Project description
A workplace of enhanced efficiency by optimal work sharing between humans and AI/robots
In a rapidly evolving technological landscape, the collaboration between humans and machines poses a pressing challenge to the modern workforce. As artificial intelligence (AI) and robotics become integral to various industries, striking the right balance between human ingenuity and machine efficiency remains elusive. The need for optimal work-sharing methods becomes paramount, spanning from manual labour to intricate decision-making processes. In this context, the EU-funded AI4Work project aims to explore and implement practical solutions for the seamless collaboration between humans and AI/robots. The key challenge lies in developing versatile tools like the sliding work sharing (SWS) approach, adapting the balance between human and machine activities based on situational context and interactions.
Objective
AI4Work will investigate practical methods and tools for optimal sharing of work between humans and AI/robots. AI and robotics are likely to be most powerful means for radical improvement of working conditions in diverse domains, as they can support human operators in diverse tasks starting from difficult and tedious manual labor tasks up to complex decision-making tasks. The vision of the AI4Work project is to improve communication and collaboration between humans, AI and robots, allowing for an improvement of the working conditions within different processes in organisations in several domains in terms of increased efficiency of work, reduction in stress upon employees, increased confidence in decision-making process etc. Due to the high level of uncertainty in modern organisations an appropriate balance between human and machine activities must be found. The key assumption is that to cope with the required flexibility and dynamics, Sliding Work Sharing (SWS), where this balance varies during the operation depending on the situational context, machine-based confidence levels and human interactions, is likely to be the most appropriate for modern organisations. The key challenge of the project is to develop a set of common methods and tools (methodology framework, digital twin service platform, SW building blocks for SWS) that can be applied in diverse sectors and with different AI/robotics services, allowing for an effective experience exchange. The project will make use of living digital twins of working systems as a mean to increase efficiency and trustworthiness of AI/robotics solutions. By this, the project, aiming at improved quality of jobs and creating more decent work for human operators, will contribute to the acceptance of the AI/robots support of work in diverse domains. The project will be driven by six pilots in different sectors: logistics, manufacturing industry, construction, healthcare, education and agriculture.
Fields of science
Keywords
Programme(s)
Funding Scheme
HORIZON-IA - HORIZON Innovation ActionsCoordinator
28359 Bremen
Germany