AI4WORK - Human-Centric Digital Twin Approaches to Trustworthy AI and Robotics for Improved Working Conditions

AI4WORK - Human-Centric Digital Twin Approaches to Trustworthy AI and Robotics for Improved Working Conditions​

VISION

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.

INNOVATIONS

Providing a scientifically backed Methodological Framework and set of tools to allow for accurate, traceable, practicable collaboration between humans and AI/robots in different working processes.

Providing tools and a process for organizations to translate ethical principles and regulation into AI governance practices.

Providing Explainable AI (XAI) focusing on systems’ users.

Enhancing working conditions through a comprehensive toolset designed to assist human workers in making informed decisions, planning work activities, and considering potential future scenarios.

Assessing the contribution of various factors to accuracy/reliability of the AI recommendations/actions and to acceptance of these recommendations by users in organisations, in order to achieve optimal balance between operator and machine activities.

Digital Twin Service Platform (DTP) for secure, reliable development of AI-based Sliding Work Sharing (SWS) in non-trivial decision environments.

AI4WORK PILOTS

OAS : Logistics sector

Using the AI4Work architecture, this pilot expects improving working conditions in yard systems by mitigating the pressure put on employees, both those in charge of yard management and lorry drivers and workers at the yard, especially concerning required decisions making at different levels.

IMA : AI in Automation Packaging System

Using the AI4Work architecture, this pilot expects taking advantage of an AI-Powered digital production assistant as a means to fill the knowledge gaps among operators and between operators and different machines.

KUKA : Construction Sector

Using the AI4Work architecture, this pilot expects to increase efficiency and productivity of construction activities, while lowering environmental disruption in districts and minimizing risks to workers’ health and safety.

HH : Healthcare Sector

Using the AI4Work architecture, this pilot expects supporting occupational doctors and psychologists to have a clear view (based on measurements) on the personnel’s physical and mental status.

UPRC + LUT : Education sector

Using the AI4Work architecture, this pilot expects supporting occupational doctors and psychologists to have a clear view (based on measurements) on the Universities personnel’s and Students physical and mental status by means of a remote monitoring system.

UTAD + QDC : Agricultural sector

Using the AI4Work architecture, this pilot expects having human workers work alongside AI/robots, in order to perform key vineyard management tasks – soil management, vineyard monitoring, field phenotyping, etc.

To AI or not to AI?