Today I gave an informal seminar on decision making (in a Bayesian context) in the "Applications of Machine Learning in Astronomy" course led by Coryn Bailer-Jones (MPIA). It forced me to write down what I think about this subject and why I think it is important. I don't think I conveyed, however, why making decisions controlled by an explicit utility matrix is better than just making uncontrolled decisions.
On a related note, Joe Hennawi (MPIA) and I discussed quasar target selection for SDSS-III at length, yesterday and today. Today our subject was hypothesis testing (star vs quasar) using not just colors but also variability. Choosing targets for spectroscopy ought to be a perfect application for decision theory, although the SDSS-III target selection code does not, at present, make use of utilities.