BRIDGING THE ALGORITHMIC ABYSS: RECONCILING RIGOUR AND RELEVANCE IN THE ERA OF GENERATIVE AI
DOI:
https://doi.org/10.18623/rvd.v23.n3.4664Keywords:
Academic-Practitioner Partnerships, Algorithmic Abyss, Artificial Intelligence, Generative AI, Rigour-Relevance Gap, Scientific IntegrityAbstract
Despite decades of scholarly attention dedicated to closing the rigour-relevance gap—the persistent divide between methodologically sound academic research and its practical utility—this challenge remains a fundamental hurdle in fields striving for both scientific excellence and societal impact. Historically, the academic imperative for rigour often led to inaccessible findings, while the practical need for relevance prioritized speed over robust methodology. However, the rapid emergence of Artificial Intelligence (AI) and Generative AI (GenAI) now introduces a critical, transformative dimension to this long-standing dilemma. While AI offers tools that could dramatically enhance rigour through large-scale analysis, this potential is threatened by an Algorithmic Abyss characterized by Black Box models and data bias that jeopardize methodological integrity. Furthermore, while AI can act as a communication layer to translate findings for practitioners, the pace of AI development is relentlessly faster than traditional publication cycles, creating a severe risk of academic obsolescence. This paper addresses the lack of a contemporary framework to reconcile these imperatives within an environment defined by rapid technological evolution. By investigating the net effect of AI on the rigour-relevance relationship, the study explores how academic-practitioner partnerships must evolve to co-create knowledge and maintain scientific integrity in the algorithmic era.
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