# AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities
## 2 Background
### Technology Diffusion in HEIs  
Technology diffusion refers to the process by which new technologies are adopted and spread across different regions, sectors, and social groups, during which technology is transferred, implemented, and utilized, leading to widespread acceptance and integration into everyday practices [29]. Technology diffusion in universities is a complicated process, which often faces multifaceted challenges rooted in both organizational and cultural aspects of HEIs [30; 31]. One primary challenge is the rapid and massive development of technology, which requires continuous adaptation and innovation from HEIs to maintain their educational and academic quality [32]. This adaptation is contingent upon the effective diffusion of innovation models that consider the profile of human resources, technological conditions, organizational policies, documentation, and environmental dynamics [33]. Additionally, the adoption of new information and communication technology is hindered by issues such as incompatible technology with faculty's traditional teaching practices, inadequate faculty support, and insufficient plans for implementation [34]. Instructors face challenges in staying updated with the changing uses of technology in the classroom, necessitating training, funding, and alignment of perceptions to facilitate technology adoption [35]. The integration of technology in teaching and learning processes is influenced by technological, pedagogical, and organizational dimensions, with contextual factors playing a determinant role [36]. Regarding the adoption of AI in HEIs, there is still a lack of sound evidence on the pedagogical impact of AI technologies, which raises questions about their ability to improve learning outcomes or facilitate effective pedagogical changes [37]. Additionally, the ethical concerns associated with biased algorithms, which could adversely affect students if used in admissions or grading processes, represent a significant technological and ethical barrier [38]. Educators' perspectives and the social, psychological, and cultural factors influencing their trust and adoption of educational technology also play a role in the slow uptake of AI tools [39]. The barriers to digital technology integration, including technophobia and the absence of planning, directly impact the adoption of AI in university teaching [40]. Therefore, to effectively govern the implementation of AI tools, it is crucial to integrate robust communication practices. AI governance in HEIs involves not just creating policies but also ensuring they are clearly communicated and understood at all levels. This includes identifying key stakeholders responsible for crafting and delivering these messages, such as senior leaders or governance committees. Effective communication from authoritative figures emphasizes the importance of these guidelines and fosters a culture of ethical compliance. Thus, a connection between governance and AI guidelines is established through the need for clear, consistent, and authoritative communications. Through the analysis of public guidelines on GenAI, we aim to shed light on how HEIs could actively adopt AI technology and how it manages the potential harms through communications with its community. These communications, in the form of policy documentation and webpages, facilitate understanding, transparency, and collaboration between the institution and its stakeholders and effectively convey how the institution is integrating AI technology and addressing any associated risks. It should be noted that this case study mainly focused on universities in the US, and there can be cultural and societal differences across countries regarding AI development and governance. For example, [PERSON] and [PERSON] [41] compared the AI development strategies in Singapore, the US, and the UK, concluding that Singapore prefers to utilize government sectors and the UK prefers to utilize education sectors while the US prefers to utilize both education sectors and private sectors.