Project title
OPTIMISING WORKFORCE EFFICIENCY AND EMPLOYEE WELLBEING THROUGH THE IMPLEMENTATION OF PSEUDONYMISATION TECHNIQUES AND AI ALGORITHMS IN THE WORKPLACE.
Project description
The general objective of the project is to establish the theoretical and methodological foundations required to design and apply pseudonymisation techniques and AI algorithms in the analysis of sensitive employee data. It aims to improve the privacy and security of information, as well as to optimise efficiency and wellbeing in the workplace, considering both the pseudonymisation of data and the analysis of workplace wellbeing factors. This project will lay the groundwork for future developments and designs of a human-resources analysis and productivity-monitoring tool in the workplace.
Objectives
- SO1: Carry out an exhaustive analysis of workplace stress, workload and productivity monitoring.
- SO2: Identify and analyse the main factors that contribute to workplace stress and workload in the agri-food and technology industries, as well as the productivity indicators relevant to these organisations.
- SO3: Identify the best practices and strategies for monitoring productivity and managing workplace stress in the agri-food and technology industries.
- SO4: Carry out an exhaustive review of the existing literature in the field of pseudonymisation technology and its application in the workplace.
- SO5: Design and develop machine-learning algorithms and predictive and prescriptive analytics that anticipate potential problems in workflows and improve process efficiency.
- SO6: Evaluate the effectiveness of the AI algorithms designed and developed in terms of accuracy, speed and scalability.
- SO7: Identify and analyse the main challenges and limitations in the design and implementation of pseudonymisation techniques and AI algorithms in the workplace, considering ethical, legal and employee-acceptance aspects.
- SO8: Establish an effective methodology for applying pseudonymisation techniques and AI algorithms in the analysis of sensitive employee data.
Expected outcomes
The project aims to create a tool that, through data pseudonymisation and the use of AI, improves workplace efficiency and wellbeing while respecting employee privacy.
