EXPLORING TOOLS FOR RESPONSIBLE INNOVATION IN AN INDUSTRIAL SETTING

Policies for Responsible Innovation (RI) seek to reflexively align science and engineering choices and activities with societal goals and values. While numerous studies have explored the possibility and utility of RI within academic research settings—where cultures of curiosity and experimentation often support reflection on societal considerations—few have sought to do so in more economically-driven corporate and industrial settings. This study will examine the societal dimensions of the corporate manufacturing system in order to determine whether reflection on these dimensions by corporate scientists can support RI while simultaneously advancing economic output and productivity. I will first compare the established RI tool of Socio-Technical Integration Research (STIR), which has been used to support RI in over three-dozen laboratories, with an engineering methodology used in the manufacturing sector known as Lean Principles, and which primarily focuses on the waste and cost entities in an entire supply chain. After developing a novel approach based on these two tools, I will assess its use by corporate scientists in terms of its residual impact on human capital. Human capital- or performance- is one of the most inconsistent components driving the supply chain. Using materiality assessments and corporate responsibility reports, the study will also benchmark the major values and components that resonate in an industrial manufacturing culture. The outcome of the study will showcase how and where RI principles of reflexivity and responsiveness can enhance alignment with societal values while at the same time making sustained improvement in manufacturing systems. RI empowers the human capital to proactively address external and internal factors limiting the system. RI has the potential to positively change the corporate direction. Where the RI principles are effective will vary for industries and by the location in the supply chain. Unlocking the potential from within the system requires a thorough evaluation of where to implement RI.