BUG: Fix bad datetime64[ns] array to str dtype conversion in Series ctor which causes odd read_csv behaviour
- [x] closes #57512
- [x] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [x] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [x] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [x] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.

Dates were being converted to nanosecond timestamps by numpy's `ndarray.astype` when converting an `M8[ns]` array to `object` during `ensure_string_array`. By wrapping the array with a `DatetimeArray` EA, we make sure that the dates get nicely converted in `ensure_string_array`.

Also added a check to `ensure_string_array` since it was converting na values disregarding the `convert_na_value` argument which caused missing dates to come out as `NaN` instead of `NaT`.
Thanks for the pull request, but it appears to have gone stale. If interested in continuing, please merge in the main branch, address any review comments and/or failing tests, and we can reopen.