Non-Standard-Model parity violation may be occurring in LHC collisions. Any such violation would go unseen, however, as searches are for it are not currently performed. One barrier to searches for parity violation is the lack of modelindependent methods sensitive to all of its forms. We remove this barrier by demonstrating an effective and model-independent way to search for parityviolating physics at the LHC. The method is data-driven and makes no reference to any particular parity-violating model. Instead, it inspects data to construct sensitive parity-odd event variables (using machine learning tools), and uses these variables to test for parity asymmetry in independent data. We demonstrate the efficacy of this method by testing it on data simulated from the Standard Model and from a non-standard parity-violating model. This result enables the possibility of investigating a variety of previously unexplored forms of parity violation in particle physics. * Authors are listed in alphabetical order.1 See later comments that BSM parity-violation models, if they are to have observable signals in the context of this work, must abandon at least one of: (i) locality, (ii) Lorentz-invariance, or (iii) a basis in quantum field theory. Vampires are not visible when mirrored [2] and so presumably the laws of physics describing them derive their parity-violation from the loss of at least one of the above three properties!