Legal automation is usually seen with suspicion by lawyers and others. Substituting a law enforcement process with a technological or self-executing enforcement process is inherently problematic and often does not hold those in charge liable or answerable for their actions.
Not all forms of legal automation are substitutive. They can also be supportive. Legal automation is supportive as it aims to reduce human intervention while ensuring that a human with relevant legal expertise is in charge, answerable, and properly informed or equipped for decision-making. Such an approach is particularly useful in the field of compliance where repeated re-interpretations, translations and specifications of high-level legal norms cause friction in the production of executable rules for a variety of business-sponsored use cases.
This whitepaper offers the beginning of a framework to effectively operationalize compliance automation, through the creation of fully-integrated automated policies, and clears the path towards effective and scalable compliance for data analytics. We start the analysis by unpacking the concepts of substitutive and supportive legal automation. We then explain what problems compliance automation can solve, analyzing a couple of common compliance anti-patterns. We finally make some recommendations for the building of fully-integrated automated policies and the enabling of organizations seeking to scale compliance across their data analytics use cases.