Afterword: Ethics as Impact—Moving From Error-Avoidance and Concept-Driven Models to a Future-Oriented Approach. (August 2018)

• Record Type: Journal Article
• Authors: Markham, Annette N.
• Is Part Of: Social media + society. Volume 4:Number 3(2018:Jul./Sep.)
• Publication Date: 2018-08
• Subjects: ethics -- method -- social media -- impact -- contextual ethics; Social media -- Periodicals; Social media -- Social aspects -- Periodicals; 302.231
• DOI: 10.1177/2056305118784504
• Languages: English
• ISSNs: 2056-3051

Abstract

Beginning with the premise that most regulatory guidelines for research ethics are deeply flawed, this article walks the reader through three models that can help social researchers, technologists, and designers identify and reflect on how they're approaching ethics, or "doing the right thing" in their own work. The first, an error-avoidance model, has traditionally focused on creating frameworks to help researchers avoid repeating historical ethical violations. The second concept-driven model focuses on refining the concepts that undergird core ethical frameworks. Both are dominant in human-focused research and tend to be highly proceduralized, implemented a priori or from the top down as part of largescale regulatory structures. In both of these models, the agency of the researcher is removed or dismissed as less relevant than the agency of the system. The article draws on recent controversies around data collection and corporate experimentation on social media users as well as two academic research cases to illustrate how these two models fail repeatedly because they do not retain enough flexibility to allow for recontextualizing ethics as needed on a case-by-case basis. The third, an impact-model of ethics, offers an alternative whereby researchers, technologists, and designers can take a more active role in decisions about the contexts they study, by exploring the possible positive and negative impact of their work. This article invites us to work toward building a different balance in agential distribution in our models around responsible conduct of research, so that the conceptual and regulatory systems that guide and impede our actions are more balanced with our own agency as decision makers, with accountability and responsibility for doing the 'right thing'.