2026 ASEE Annual Conference & Exposition

As artificial intelligence becomes more deeply embedded in engineering practice, engineering ethics education must move beyond general moral awareness toward forms of reasoning that address the distinctive socio-technical demands of AI-enabled systems. Existing approaches to ethics assessment in engineering education, including the Defining Issues Test-2, the Engineering and Science Issues Test, and the Engineering Ethical Reasoning Instrument, provide important foundations but were not designed for AI-related contexts involving subgroup disparities, opacity, privacy risks, and responsibility under partial automation. In response to this gap, this paper proposes AI-Situated Ethical Reasoning (ASER) as a conceptual framework for engineering education.

ASER is organized around three interrelated dimensions: ethical recognition, or the ability to identify ethically salient features of an AI-enabled engineering problem; ethical evaluation, or the ability to interpret and weigh competing principles, stakeholder consequences, and technical evidence; and responsible action, or the ability to articulate justified, context-sensitive responses. The paper situates this framework within four strands of scholarship: engineering ethics education, ethics assessment research, AI ethics and responsible-AI literature, and professional frameworks including ABET Student Outcome 4 and the NIST AI Risk Management Framework. It also illustrates the educational use of the framework through a visual model, a synthesis table, and a worked example involving an AI-enabled skin lesion triage tool.

Rather than presenting a validated instrument, this paper offers a conceptual foundation for future assessment development, instructional design, and curricular integration in AI-integrated engineering education. By clarifying the structure of ASER, the manuscript provides a more explicit basis for studying and supporting ethical reasoning in contemporary engineering contexts.