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How universities can influence socially responsible AI technology development and use. 

In light of both social and ABET expectations, engineering educators need to consider how to effectively infuse engineering ethics education into current engineering curricula. This article describes our initial efforts in that realm. We considered how to improve ethics education in engineering through establishing an academic-industry partnership, which facilitated conversation between engineering faculty members and practicing engineers in industry. We formed a College-level Ethics Advisory Council with representation from industry partners across all 13 engineering departments in Purdue’s College of Engineering. As the first official activity, we held an Ethics Advisory Council Workshop to define common goals and share mutual expectations for long-term relationships. This article shares some basic information about the academic-industry partnership and outputs from the Ethics Advisory Council Workshop. We also discuss lessons we learned from the initial work on the partnership, including limitations and other considerations important for potential adopters of such a strategy at their institution. This article can provide insights to engineering educators who are interested in adopting the academic-industry partnership approach to facilitate direct conversations between academia and industry, especially for better engineering ethics education. 

This WIP paper describes a team approach to phenomenography on ethical engineering practice in the health products industry and its potential impact on research quality. Although qualitative researchers often conduct phenomenography collaboratively, most often a single individual leads the data collection and analysis; others primarily serve as critical reviewers. However, quality may be enhanced by involving collaborators as data analysts in “sustained cycles of scrutiny, debate and testing against the data” [1, p. 88], thus interweaving unique perspectives and insights throughout the analysis process. Nonetheless, collaborating in this intensive data analysis process also presents unique challenges. In this paper, we (1) describe the processes we are applying in an integrated team-based phenomenographic study, (2) identify how the team approach affects research quality, and (3) reflect on the challenges inherent to this process. We ground this reflective case study in the methodological literature on phenomenography. Our team strategies include multiple interviewers (and, when possible, two interviewers per inter-view), team communication through reflective memos, and integration of individual and team-based data analysis with peer critique of individual analyses. We compare our team approach with typical individual phenomenographic approaches, and we align our procedures with the five strategies of the Qualifying Qualitative Research Quality Framework, or Q3, designed by Walther, Sochacka, and Kellam [2]. In aligning strategies, we consider benefits and trade-offs. 

This Work-in-Progress Research paper describes (1) the contemporary research space on ethics education in engineering; (2) our long-term research plan; (3) the theoretical underpinnings of Phase 1 of our research plan (phenomenography); and (4) the design and developmental process of a phenomenographic interview protocol to explore engineers’ experiences with ethics. Ethical behavior is a complex phenomenon that is complicated by the institutional and cultural contexts in which it occurs. Engineers also have varied roles and often work in a myriad of capacities that influence their experiences with and understanding of ethics in practice. We are using phenomenography, a qualitative research approach, to explore and categorize the ways engineers experience and understand ethical engineering practice. Specifically, phenomenography will allow us to systematically investigate the range and complexity of ways that engineers experience ethics in professional practice in the health products industry. Phenomenographic data will be obtained through a specialized type of semi-structured interview. Here we introduce the design of our interview protocol and its four sections: Background, Experience, Conceptual, and Summative. We also describe our iterative process for framing questions throughout each section.