Abstract
In most astronomy contexts, there are trade-offs among the three competing goals of (1) making as-efficient-as-possible measurements of quantities of interest, (2) creating openings for unanticipated discoveries (especially in real time), and (3) leaving behind public data sets of high legacy value for new investigations. I bring an economic or operational attitude to these questions: These trades could be made well if we could put quantitative measures of utility on various kinds of high-level outcomes. But I will also show that such valuation is impossible to do with precision. I discuss some of the relevant issues in the context of the Sloan Digital Sky Survey collection of cosmology experiments, the Astrometry.net image-recognition system, and ground-based radial-velocity-method exoplanet discovery projects. Expect to hear the phrase "Long-term future discounted free-cash flow" (which I will define).