نبذة مختصرة : Strong sustanbility demands that decisions on climate mitigation be guided by a climate target and that compliance with the target be the primary concern prior to saving mitigation cost. Climate targets have often been formulated as temperature targets and for the case of uncertainty about climate sensitivity as probability targets. However, for the realistic case that we learn about climate sensitivity over the decision-making period, it is not clear how strong sustainability would consistently derive decisions on climate mitigation before and after leraning. We systematically structure the normative debate on adequate decision criteria for strong sustainability under uncertainty and learning along the lines of the von-Neumann-Morgenstern axioms of expected utility theory. We distinguish between a strict and a pragmatic-probabilistic interpretation of strong sustainability. We find that both interpretations break with the continuity axiom, while the pragmatic-proabilistic interpretation violates, in addition, the independence axiom. We discuss different possible decision criteria for strong sustainability under learning about climate sensitivity, among them a new time-recursive cost-effectiveness analysis. This probabilistic target formulation for the case of learning leads to non-trivial results if a "safe" probability level can be reached at zero mitigation cost in at least one learning scenario in which climate sensitivity turns out to be sufficiently low. This may occur if learning happens rather late and major parts of the low-carbon transformation have been achieved already before learning. Overall, our decision-analytic review helps to better understand the position of strong sustainaibility and its potential inconsistencies. We would encourage future work to use the methods of decision theory for structuring normative positions in the sustainability discourse.
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