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Although development of Artificial Intelligence (AI) technologies has been underway for decades, the acceleration of AI capabilities and rapid expansion of user access in the past few years has elicited public excitement as well as alarm. Leaders in government and academia, as well as members of the public, are recognizing the critical need for the ethical production and management of AI. As a result, society is placing immense trust in engineering undergraduate and graduate programs to train future developers of AI in their ethical and public welfare responsibilities. In this paper, we investigate whether engineering master’s students believe they receive the training they need from their educational curricula to negotiate this complex ethical landscape. The goal of the broader project is to understand how engineering students become public welfare “watchdogs”; i.e., how they learn to recognize and respond to their public welfare responsibilities. As part of this project, we conducted in-depth interviews with 62 electrical and computer engineering master’s students at a large public university about their educational experiences and understanding of engineers’ professional responsibilities, including those related specifically to AI technologies. This paper asks, (1) do engineering master’s students see potential dangers of AI related to how the technologies are developed, used, or possibly misused? (2) Do they feel equipped to handle the challenges of these technologies and respond ethically when faced with difficult situations? (3) Do they hold their engineering educators accountable for training them in ethical concerns around AI? We find that although some engineering master’s students see exciting possibilities of AI, most are deeply concerned about the ethical and public welfare issues that accompany its advancement and deployment. While some students feel equipped to handle these challenges, the majority feel unprepared to manage these complex situations in their professional work. Additionally, students reported that the ethical development and application of technologies like AI is often not included in curricula or are viewed as “soft skills” that are not as important as “technical” knowledge. Although some students we interviewed shared the sense of apathy toward these topics that they see from their engineering program, most were eager to receive more training in AI ethics. These results underscore the pressing need for engineering education programs, including graduate programs, to integrate comprehensive ethics, public responsibility, and whistleblower training within their curricula to ensure that the engineers of tomorrow are well-equipped to address the novel ethical dilemmas of AI that are likely to arise in the coming years.
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This content will become publicly available on April 25, 2026
"I Would Never Trust Anything Western": Kumu (Educator) Perspectives on Use of LLMs for Culturally Revitalizing CS Education in Hawaiian Schools
As large language models (LLMs) become increasingly integrated into educational technology, their potential to assist in developing curricula has gained interest among educators. Despite this growing attention, their applicability in culturally responsive Indigenous educational settings like Hawai‘i’s public schools and Kaiapuni (immersion language) programs, remains understudied. Additionally, ‘Ōlelo Hawai‘i, the Hawaiian language, as a low-resource language, poses unique challenges and concerns about cultural sensitivity and the reliability of generated content. Through surveys and interviews with kumu (educators), this study explores the perceived benefits and limitations of using LLMs for culturally revitalizing computer science (CS) education in Hawaiian public schools with Kaiapuni programs. Our findings highlight AI’s time-saving advantages while exposing challenges such as cultural misalignment and reliability concerns. We conclude with design recommendations for future AI tools to better align with Hawaiian cultural values and pedagogical practices, towards the broader goal of trustworthy, effective, and culturally grounded AI technologies.
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- Award ID(s):
- 2345488
- PAR ID:
- 10648943
- Publisher / Repository:
- ACM
- Date Published:
- Page Range / eLocation ID:
- 1 to 10
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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