By Rachel Finn, 22 June 2017
The use of data analytics, machine learning and data visualisation for quality control and predictive maintenance within manufacturing settings is not an obvious space to consider research ethics. Nevertheless, such projects often use employees or members of the public to gather requirements, test systems and evaluate new products and technologies. This is particularly necessary as the manufacturing sector needs to define new ways of working with data and new skills, expertise and work practices for employees where factories are transitioning to industry 4.0. In the context of smart manufacturing, employees must acquire sufficient skills to enable them to work with data, interpret data visualisations and engage with new complex capabilities of, and additions to, manufacturing equipment (e.g., sensors). Unlike the blue-collar employees of the previous generation, contemporary factory workers increasingly need to become data literate. However, these transitions can be contentious, and research projects using employees to test new data-driven industry 4.0 systems may introduce tensions within workplaces that have real-world consequences for employees.
In the context of our EU-funded PROTEUS project (Scalable Online Machine Learning for Predictive Analytics and Real-time Interactive Visualisation), Trilateral has constructed a research ethics protocol for precisely this purpose. PROTEUS uses data analytics, machine learning and data visualisation to improve production processes within the steel manufacturing industry. The research ethics protocol constructed by Trilateral provides templates to explain the project to employee research participants and ensure that they understand the implications of participating in the research. This is particularly important as many employees are unfamiliar with applied research methodologies and practices. Some of the key issues that are covered in the ethics protocol are issues around the voluntary nature of the research and the potential side-effects of unfavourable feedback on the utility of new systems for employees, managers and researchers. For example, how can PROTEUS make sure that employee participation is truly voluntary, and not mandated by supervisors and managers? How can the project protect employees who give negative feedback about the system or employees who don’t have the skills required to use the system or interpret the outputs? Could the research results be used to identify under-skilled employees? The research ethics protocol developed by Trilateral ensures that employee participants do not experience any negative effects from participating in the research. It also provides good practice guidelines for industry representatives and technology developers not accustomed to considering these questions in the context of their development projects.
For more information on PROTEUS, visit the project website: https://www.proteus-bigdata.com
For more information on our research ethics service, visit our services page: http://site.trilateralresearch.co.uk/about-us-trilateral-research/services/
For any other information, contact: Rachel.email@example.com