The increasing reliance on algorithmic management in digital labour platforms is transforming how tasks are allocated, and worker performance is evaluated. While these systems offer significant efficiency and scalability benefits, they also raise concerns about transparency and worker trust. Regulatory initiatives, such as the European AI Act, aim to address these concerns by mandating human oversight for high-risk AI systems. This study investigates the role and effectiveness of human oversight by exploring its effects on decision performance and worker trust. We devise a controlled economic experiment to analyse outcomes under three distinct management scenarios: human management, algorithmic management, and algorithmic management with human oversight. Preliminary findings indicate that integrating human oversight into algorithmic management can enhance decision performance and foster worker trust. This research contributes to the understanding of hybrid approaches in algorithmic management and offers insights for organizations aiming to balance efficiency with worker well-being within emerging regulatory frameworks.