Using structured ethical techniques to facilitate reasoning in technology ethics

Despite many experts’ best intentions, technology ethics continues to embody a commonly used definition of insanity—by repeatedly trying to achieve ethical outcomes through the same methods that don’t work. One of the most intractable problems in technology ethics is how to translate ethical principles into actual practice. This challenge persists for many reasons including a gap between theoretical and technical language, a lack of enforceable mechanisms, misaligned incentives, and others that this paper will outline. With popular and often contentious fields like artificial intelligence (AI), a slew of technical and functional (used here to mean primarily “non-technical”) approaches are continually developed by diverse organizations to bridge the theoretical-practical divide. Technical approaches and coding interventions are useful for programmers and developers, but often lack contextually sensitive thinking that incorporates project teams or a wider group of stakeholders. Contrarily, functional approaches tend to be too conceptual and immaterial, lacking actionable steps for implementation into product development processes. Despite best efforts, many current approaches are therefore impractical or challenging to use in any meaningful way. After surveying a variety of different fields for current approaches to technology ethics, I propose a set of originally developed methods called Structured Ethical Techniques (SETs) that pull from best practices to build out a middle ground between functional and technical methods. SETs provide a way to add deliberative ethics to any technology’s development while acknowledging the business realities that often curb ethical deliberation, such as efficiency concerns, pressures to innovate, internal resource limitations, and more.