Funding Source: SNF

Over the years, there has been a growing concern about the impact of technology on employee well-being, especially with the rise of technological supervision, which can lead to physical and mental exhaustion among employees. The COVID-19 pandemic and the increase in remote work have further highlighted these issues. To tackle these challenges, the TRUST-ME project aims to address the complex relationship between employee productivity, job satisfaction, and well-being in the modern workplace. The project leverages recent developments in sensing technology and advanced AI algorithms to create personalized digital tools for monitoring well-being and boosting productivity. By combining expertise in sensing technology, privacy, user experience design, and explainable AI, the project focuses on multimodal monitoring and modeling of job satisfaction and productivity, as well as secure and private AI for productivity assessment. The project’s approach involves using unobtrusive workplace sensors for knowledge workers and implementing privacy-preserving techniques, such as federated learning. The goal is to provide transparent and actionable insights to both employees and employers without compromising privacy. A validation study with academic knowledge workers will contribute to refining the TRUST-ME approach and the AI-driven dashboard presenting the outputs. Ultimately, the project aims to improve job satisfaction and productivity while upholding ethical values like privacy and autonomy.