  We discuss our insights into interpretable artificial-intelligence (AI)
models, and how they are essential in the context of developing ethical AI
systems, as well as data-driven solutions compliant with the Sustainable
Development Goals (SDGs). We highlight the potential of extracting
truly-interpretable models from deep-learning methods, for instance via
symbolic models obtained through inductive biases, to ensure a sustainable
development of AI.
