Anticipatory life-cycle assessment for responsible research and innovation

Ben A. Wender, Rider W. Foley, Troy A. Hottle, Jathan Sadowski, Valentina Prado, Daniel A. Eisenberg, Lise Laurin, Thomas P. Seager

Journal of Responsible Innovation · 2014 · 136 citations · 27 references

Concepts

TL;DR

Responsible research and innovation seeks to steer innovation toward beneficial social and environmental outcomes, yet existing life‑cycle assessment tools are largely retrospective and under‑engage stakeholders, limiting their usefulness for emerging technologies. This paper proposes anticipatory life‑cycle assessment, a non‑predictive, uncertainty‑inclusive approach, to evaluate future environmental burdens of emerging technologies. By pinpointing key uncertainties and involving R&D decision‑makers, anticipatory LCA can generate alternative research agendas and serve as a practical tool for environmental responsible research and innovation.

Abstract

The goal of guiding innovation toward beneficial social and environmental outcomes – referred to in the growing literature as responsible research and innovation (RRI) – is intuitively worthwhile but lacks practicable tools for implementation. One potentially useful tool is life-cycle assessment (LCA), which is a comprehensive framework used to evaluate the environmental impacts of products, processes, and technologies. However, LCA ineffectively promotes RRI for at least two reasons: (1) Codified approaches to LCA are largely retrospective, relying heavily on data collected from mature industries with existing supply chains and (2) LCA underemphasizes the importance of stakeholder engagement to inform critical modeling decisions which diminishes the social credibility and relevance of results. LCA researchers have made piecemeal advances that address these shortcomings, yet there is no consensus regarding how to advance LCA to support RRI of emerging technologies. This paper advocates for development of anticipatory LCA as non-predictive and inclusive of uncertainty, which can be used to explore both reasonable and extreme-case scenarios of future environmental burdens associated with an emerging technology. By identifying the most relevant uncertainties and engaging research and development decision-makers, such anticipatory methods can generate alternative research agenda and provide a practicable tool to promote environmental RRI.

References

27