  In the rapidly evolving landscape of computing disciplines, substantial
efforts are being dedicated to unraveling the sociotechnical implications of
generative AI (Gen AI). While existing research has manifested in various
forms, there remains a notable gap concerning the direct engagement of
knowledge workers in academia with Gen AI. We interviewed 18 knowledge workers,
including faculty and students, to investigate the social and technical
dimensions of Gen AI from their perspective. Our participants raised concerns
about the opacity of the data used to train Gen AI. This lack of transparency
makes it difficult to identify and address inaccurate, biased, and potentially
harmful, information generated by these models. Knowledge workers also
expressed worries about Gen AI undermining trust in the relationship between
instructor and student and discussed potential solutions, such as pedagogy
readiness, to mitigate them. Additionally, participants recognized Gen AI's
potential to democratize knowledge by accelerating the learning process and act
as an accessible research assistant. However, there were also concerns about
potential social and power imbalances stemming from unequal access to such
technologies. Our study offers insights into the concerns and hopes of
knowledge workers about the ethical use of Gen AI in educational settings and
beyond, with implications for navigating this new landscape.
