That's not exactly the aim of lossy compression. Its aim is to reduce data size while introducing as little discernible effect as realistically possible. That usually means optimizing the algorithm such that most of the loss is indiscernible to us, such as in a darkest regions of an image, or the extremely high frequencies in audio -- both areas we don't perceive with too much granularity. Something like spread-spectrum phase distortion may survive compression just fine but still be indiscernible to us. The two are not mutually exclusive.
Suppose you could encode 0.2 bits per second of watermark in a recording without humans being able to discern it. Suppose the compression algorithm did the same thing to encode additional information which is part of the recording, allowing it to achieve higher quality at the same bitrate or the same quality at a lower bitrate.
It's information theory. Either you can encode additional information without impacting the result, in which case the compression algorithm could use it to be more efficient, or you can't. TANSTAAFL.
If there is a known way to cram more data into the same space, compression algorithms are going to want to use it, or something like it which makes use of the same space. Even minor improvements in compression algorithms are extremely valuable at the scale of the internet.
There is an obvious third choice: the gain in compression isn't worth the effort of writing code to detect these non-discernible artifacts.
People are throwing around 0.2 bits/second in this thread. I doubt a company or individual would write code for such a trivial gain, never mind the slowdown in encoding it might cause.
If an audio signal survives a lossy compression algorithm, then there are two possibilities:
- the compression algorithm should be improved, as it preserves some data that isn't important to the human ear
- the signal is audible