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1. Exploring the role of engineering judgment in engineer identity formation through student technical reports

   https://doi.org/10.1109/FIE44824.2020.9273970  

   Francis, Royce; Paretti, Marie; Riedner, Rachel (October 2020, 2020 IEEE Frontiers in Education Conference (FIE))

   null (Ed.)

   The engineering disciplines are rigorous in their application of scientific principles, and these principles are the ones most directly addressed in undergraduate engineering classrooms. However, engineers are also called to make decisions that implicitly account for complex criteria, including the welfare of those who use or are impacted by the systems engineers design and the economic needs of their employers. As a result, engineering is an art that requires practitioners to routinely navigate difficult tradeoffs that require professional judgments. These judgments include economic, ethical, social, and value-based dimensions. These dimensions can be conflicting, increasing the complexity of practice and foregrounding the prominence of judgment. And often, these judgements need to be explained to colleagues, managers, and clients through a range of written documents. Yet little work to date has investigated the relationship between the writing engineering students do and the development of engineering judgement, particularly in terms of how these facets intersect in students developing engineering identities . Therefore, the overall goal of this project is to elucidate the interactions between how students’ identification with the engineering profession impacts the way they convey engineering judgments to different audiences. 

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2. It’s about power: What ethical concerns do software engineers have, and what do they (feel they can) do about them?

   https://doi.org/10.1145/3593013.3594012  

   Widder, David Gray; Zhen, Derrick; Dabbish, Laura; Herbsleb, James (June 2023, ACM)

   How do software engineers identify and act on their ethical concerns? Past work examines how software practitioners navigate specific ethical principles such as “fairness”, but this narrows the scope of concerns to implementing pre-specified principles. In contrast, we report self-identified ethical concerns of 115 survey respondents and 21 interviewees across five continents and in non-profit, contractor, and non-tech firms.We enumerate their concerns – military, privacy, advertising, surveillance, and the scope of their concerns – from simple bugs to questioning their industry’s entire existence. We illustrate howattempts to resolve concerns are limited by factors such as personal precarity and organizational incentives. We discuss how even relatively powerful software engineers often lacked the power to resolve their ethical concerns. Our results suggest that ethics interventions must expand from helping practitioners merely identify issues to instead helping them build their (collective) power to resolve them, and that tech ethics discussions may consider broadening beyond foci on AI or Big Tech. 

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3. Theorizing Engineering Judgment at the Intersection of Decision-Making and Identity

   Royce A. Francis, Marie C. (January 2022, Studies in engineering education)

   Engineering judgment is critical to both engineering education and engineering practice, and the ability to practice or participate in engineering judgment is often considered central to the formation of professional engineering identities. In practice, engineers must make difficult judgments that evaluate potentially competing objectives, ambiguity, uncertainty, incomplete information, and evolving technical knowledge. Nonetheless, while engineering judgment is implicit in engineering work and so central to identification with the profession, educators and practitioners have few actionable frameworks to employ when considering how to develop and assess this capacity in students. In this paper, we propose a theoretical framework designed to inform both educators and researchers that positions engineering judgment at the intersection of the cognitive dimensions of naturalistic decision-making, and discursive dimensions of identity. Our proposed theory positions engineering judgment not only as an individual capacity practiced by individual engineers alone but also as the capacity to position oneself within the discursive community so as to participate in the construction of engineering judgments among a group of professionals working together. Our theory draws on several strands of existing research to theorize a working framework for engineering judgment that considers the cognitive processes associated with making judgments and the inextricable discursive practices associated with negotiating those judgments in context. In constructing this theory, we seek to provide engineering education practitioners and researchers with a framework that can inform the design of assignments, curricula, or experiences that are intended to foster students’ participation in the development and practice of engineering judgment. 

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4. “I Don’t Know If We’re Doing Good. I Don’t Know If We’re Doing Bad”: Investigating How Practitioners Scope, Motivate, and Conduct Privacy Work When Developing AI Products

   Lee, H-P; Gao, L; Yang, S; Forlizzi, J; Das, S (August 2024, USENIX Security)

   How do practitioners who develop consumer AI products scope, motivate, and conduct privacy work? Respecting pri- vacy is a key principle for developing ethical, human-centered AI systems, but we cannot hope to better support practitioners without answers to that question. We interviewed 35 industry AI practitioners to bridge that gap. We found that practitioners viewed privacy as actions taken against pre-defined intrusions that can be exacerbated by the capabilities and requirements of AI, but few were aware of AI-specific privacy intrusions documented in prior literature. We found that their privacy work was rigidly defined and situated, guided by compliance with privacy regulations and policies, and generally demoti- vated beyond meeting minimum requirements. Finally, we found that the methods, tools, and resources they used in their privacy work generally did not help address the unique pri- vacy risks introduced or exacerbated by their use of AI in their products. Collectively, these findings reveal the need and opportunity to create tools, resources, and support structures to improve practitioners’ awareness of AI-specific privacy risks, motivations to do AI privacy work, and ability to ad- dress privacy harms introduced or exacerbated by their use of AI in consumer products. 

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5. Humanizing AI Grading: Student-Centered Insights on Fairness, Trust, Consistency and Transparency

   Riahi, Bahare; Storozhevykh, Viktoriia; Catet'e, Veronica (February 2026, arXiv)

   This study investigates students' perceptions of Artificial Intelligence (AI) grading systems in an undergraduate computer science course (n = 27), focusing on a block-based programming final project. Guided by the ethical principles framework articulated by Jobin (2019), our study examines fairness, trust, consistency, and transparency in AI grading by comparing AI-generated feedback with original human-graded feedback. Findings reveal concerns about AI's lack of contextual understanding and personalization. We recommend that equitable and trustworthy AI systems reflect human judgment, flexibility, and empathy, serving as supplementary tools under human oversight. This work contributes to ethics-centered assessment practices by amplifying student voices and offering design principles for humanizing AI in designed learning environments. 

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