Industry 4.0: Can AI ethics be embedded in the innovation lifecycle?

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Can AI ethics frameworks be embedded in Industry 4.0? Industry 4.0 (I4) refers to the digitization of manufacturing. Smart and autonomous systems that connect multiple machines make use of data to enhance manufacturing processes across the entire lifecycle of products-from concept and design through to use, maintenance and end-of-life. AI is critical to this. It enables computer systems to act autonomously to, for example, diagnose problems and to solve them. The role of humans in shifting. On the one hand, AI displaces the need for human input in decision-making. On the other hand, humans will work in ever closer connection with the AI-led data collecting tools, such as wristbands, data glasses, or other sensor related devices. Given widespread ethical concern regarding AI and human machine interactions, the numbers of ethical frameworks in existence have proliferated in recent years. However, these tend to focus on abstract principles with little detail on how to practically apply them when designing AI or when implementing AI systems at different stages of the innovation lifecycle. Ethical frameworks targeted specifically at I4 tend to focus on employee health and safety, with little consideration of employee voice. The project involves scoping work that will lay the foundation for future in-depth investigations into the impact of AI ethics frameworks on workplace cultures in I4. Our guiding questions for the scoping study are: How do different stakeholders and drivers within I4 networks perceive ethical issues related to AI? To what extent do these perceptions reflect dominant cultures within the I4 innovation lifecycle which impact the implementation of responsible AI? How are stakeholders' perceptions of AI ethics shaped by their own workplace culture and to what extent do they reflect underlying professional, occupational, or broader societal values and norms? Our stakeholders are variously positioned in relation to the innovation lifecycle in I4. This includes teams tasked with taking such innovations through the lifecycle, such as those involved in design, testing and use. It also includes the teams developing the 'stack' of technologies, from hardware, compilers, libraries, services and application development, needed for AI innovations in I4. Aligning our focus with the full range of actors and actions taken in I4 will enable us to better capture the broad-spectrum workplace culture issues involved, including those arising from the interconnection between these actors. The project will identify and form a Community of Interest (CoI) that brings together the range of stakeholders involved in I4. The CoI will center around our project partners, the National Manufacturing Institute Scotland, a government-funded hub that acts as a nexus of these stakeholders, and a data science company, providing the world's most widely used Python distribution, cloud services for industrial AI and data science and professional services for the development of AI/data science applications. In our scoping study report, we will present a set of topics and themes to inform a future programme of research relating to workplace cultures and the challenges for embedding AI ethics in I4 innovation throughout the lifecycle. This report will emerge as part of a dialogue between our project partners, members of the Community of Interest, and the research team.