identify barriers, which need to be surmounted in order for data-driven technologies to become useful in humanitarian and development contexts. We argue that, without organized and purposeful efforts, these new technologies risk at best falling short of promised goals, at worst they can increase inequality, amplify discrimination, and infringe upon human rights.

翻译：新型数字数据源与机器学习（ML）、人工智能（AI）等工具具有革新发展相关数据的潜力，并可助力监测和缓解人道主义问题。应用新兴技术解决人类最紧迫问题的潜力，已引起传统国际发展研究与工作领域之外的广泛关注。如今，计算社会科学、网络科学、复杂系统、人机交互、机器学习及更广泛的人工智能领域的科学界正日益关注这些紧迫议题。然而，这些基于复杂数据的工具是否已准备好用于解决现实世界中数据不完善且复杂度惊人的问题？我们梳理了当前技术发展现状，并识别出阻碍数据驱动技术在人道主义与发展领域发挥效用的关键障碍。我们认为，若无组织、有目的性的努力，这些新技术轻则无法实现承诺目标，重则可能加剧不平等、强化歧视并侵犯人权。