The two-lane road to hell is paved with good intentions: why an all-or-none approach to generative AI, integrity, and assessment is insupportable

Abstract

A ‘two-lane’ (All-or-None) approach to the use of generative artificial intelligence (genAI) is the idea that there should be two categories of assessments in higher education: Lane 1/None: where the use of genAI is prohibited, and Lane 2/All: where any use of genAI is permitted. This idea has been thoughtfully detailed and continues to be debated. Although this idea is generally well-intentioned, in this comment piece I argue that, if implemented, it will promote an impoverished approach to education and educational assessment. One argument often invoked in favour of an All-or-None approach is that genAI use may sometimes be undetectable. Contract cheating (e.g., students outsourcing assessments to ghostwriters) is sometimes undetectable, yet an argument that there should be an All-or-None approach permitting contract cheating in some assessments is clearly absurd. An All-or-None approach to genAI and assessment is also absurd. A middle lane, where genAI use in assessments is allowed with some limitations, is essential.

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