  This two part paper argues that seemingly "technical" choices made by
developers of machine-learning based algorithmic tools used to inform decisions
by criminal justice authorities can create serious constitutional dangers,
enhancing the likelihood of abuse of decision-making power and the scope and
magnitude of injustice. Drawing on three algorithmic tools in use, or recently
used, to assess the "risk" posed by individuals to inform how they should be
treated by criminal justice authorities, we integrate insights from data
science and public law scholarship to show how public law principles and more
specific legal duties that are rooted in these principles, are routinely
overlooked in algorithmic tool-building and implementation. We argue that
technical developers must collaborate closely with public law experts to ensure
that if algorithmic decision-support tools are to inform criminal justice
decisions, those tools are configured and implemented in a manner that is
demonstrably compliant with public law principles and doctrine, including
respect for human rights, throughout the tool-building process.
