Responsible epistemic innovation: How combatting epistemic injustice advances responsible innovation (and vice versa)

ABSTRACT

Epistemic resources, including concepts, categories, and metrics, are invented regularly. Yet this process of epistemic innovation has not been recognized in responsible innovation (RI) scholarship. I argue that it should be: epistemic innovation can foster central goals of RI, including anticipatory governance and alignment with the goal of epistemic justice. An RI framework can help direct and evaluate epistemic innovation, as shown in three examples of epistemic innovation in communities adjacent to oil refineries: initiated without RI in mind, not all were well aligned with epistemic justice and each would have been strengthened by a stronger commitment to deliberation and foresight. These examples highlight challenges to achieving responsible epistemic innovation: having innovation be mistaken for error; coalescing experience and data into intelligible epistemic resources; and structuring inclusive deliberation. These challenges can be addressed by developing new forms of material deliberation and including resources for responsible epistemic innovation in RI policy.

KEYWORDS:

• Epistemic resources
• epistemic injustice
• environmental regulation
• environmental justice
• air monitoring

Acknowledgments

My thanks to all of the fenceline community residents and environmental justice activists who have spoken to me over the years about their experiences with air pollution, air monitoring, and regulatory characterizations of air quality. I am indebted to them for their insight. I am also deeply grateful to all of the participants in the Meaning from Monitoring project, which gave rise to the Toxic Soup Index. Dawn Nafus and Amos Akinola deserve special thanks for their work. An ACLS-Burkhardt Fellowship and a year at the Center for Advanced Study in the Behavioral Sciences greatly aided in the preparation of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Activists’ efforts have added to epistemic resources surrounding this problem. However, because their innovations have been largely rejected by environmental regulators, gaps in collective epistemic resources remain. The use of present tense in this paragraph reflects that lack of uptake in the regulatory context.

2 As a volunteer for Communities for a Better Environment in 2001 and 2002, I elaborated Subra’s original Levels of Concern by incorporating levels from additional government agencies and creating a website to automate the process of looking up Levels of Concern and comparing them to bucket sample results.

3 At the time of writing, this refinery is owned by Phillips 66.

4 One of the five Bay area refineries closed in 2020.

5 Dawn Nafus helpfully characterizes this as the data’s ‘topology.’

6 This does not necessarily suggest that they were below levels of health concern. For some chemicals, like benzene, the detection limits of fenceline monitoring are significantly above levels which are considered to pose a long-term threat to human health.

7 Amos Akinola, former student at Drexel University, performed the data cleaning and analysis to come to these findings.

8 The demographics of the five refinery-adjacent communities in the Bay area are quite different from one another, and not necessarily typical of how one imagines fenceline communities in the United States. Three (Benicia, Crockett, and Martinez) are nearly three-quarters white, and more than 40% of residents in each place hold at least a bachelor’s degree. Richmond and Rodeo are significantly more diverse: less than half of residents are white, and Black, Asian, and Latinx residents each make up a significant portion of the population. Educational attainment is lower, with 28.2% of Richmond residents and 23.9% of Rodeo residents holding at least a bachelor’s degree. (Source: data.census.gov, accessed 7/29/2021).

Additional information

Funding

This work was supported by United States National Science Foundation: [Grant Number 1352143].

Notes on contributors

Gwen Ottinger

Gwen Ottinger is Associate Professor at Drexel University, in the Department of Politics and the Center for Science, Technology, and Society. She directs the Fair Tech Collective, a research group that uses social science theory and methods to promote social justice in science and technology. She is author of Refining Expertise: How Responsible Engineers Subvert Environmental Justice Challenges (2015 Rachel Carson Prize, Society for Social Studies of Science). Ottinger has been an ACLS-Burkhardt Fellow, a Fellow at the Center for Advanced Study in the Behavioral Sciences at Stanford University, and the 2022 Fulbright Research Chair in Science and Society at the University of Ottawa.