Public sector AI has the potential to harm citizens, with risks increasing as its use expands. Recent work positions public procurement as a way to shape public sector AI in line with public interests, using the state’s purchasing power to influence which AI systems are procured and under what conditions. This paper examines how this potential can be realised in practice by drawing on semi-structured interviews with UK and EU buyers, providers, and procurement experts. Our findings result in six promising procurement practices that enable the public sector to shape AI in line with public interests, alongside concrete mechanisms to support their uptake. Further, we find that AI-specific procurement approaches remain immature and systems often enter through informal channels with less scrutiny. We provide directions for both research and practice on how public procurement can be used as a governance mechanism for better aligning AI with public interests.

Fertility trackers are popular for self-monitoring menstrual cycles and managing other aspects of reproductive or sexual health. However, the intimate nature of fertility tracking raises particular concerns about potential data (mis)use. Our study deepens understandings of fertility tracker data sharing and presents co-created mechanisms to enhance user agency over their data in intimate contexts. To achieve this, we first analysed the network transmissions from eight fertility tracker products, observing that many data transmissions appear to be tied to particular uses of the tracker and that the products communicate with endpoints associated with various organisations across different countries. This raises concerns about how intimate data is governed, used, and shared. To understand user attitudes towards data sharing in intimate contexts, we then conducted a survey exploring factors influencing user data sharing preferences. Our findings reveal that users desire transparency and control mechanisms and that their willingness to share data is influenced by contextual factors, including the third parties involved, the purposes of data collection, and the sensitivity of the data. Building on these findings, we worked with users to co-design ten concrete mechanisms for enhancing data transparency and control throughout fertility tracker product usage lifecycles. In all, our mixed-method study provides an in-depth understanding of fertility tracker data flows and preferences and proposes actionable mechanisms designers can utilise to support and protect data rights in intimate data ecosystems.