I mean, nobody expects the engineers to manually read through everything, but if the quality of the input text is significant for the quality of the autocorrect (or whatever other application you're using machine learning with), you kind of have to make sure the input is pretty good... You could for example choose datasets which is expected to contain mostly correct grammar and spelling (such as Wikipedia, books, etc.) rather than datasets which is expected to contain mostly incorrect grammar and spelling.

Or don't use a machine learning model. I honestly don't care, just don't automatically turn a correct "its" into an incorrect "it's".