[Dissertation summary] When performing intertemporal cost-benefit analyses of policies, both in terms of climate change and other long-term problems, the discounting problem becomes critical. The question is how to weight intertemporal costs and benefits to generate present value equivalents. This thesis argues that those best placed to answer the discounting problem are domain experts, not moral philosophers or the public at large. It does this by arguing that the discounting problem is a special case of an interesting class of problems, (...) those which are both what I call morally complex and quantitative. [Open access]. (shrink)

When probability discounting (or probability weighting), one multiplies the value of an outcome by one's subjective probability that the outcome will obtain in decision-making. The broader import of defending probability discounting is to help justify cost-benefit analyses in contexts such as climate change. This chapter defends probability discounting under risk both negatively, from arguments by Simon Caney (2008, 2009), and with a new positive argument. First, in responding to Caney, I argue that small costs and benefits need to be evaluated, (...) and that viewing practices at the social level is too coarse-grained. Second, I argue for probability discounting using a distinction between causal responsibility and moral responsibility. Moral responsibility can be cashed out in terms of blameworthiness and praiseworthiness, while causal responsibility obtains in full for any effect which is part of a causal chain linked to one's act. With this distinction in hand, unlike causal responsibility, moral responsibility can be seen as coming in degrees. My argument is, given that we can limit our deliberation and consideration to that which we are morally responsible for and that our moral responsibility for outcomes is limited by our subjective probabilities, our subjective probabilities can ground probability discounting. (shrink)