Some of the most pressing issues facing the world are of direct relevance to AI policy, including mobility, finance, and health care. Implementing policies requires not only principles but also trade-offs, which is what makes concrete policies hard to develop. For instance, privacy is an important AI principle, but protecting privacy may affect accuracy. If this is in health care and the cost is lost lives, how does one make these trade-offs? Other trade-offs may go against other important collective concerns like climate change, for example when new computing techniques imply a growing carbon footprint. Also, two AI principles may conflict against each other, for example when in some specific contexts more explainable models may result in more unfair algorithmic classification. Who decides what is the right choice here, and how? Our task forces will zero in on exactly these kinds of questions.