| Summary: | Early childhood is seen by many as the ideal time to shape, support and encourage the child in order to become fully emotionally, intellectually and socially competent adults in the future. Discussions about the degree that children can participate and have agency in these processes are ongoing. However, what happens with these agentic capacities when decisions are made based on big data analytics and predictive algorithms?
Predictive algorithms are enacted in the everyday in multiple ways: for example, autosuggested google search terms; Amazon recommendations; or more controversially in predictive (and pre-emptive) policing practices. Prediction entails forecasting possible outcomes based on modelling, pattern detection and recognition through the (supervised and/or unsupervised) analysis of large data sets using iterative machine learning algorithmic processes. These practices inform strategies, policies and planning.
Within the contemporary child’s digital ecosystem/s, there are multiple and diverse predictive practices at play. This chapter explores a number of predictive practices in early childhood initiatives. In doing so, the paper raises questions about broader ethical, and normative issues for child rearing practices, and the possibilities for child or parental agency when predictive practices drive choices that are available, hidden or negated.
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