Canadian Journal of Law and Technology


Student Loans, judicial decision-making, artificial intelligence, hardship requirement


Section 178(1.1) of the Bankruptcy and Insolvency Act allows individuals to apply for discretionary relief from the non-dischargeable nature of student loan debts. Subparagraph (b) of this relief establishes a ‘‘hardship” requirement. The elements for this hardship requirement have been developed and applied by judges in the form of standards. The issue addressed in this paper is whether these standards are applied predictably. Using both statistical analysis and machine learning algorithms, this paper demonstrates that judicial decision-making on the hardship requirement is predictable. This predictability has significant implications. Most importantly it suggests that predictive software could be created for s. 178(1.1) applications that could significantly reduce the uncertainty and cost of these applications.