This chapter discusses the ethical aspects related to inclusion, bias and privacy in New information technology, data science and digital data, and explores how they impact on evaluation and programmatic decision-making in the area of development. Biases that intervene in the course of using information and communication technologies in general and data sciences in particular could be tackled using social as well as technological measures. In terms of using technology to combat biases in datasets and machine learning models, new tools such as IBM AI Fairness 360 are being introduced. Such tools can check for biases at several points along the machine learning pipeline, using the appropriate bias metric for their circumstances. As development agencies incorporate more digital tools and data processes into their work, data ownership, protection, privacy and security have come to the forefront. Even if development agencies were allowed to access the “black box” algorithms, they lack the skills to examine, assess and question them.