We propose that the reason active learning failed in this pKa prediction task is that all of the molecules are informative. If almost every molecule is informative, then selecting the "best" molecule according to some metric would have nearly the same performance as picking randomly as we observed. There is also some small evidence for this being the case here with our Greedy selection baseline approaches being the only way to consistently beat random selection. The Greedy selection is designed to maximise its fit to a given test set, and we showed that selecting in this way fails to outperform random selection on a withheld test set even when testing on within cluster data (Experiments 3 and 4).