Can we decrease the costs of database curation by crowd-sourcing curation work or by offloading curation to publication authors? This perspective considers the significant experience accumulated by the bioinformatics community with these two alternatives to professional curation in the last 20 years; that experience should be carefully considered when formulating new strategies for biological databases. The vast weight of empirical evidence to date suggests that crowd-sourced curation is not a successful model for biological databases. Multiple approaches to crowd-sourced curation have been attempted by multiple groups, and extremely low participation rates by 'the crowd' are the overwhelming outcome. The author-curation model shows more promise for boosting curator efficiency. However, its limitations include that the quality of author-submitted annotations is uncertain, the response rate is low (but significant), and to date author curation has involved relatively simple forms of annotation involving one or a few types of data. Furthermore, shifting curation to authors may simply redistribute costs rather than decreasing costs; author curation may in fact increase costs because of the overhead involved in having every curating author learn what professional curators know: curation conventions, curation software and curation procedures.