Implementing AI Ethics in Practice: An Empirical Evaluation of the RESOLVEDD Strategy

Abstract

Use of artificial intelligence (AI) in human contexts calls for ethical considerations for the design and development of AI-based systems. However, little knowledge currently exists on how to provide useful and tangible tools that could help software developers and designers implement ethical considerations into practice. In this paper, we empirically evaluate a method that enables ethically aligned design in a decision-making process. Though this method, titled the RESOLVEDD strategy, originates from the field of business ethics, it is being applied in other fields as well. We tested the RESOLVEDD strategy in a multiple case study of five student projects where the use of ethical tools was given as one of the design requirements. A key finding from the study indicates that simply the presence of an ethical tool has an effect on ethical consideration, creating more responsibility even in instances where the use of the tool is not intrinsically motivated.

Operationalising AI ethics: barriers, enablers and next steps

“…When designing a programme of research, the choice of which method to employ is dependent upon the nature of the research problem (Noor 2008). If our intention was to develop an in-depth understanding of how one method for translating ethics principles into practice might become effective, then a case study approach would be most appropriate, as demonstrated by Vakkuri and Kemell (2019) in their review of the RESOLVEDD strategy for ethical decision-making, or Wong et al (2018) in their evaluation of mobile Augmented Reality (AR) learning trails-Trails of Integrity and Ethics-in Hong Kong. Alternatively, a scoping or systematic review approach could be appropriate, as Nicholls et al (2015) highlighted with their review of empirical research assessing the quality and effectiveness of research ethics reviews.…”

Integrating ethics in AI development: a qualitative study

“…Within the frameworks that guide AI’s development, the question remains: Who is in charge or responsible for ethically aligning AI in healthcare? Empirical evidence suggests that development teams are often more concerned with the usefulness and viability of the product rather than its ethical aspects [ 35 ]. In part, these results are expected as software developers are not responsible for strategic decisions regarding how and why AI is developed [ 17 ].…”

Managing Ethical Risks of Artificial Intelligence in Business Applications

“…If all the organization has is a set of principles that do not change its daily practices, they are of little practical effect. This "principles-to-practice" quandary is a recognized problem in the literature, and while many researchers have proposed solutions that include frameworks, toolkits, and guidelines [5,6,[49][50][51], their lack of organizational adoption persists [33,[52][53][54].…”

“…Based on the literature, many frameworks, toolkits, and guidelines have linked AI Ethical Principles to proposed AI Ethical Practices. These included the IEEE's Ethically Aligned Design principles [5] for AI system design, Shneiderman's [6] fifteen proposals for bridging the gap between ethics and practice using an enhanced governance approach, Peters et al's [50] proposal for balancing a responsible design process with the user's interaction with the technology, and Vakkuri and Kemell's [51] nine-step "RESOLVEDD strategy" for rational ethical decision-making. These various approaches form the foundation for part of the problem space that the RRD can address.…”