  In the contemporary landscape of computing education, the ubiquity of
Generative Artificial Intelligence has significantly disrupted traditional
assessment methods, rendering them obsolete and prompting educators to seek
innovative alternatives. This research paper explores the challenges posed by
Generative AI in the assessment domain and the persistent attempts to
circumvent its impact. Despite various efforts to devise workarounds, the
academic community is yet to find a comprehensive solution. Amidst this
struggle, ungrading emerges as a potential yet under-appreciated solution to
the assessment dilemma. Ungrading, a pedagogical approach that involves moving
away from traditional grading systems, has faced resistance due to its
perceived complexity and the reluctance of educators to depart from
conventional assessment practices. However, as the inadequacies of current
assessment methods become increasingly evident in the face of Generative AI,
the time is ripe to reconsider and embrace ungrading.
