Algorithms increasingly govern societal functions, impacting multiple stakeholders and social groups. How can we design these algorithms to balance varying interests in a moral, legitimate way? As one answer to this question, we present WeBuildAI, a collective participatory framework that enables people to build algorithmic policy for their communities. The key idea of the framework is to enable stakeholders to construct a computational model that represents their views and to have those models vote on their behalf to create algorithmic policy. As a case study, we applied this framework to a matching algorithm that operates an on-demand food donation transportation service in order to adjudicate equity and efficiency trade-offs. The service's stakeholders--donors, volunteers, recipient organizations, and nonprofit employees--used the framework to design the algorithm through a series of studies in which we researched their experiences. Our findings suggest that the framework successfully enabled participants to build models that they felt confident represented their own beliefs. Participatory algorithm design also improved both procedural fairness and the distributive outcomes of the algorithm, raised participants' algorithmic awareness, and helped identify inconsistencies in human decision-making in the governing organization. Our work demonstrates the feasibility, potential and challenges of community involvement in algorithm design.

Objectives: The characteristics of non-electrocardiography-and electrocardiographygated multidetector computed tomography have not been extensively studied in veterinary clinics but it can be useful for cardiac imaging. This study aimed to ascertain the differences between non-electrocardiography and electrocardiography gating methods and to establish their clinical utility based on patient history.Methods: Six client-owned dogs (two with patent ductus arteriosus, two with heart base tumour, one with pericardial mesothelioma, and one with normal health) were included in this study. All the dogs were examined using a non-electrocardiographygated scan, followed by a retrospective electrocardiography-gated scan. Images were reviewed to determine the optimal scan timing and R-R interval in nonelectrocardiography-and electrocardiography-gated images, respectively, for detailed coronary artery imaging, diagnostic quality of the best coronary artery visualisation in non-electrocardiography-and electrocardiography-gated images through visual assessment of the main coronary artery branches, and branching patterns of the left coronary artery. Further, we compared the size and margin demarcation of the heart or pericardial lesions in non-electrocardiography-and electrocardiography-gated images obtained from patients with heart or pericardial tumours. Results:The optimal scan timing and R-R interval were the second-scan timing and end-diastole (70%-90%), respectively. Second-scan non-electrocardiography-gated images allowed coronary artery evaluation, indicating high-grade quality in visual assessment, except for the septal branch. Electrocardiography-gated images, but not non-ECG-gated images, clearly revealed pericardial nodules in two dogs.Clinical Significance: Our findings suggest the respective clinical utilities of nonelectrocardiography-or electrocardiography-gated imaging using high-slice cardiac computed tomography based on patient history.