Periodic Reporting for period 1 - SEISMEC (Supporting European Industry Success Maximization through Empowerment Centred development)
Période du rapport: 2024-01-01 au 2025-06-30
SEISMEC will demonstrate an empowered, human-centred and ethical development of digital and industrial technologies in 17 pilots from 14 countries across 14 industrial ecosystems. It will do so through a two-way engagement in the development of technologies, empowering end-users and workers, and supporting social innovation. This human-centred approach to technology development is one aligned with European social and ethical values.
The SEISMEC pilots are representative of all sectors and company sizes, and most European countries and worker roles. Every industrial enterprise in Europe will be able to see some aspect of their activity reflected in SEISMEC pilots and will be able to learn from the project’s outputs.
- SEISMEC Framework: conceptualises human-centric industrial transformation at individual, organisational, and industrial levels. The framework utilises "CAPS empowerment factors" (Creativity, Collaboration, Autonomy, Automation, Productivity, Privacy, Safety, and Job Satisfaction) as diagnostic tool to assess human-centrism and guide technology development. A first version of the framework was developed.
- Development of Advanced Human-Centric Tools: creation and testing of tools and procedures for advanced technologies. Key areas include Explainable AI (XAI), privacy-preserving models and methods for real-time worker feedback, and tools and guidelines for human-centric interface redesign. To do this, the project developed 1) design guidelines that act as a bridge between the theoretical foundations and the operational realities of the SEISMEC pilots; 2) a research protocol and assessment instruments for measuring human-centric objectives and worker empowerment; 3) A methodology for worker participation to ensure that technology solutions are co-designed and refined with workers. The research partners have worked with the pilots to define the focus of collaboration.
- Pilot-Driven Implementation: SEISMEC solutions are tested and refined in 17 pilots across diverse real-world industrial and service environments in Europe. The pilots follow a three-phase research process that strongly emphasizes worker participation and co-design in the development and implementation of new technologies. All pilots have started designing their interventions.
- Cross-Pilot Analysis and Evidence-Based Recommendations: WP4 conducts transversal analyses across pilots to evaluate performance against human-centric objectives. This includes examining themes like cybersecurity, privacy, human trust and understanding, inclusion, and in-work learning and skills development. The first periodic report focused on development of definitions, methodologies, and instruments to conduct the analyses and on identifying early trends and opportunities for synergy between pilots.
SEISMEC developed human-centric frameworks and methodologies. The SEISMEC framework enables human-centric industrial transformation introducing CAPS empowerment factors as a novel diagnostic tool to balance worker empowerment with economic competitiveness. Solution Directions form the conceptual core of practical Design Guidelines that provide tools, methodological justifications, and pilot-based examples for implementing human-centric technology. An AGILE guidebook for iterative and collaborative worker participation provides the methodology to engage workers in the co-design and implementation of workplace technologies.
SEISMEC is developing tailored XAI methods and tools for specific industrial use cases, such as object detection for airport safety, concept-based explainability for generative AI training, and explainable scheduling systems. These tools are designed to enhance transparency, user trust, and acceptance by making AI reasoning clearer and more understandable for workers.
SEISMEC introduces new privacy-preserving models for capturing worker feedback using wearable and vision-based sensors. Crucially, data collection is initiated and controlled by the workers themselves, with on-edge processing and differential privacy techniques. This approach has been successfully applied e.g. in detecting risky behaviours in construction.
The project formulates evidence-based recommendations for stakeholders and policymakers, with plans to propose new regulatory frameworks that better integrate human-centric principles into industrial policy.