Jan 17, 2024
                       

Empowering the Manufacturing Workforce for the Future: Democratisation of Digitalisation and Ethical Integration of AI

Industry 4.0, the advancement of AI technology and software, has made industrial workflows faster and more accurate. It is a revolution in the industry of the future and enters a completely new era.

The Research problem

The integration of AI into the manufacturing sector is rapidly advancing, promising substantial benefits in terms of efficiency, accuracy, and innovation. However, this integration also raises critical concerns regarding job displacement and ethical considerations related to workforce rights and training. Understanding and proactively addressing these challenges are paramount for the future of the manufacturing industry and higher education. The project aims to investigate the potential job displacement due to AI integration and the associated ethical considerations regarding worker rights and skills.

The initiative proposes to establish an international network of experts from various fields, such as AI, manufacturing, ethics, and social responsibility. This collaboration will facilitate a thorough exploration of future employability and skills development, identifying necessary changes in current training and engineering programs. The project aims to bridge the gap between researchers, industry professionals, and educators to address the challenges and offer valuable insights.

This project recognises the critical importance of democratising digital skills, aiming to ensure equitable access and education across diverse communities. By emphasising the democratisation of digital skills, we strive to promote inclusivity and empower individuals from various socio-economic backgrounds to participate meaningfully in the evolving landscape of digital manufacturing, thereby fostering a more inclusive and just society.

Research Design

In this project, we will build an international network of experts in AI, manufacturing, ethics and social responsibility to investigate future employability and skills development, what needs to change in the current training and engineering programmes and what it means for employers and employees. This project connects a diverse group of researchers, industry professionals, and educators, establishing a robust foundation for addressing this gap and offering valuable insights. As an outcome, we will gather international expert’s views from both academia and industry to develop a framework to address the ethical aspects of AI in manufacturing, ensuring transparency, fairness, and accountability in its applications. The results of this project will assist the stakeholders in redesigning their engineering training and programme to upskill the workforce for digital manufacturing, with ethics being at the heart of it. Hence, the future engineering workforce will be able to deal with the complex ethical issues of using digital technologies in particular AI.

Project Objectives

1- Conduct Comprehensive Research and Analysis:

Goal: An in-depth analysis of the current landscape of AI in DTs and its impact on workforce rights, training, and manufacturing processes.

Objective: Investigate existing AI technologies their applications in DTs and evaluate their potential implications on workforce rights and skills.

2- Develop an Ethical Assessment Framework:

Goal: Create a robust framework for evaluating the ethical aspects associated with the implementation of AI in manufacturing processes through DTs.

Objective: Develop a comprehensive ethical assessment framework that addresses potential biases, job displacement, and discrimination concerns related to AI in manufacturing.

3- Enhance Engineering Curriculum and Skill Development:

Goal: To enhance engineering education and training by integrating insights into AI in DTs to equip future engineers with the necessary skills and knowledge.

Objective: Identify key skills required by engineers in the evolving AI-driven manufacturing landscape and recommend curriculum enhancements for engineering education and training.

4- Facilitate International Collaborations and Knowledge Sharing:

Goal: To foster collaboration and knowledge exchange between international academia, industry, and policymakers on the topic of responsible AI applications in DTs.

Objective: Establish a collaborative network by bringing together experts from academia and industry for joint research, knowledge sharing, and future collaborative initiatives.

5- Disseminate Research Findings and Insights:

Goal: To share research outcomes and insights with a broad audience, including scholars, practitioners, policymakers, and the public, for maximum impact.

Objective: Publish peer-reviewed articles, deliver conference presentations, and disseminate findings through accessible channels to ensure wide dissemination and application of research outcomes.

Who's involved

Professor Brent Young
The University of Auckland

Dr Payam Soulatiantork
Dr Mahnaz Arvaneh
The University of Sheffield

Dr Hamed Ahmadi
The University of York