The integration of humans-in-the-loop for decision-making in the Industrial Internet of Things (IIoT) has intensified workers’ interaction with complex information systems. Tracking workers’ mental workload, comparable to anomaly detection in IIoT, raises ethical questions requiring careful regulation. We contribute to mitigating these ethical risks with design principles drawing on responsibility-oriented ethical considerations, emphasizing precaution and the protection of long-term human well-being. Following design science research, design principles were derived based on literature to offer long-term ethical guidance rather than short-term solutions. While studies acknowledge ethical challenges related to workload monitoring, the practical problem remains how such insights can be translated into ethically responsible system design. The paper consolidates ethical concerns into actionable design principles fostering continuous ethical reflection throughout technology development. The proposed design principles were evaluated through qualitative interviews with practitioners to ensure relevance and incorporate their perspectives into refinement. The principles provide a foundation for developing ethically informed decision-making in IIoT, helping organizations align technological innovation with human-centric values.