The value-ladenness of computer algorithms is typically framed around issues of epistemic risk. In this article, I examine a deeper sense of value-ladenness: algorithmic methods are not only themselves value-laden but also introduce value into how we reason about their domain of application. I call this domain distortion. In particular, using insights from jurisprudence, I show that the use of recidivism risk assessment algorithms (1) presupposes legal formalism and (2) blurs the distinction between liability assessment and sentencing, which distorts how the domain of criminal punishment is conceived and provides a distinctive avenue for values to enter the legal process.