Global concerns about the preparedness of engineering Ph.D. students for professional practice are not new. In the U.S., educational reform has focused on the research experiences of students to foster better preparation. Yet, little is known about which aspects of students’ research experiences are essential to prepare them for practice due to the heterogeneity of the experiences, and what opportunities they have in their research to practice being a professional. The goal of this study was to develop and initially validate an instrument that measures students’ perceptions of their research experiences utilizing an ontological theoretical framework that focuses on what it means to become a professional. This framework simplified the heterogeneity and allowed for the investigation of how the research experiences of engineering Ph.D. students are providing opportunities for students to practice being a professional. Four distinct phases of development were utilized to accumulate validity evidence for the instrument: a development phase that focused on question generation and review: an initial pilot test that centered on an Exploratory Factor Analysis on responses (n = 236) from a large Midwestern University; a second pilot test that centered on a Confirmatory Factor Analysis on responses (n = 215) from multiple universities; and a Group Analysis phase that tested statistical differences between groups. Three key results emanated from this work. First, the accumulated validity evidence justifies the intended use of the instrument as a research and program evaluation survey to assess engineering Ph.D. students’ research experiences for opportunities to practice being a professional. Second, the results suggest that, on average, students had fewer opportunities to work with professionals (i.e., take on others’ forms of practice) in their research experiences than other types of opportunities. Third, the results suggest that research experiences can be categorized into those that provide significantly more and significantly fewer opportunities for students to practice being a professional. Higher education tends to focus on the epistemological aspects of professional practice preparation, but utilizing an ontological approach can identify gaps in preparation. Implications of the opportunities identified in this study are discussed for faculty, students, other researchers, instrument users, engineering administrators, and national program administrators, with a focus on providing more opportunities to students to practice being a professional. The utilization of an ontological approach for engineering Ph.D. students’ research experiences, including tangible examples and a call for a new vision for U.S. engineering Ph.D. research experiences, are discussed.

Yes / The use of Artificial Intelligence (AI) in Digital technologies (DT) is proliferating a profound socio-technical transformation. Governments and AI scholarship have endorsed key AI principles but lack direction at the implementation level. Through a systematic literature review of 59 papers, this paper contributes to the critical debate on the ethical use of AI in DTs beyond high-level AI principles. To our knowledge, this is the first paper that identifies 14 digital ethics implications for the use of AI in seven DT archetypes using a novel ontological framework (physical, cognitive, information, and governance). The paper presents key findings of the review and a conceptual model with twelve propositions highlighting the impact of digital ethics implications on societal impact, as moderated by DT archetypes and mediated by organisational impact. The implications of intelligibility, accountability, fairness, and autonomy (under the cognitive domain), and privacy (under the information domain) are the most widely discussed in our sample. Furthermore, ethical implications related to the governance domain are shown to be generally applicable for most DT archetypes. Implications under the physical domain are less prominent when it comes to AI diffusion with one exception (safety). The key findings and resulting conceptual model have academic and professional implications.