  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.
