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Abstract As artificial intelligence (AI) grows in popularity and importance—both as a domain within broader computing research and in society at large—increasing focus will need to be paid to the ethical governance of this emerging technology. The attitudes and competencies with respect to AI ethics and policy among post-secondary students studying computer science (CS) are of particular interest, as many of these students will go on to play key roles in the development and deployment of future AI innovations. Despite this population of computer scientists being at the forefront of learning about and using AI tools, their attitudes towards AI remain understudied in the literature. In an effort to begin to close this gap, in fall 2024 we fielded a survey ($$n=117$$) to undergraduate and graduate students enrolled in CS courses at a large public university in the United States to assess their attitudes towards the nascent fields of AI ethics and policy. Additionally, we conducted one-on-one follow-up interviews with 13 students to elicit more in-depth responses on topics such as the use of AI tools in the classroom, ethical impacts of AI, and government regulation of AI. In this paper, we describe the findings of our exploratory study, drawing parallels and contrasts to broader public opinion polling in the United States. We conclude by evaluating the implications of CS student attitudes on the future of AI education and governance. 

It is emphasized in national legislation, such as the America COMPETES Act and the more recent CHIPS and Science Act, that research integrity is considered essential to the competitiveness and innovation of the U.S. economy. Various stakeholders, particularly research universities, have been developing interventions and programs to foster an ethical culture in STEM (science, technology, engineering, and mathematics) research and practice among faculty and students. Dominant approaches to research ethics education have historically been shaped by biomedical ethics and the broader ethics of science, placing significant emphasis on misconduct of individual researchers, including the falsification, fabrication, and plagiarism (FFP) of research results. Although these approaches have contributed to promoting ethical conduct among individual researchers, we argue that they still face several challenges. Most notably, due to their narrow scope, traditional research ethics education approaches fail to consider the role of disciplinary cultures in shaping research ethics issues. Additionally, they do not leverage the agency of STEM researchers to identify and address these issues or to generate scalable and sustainable impacts within institutions. To address these issues, this paper introduces the IREI (Innovative Research and Ethical Impact) project, which provides an institutional transformation approach to research ethics education for faculty in STEM fields. This approach aims to transform the institutional culture for ethical STEM research by helping faculty develop and enhance their capacity to identify and address ethical issues in their daily work, while generating scalable and sustainable impacts by leveraging their social networks. More specifically, this paper introduces the curriculum design for a professional development workshop for STEM faculty, which is a key component of the IREI project. This faculty development workshop begins by broadening the understanding of ethics, shifting the focus from aligning the conduct of individual researchers with predetermined ethical principles to the impacts of their actions on the lives of others, as well as on the broader environment and society. This expanded definition is used for two main reasons. First, it emphasizes that it is the actions themselves that ultimately affect others, rather than merely a researcher’s intent or the ethical justification of their behavior. Second, it highlights that future potential impacts are as crucial in research as present, actual impacts—if not more so—since research is intrinsically novel and often future-oriented. Based on this definition, researchers are introduced to steps in the research process, from formulating questions to disseminating results. Participants are then provided with reflective tools and hands-on activities to enhance their ethical sensitivity and expertise throughout the entire research process. This enables them to identify (1) who is affected by their research at various stages and how they are impacted, and (2) strategies to maximize positive effects while minimizing any negative consequences. Finally, faculty are provided with mentoring opportunities to incorporate these reflective insights into broader impacts statements of their own research proposals and projects. Given that these statements directly pertain to their research, we hope that participants will view this workshop as both significant and relevant, as they have a natural interest in making their statements as clear and compelling as possible. 

As artificial intelligence and robotics are increasingly integrated in graduate research and education, graduate students across disciplines need to develop a “technological literacy” in how they work along with the ethical understanding needed to navigate these technologies responsibly. To satisfy this need, the corresponding and last author has developed a graduate-level course on AI ethics and human-robot interaction (HRI) designed for students from a variety of disciplines and backgrounds. The paper offers an overview of the course, detailing its content, institutional context, and the rationale behind its development. It describes the curriculum structure, including key themes and learning objectives, and the pedagogical approaches and assessment methods utilized in the course. The paper concludes with reflections from the instructor on the lessons learned from teaching the course and the experiences gained throughout the learning process. 

Abstract The explosive growth of artificial intelligence (AI) over the past few years has focused attention on how diverse stakeholders regulate these technologies to ensure their safe and ethical use. Increasingly, governmental bodies, corporations, and nonprofit organizations are developing strategies and policies for AI governance. While existing literature on ethical AI has focused on the various principles and guidelines that have emerged as a result of these efforts, just how these principles are operationalized and translated to broader policy is still the subject of current research. Specifically, there is a gap in our understanding of how policy practitioners actively engage with, contextualize, or reflect on existing AI ethics policies in their daily professional activities. The perspectives of these policy experts towards AI regulation generally are not fully understood. To this end, this paper explores the perceptions of scientists and engineers in policy-related roles in the US public and nonprofit sectors towards AI ethics policy, both in the US and abroad. We interviewed 15 policy experts and found that although these experts were generally familiar with AI governance efforts within their domains, overall knowledge of guiding frameworks and critical regulatory policies was still limited. There was also a general perception among the experts we interviewed that the US lagged behind other comparable countries in regulating AI, a finding that supports the conclusion of existing literature. Lastly, we conducted a preliminary comparison between the AI ethics policies identified by the policy experts in our study and those emphasized in existing literature, identifying both commonalities and areas of divergence. 

This chapter presents a historical and cross-national comparative examination of the formal incorporation of ethics and related learning outcomes in accreditation criteria for engineering graduates. The authors begin by exploring the origin of modern accreditation systems in higher education, emphasizing key developments in the United States over more than a century. They note more recent, widespread moves from inputs- to outputs-based frameworks, alternate quality assurance methods used in some non-US regions, and the continued global influence of US-style approaches to accreditation. They then present a series of specific cases to explore when, where, and how ethics and associated concerns have been formally codified in accreditation requirements for engineering graduates. They start with the United States as a well-documented and influential example and follow this with a description of two other Western/Anglo settings (the United Kingdom and Canada). They then turn to two international agreements (the Washington Accord and EUR-ACE) and two East Asian cases (Japan and China). Their account synthesizes prior scholarship and references some primary source materials, offering fresh new insight into the origins and development of engineering ethics education accreditation.