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This paper analyses how precision has become a ubiquitous prefix in medicine, agriculture and education. The accompanying imagination in each of these domains is that "data" will enable greater predictive accuracy through new sensors and interfaces. In this paper, we aim to provide insights regarding the ways in which precision assemblages function to augment and extend existing knowledge and data infrastructures, while also being underpinned by the anticipatory promise of the ubiquity of digital and sensing technologies. We argue that precision is marked by new data production and aggregation frameworks to measure and intervene. At the same time, precision draws on–and augments–established clinical, agricultural and educational subjectivities in ways that depict new logics of patient, student and environmental care. As we outline below, the threshold of the shift to precision is articulated and institutionalized at different points in each field we analyse in the subsequent sections of this paper–namely medicine, agriculture and education. This suggests that precision should be understood as an unevenly realized moment in policy development, rather than as simply produced through processes of technological change.

Research Report—'Education, work and Australian society in an AI world: A review of research literature'1. Research BackgroundThe research was in the field of education. The Gonski Institute for Education commissioned us to research and write a report on current research literature concerning artificial intelligence and education. The emergence of Artificial Intelligence has become an issue for education in two ways—in terms of changing provision and practices within education itself, and in terms of education's crucial role in preparing for the future, especially but not only the future of work. Policy makers are seeking guidelines as to how to respond. The report's key aim was to review the literature in order to present policy recommendations. 2. Research Contribution The report contributes to knowledge by synthesising and evaluating the current literature and presenting 6 key policy recommendations in order to safeguard the future of Australian education and to foster social innovation. Its main concern is the organisation and administration of education in a world in which AI is becoming an increasingly powerful social force. The recommendations include: forming a cross-sector representative body; providing professional development opportunities for teachers; working towards the ethical and effective procurement of AI systems; introducing adaptive and personalised learning in a way that ensures a focus on educational and equity principles; providing appropriate data protection and legislation; focusing on AI-complimentary skills. 3. Research Significance & Evidence of Excellence The significance of this research is that it enables education policy influencers, policy makers and other stakeholders to frame appropriate responses to the emergence of AI. Its value is attested to by the following indicators: • Accepted and published by the Gonski Institute for education • Invited to publish an article based on the report for the Journal of Professional Learning published by The NSW Teachers Federation's (NSWTF) Centre for Professional Learning (CPL) [written and published January 2019]• Has received responses international from various teacher's group (e.g. from Canada)