Department of Sociology, University of Cambridge, Cambridge, UK.
Sociol Health Illn. 2019 Oct;41 Suppl 1(Suppl 1):193-209. doi: 10.1111/1467-9566.12881.
The 21st century has witnessed the emergence of in silico reproduction alongside the familiar in vitro reproduction (e.g. IVF), as increasingly large and automatically-generated data sets have come to play an instrumental role in assisted reproduction. The article addresses this datafication of reproduction by analysing time-lapse embryo imaging, a key data-driven technology for embryo selection in IVF cycles. It discusses the new forms of knowledge and value creation enabled by data-driven embryo selection and positions this technology as a harbinger of a wider datafication of (reproductive) health. By analysing the new ways of seeing embryos with 'in silico vision,' the 'data generativity' of developing embryos and the patenting of embryo selection algorithms, I argue that this datafied method of embryo selection may not just result in more or less 'IVF success,' but also affects the conceptualisation and commercialisation of the assisted reproductive process. In doing so, I highlight how the datafication of reproduction both reflects and reinforces a consolidating trend in the fertility sector-characterised by mergers resulting in larger fertility chains, online platforms organising fertility care and expanded portfolios of companies aiming to cover each step of the IVF cycle.
21 世纪见证了计算生殖的出现,与此同时,人们也熟悉体外生殖(例如 IVF),因为越来越大且自动生成的数据集开始在辅助生殖中发挥重要作用。本文通过分析延时胚胎成像来解决生殖的数据化问题,延时胚胎成像技术是 IVF 周期中胚胎选择的关键数据驱动技术。本文讨论了数据驱动的胚胎选择所带来的新知识和新价值创造形式,并将该技术定位为(生殖)健康数据化的更广泛趋势的先兆。通过分析用“计算视觉”观察胚胎的新方法、发育中的胚胎的“数据生成能力”以及胚胎选择算法的专利化,我认为这种数据化的胚胎选择方法不仅可能导致更多或更少的“IVF 成功”,还会影响辅助生殖过程的概念化和商业化。通过这样做,我强调了生殖数据化既反映又加强了生育领域的一个巩固趋势——合并导致更大的生育链、在线平台组织生育护理以及扩大旨在涵盖 IVF 周期每个步骤的公司组合。