
by Claire Maiers
The advancement of predictive data analytics into areas such as medicine, policing, or education has been greeted with both enthusiasm and concern. Where advocates stress a hopeful narrative in which data analytics will allow scientists to solve some of the society’s most difficult problems, critics worry about the potentially narrow and reductive depiction of the world generated by data analytics and about negative outcomes of allowing analytics and algorithms (rather than seasoned experts) to direct decisions.
In a recent article, I explored this tension between experiential and data-driven knowledge by examining the use of predictive analytics in a neonatal intensive care unit, or NICU. I argue that data analytics filter into decision-making through an interpretive process. Although highly dependent upon institutional context, this process may buttress, rather than simply replace, experiential knowledge.








