Addressing ethical challenges in geospatial data science and AI is important to ensure that research used to inform policy- and decision-making is fair, beneficial, minimally risky, and accountable, to affected communities; to build and maintain public trust in geospatial data science and AI; and to ensure compliance with relevant regulations, standards, and journal and funding agency policies.

This hands-on session will allow you to explore tools from the I-GUIDE Data Ethics Toolkit, designed to make geospatial data science and AI research more ethical, transparent, and reproducible. Tools exist for generating model and dataset documentation, documenting uncertainty, and project management. You will be guided how to identify whether your research is high-, medium- or low-risk, and how to choose and use tools appropriate to the level of risk.