This post won’t really include much about Davies & Wagner 2013, expect for one line:
“[T]he criteria for searching a database should be primarily tied to cost rather than plausibility. If it costs little to scan data for signs of intelligent manipulation, little is lost in doing so, even though the probability of detecting alien technology at work may be exceedingly low.”
This is remarkably well said, and I completely agree. A huge argument against SETI is that nothing has been found yet, so it’s a waste to keep looking. While this argument is fallacious in itself, it can quite easily be rebutted with the above statement. If searching requires little time/money/effort, than there is no waste.
One great thing about SETI is that it (normally) does not require its own dataset. Astronomers are already observing interesting targets with different instruments at different wavelengths, either to catalog them or to look for anomalies. Any anomalies discovered will probably be scrutinized, so why not borrow the data and look at it from a SETI point of view? There are currently many algorithms searching datasets now (a solution to our big data problems), so altering these algorithms just slightly to look for expected ETI alterations or just anomalies takes minimal effort and, if the algorithm is light, has minimal computation costs. Such searches could even just piggyback off of current searches (flag anomalies) such that there is no additional computational costs.
Davies and Wagner specifically motivate looking through all of the wonderful data we have on the Moon, noting that because the resolution is so great, many artifacts/trash would be visible (assuming they aren’t buried in regolith). Personally I think that looking at these by eye is not the way to go, and that the search should be automated. It would also be neat if some machine learning were applied to find such artifacts, but this would require some kind of training set and therefore not only more work/time/money but also some kind of assumptions about the sizes and shapes of alien artifacts.
I think it would be really neat if someone were to dedicate some time (probably unpaid =/) to developing algorithms for finding anomalies in all of the (mostly planetary) datasets we have (images, transits, gravity anomalies, all-sky surveys in every wavelength). This would not take much, and the algorithms could just run in the background. Follow-ups for any flagged anomalies would include compilation of all possible data and either human or artificial analysis to somehow rank how anomalous the data are. This would simply be really awesome.