There is a growing privacy problem introduced by integrating predictive generative AI search layers directly into library discovery systems. As these automated tools log, aggregate, and analyze nuanced user search workflows to hyper-personalize recommendations, they frequently establish unmonitored data pipelines that conflict with core library ethics regarding data minimization and intellectual freedom. How is your library or digital scholarship department establishing algorithmic transparency guidelines or patron data governance frameworks to audit these third-party AI-driven discovery tools without diminishing search utility?
