Advanced International Journal for Research

E-ISSN: 3048-7641   •   Impact Factor: 9.11

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Volume 7 Issue 3
May-June 2026

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Algorithmic Prognosis and the Ethics of Behavioural Intervention

Author(s) Mr. Srijith Nair
Country India
Abstract This paper critically interrogates the confluence of machine learning-driven predictive attrition modelling and the ethical architectures governing AI-mediated retention interventions within large-scale organisational contexts. Drawing upon a multidisciplinary framework spanning organisational behaviour theory, algorithmic accountability scholarship, employment law jurisprudence, and human capital strategy, the study advances three central arguments. First, that current deployments of predictive attrition systems systematically conflate probabilistic inference with deterministic managerial action, producing what the paper terms 'intervention paradoxes' wherein algorithmically-flagged employees are subjected to behavioural nudges that alter the very conditions upon which predictions were premised. Second, that the normative foundations of informed consent embedded within General Data Protection Regulation (GDPR) frameworks are structurally inadequate to govern the opacity and inductive complexity of ensemble learning and deep neural network architectures deployed in workforce analytics platforms. Third, that the emergent literature on psychological contract theory, when synthesised with algorithmic accountability discourse, provides the most analytically coherent basis for a prescriptive governance framework capable of balancing organisational efficiency imperatives against employee dignity and autonomy rights.
Keywords Predictive attrition modelling; workforce analytics; algorithmic accountability; GDPR compliance; psychological contract theory; AI ethics; human capital management; retention interventions; machine learning; organisational behaviour
Field Business Administration
Published In Volume 7, Issue 3, May-June 2026
Published On 2026-06-04
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E-ISSN 3048-7641
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