Agricultural decision support systems (DSSs) are hardware and software tools that utilize big data collected from satellites and drones, ground-based sensors, and analyzed with machine learning algorithms to provide site-specific farming recommendations. Despite the promise of DSSs to address many challenges of the farm economy, there are social and ethical concerns that need to be addressed. Utilizing a mixed-methods approach that consisted of focus group discussions and a follow-up survey questionnaire, we highlight the experiences and affectations of heterogeneous food system actors from Vermont and South Dakota. We find that DSSs transform agricultural knowledge production, reconfigure labor arrangements and unevenly distribute benefits and burdens among farmers. We suggest that agritech developers implement inclusive and deliberative processes when redesigning DSSs to engender ethical, equitable and sustainable improvements to food production systems. Inclusive processes of open deliberation are modalities of responsible innovation, tasked with mitigating frictions within socio-technical systems.