In September 2015, Rana Novack, a Syrian American advocate for refugees and civilians in conflict and founder of the Refugee Admissions Network Alliance, wrote an article in Wired magazine entitled ‘We should have seen this refugee crisis coming’. There, Novack berates the reactive approach taken to the escalating refugee crisis that first captured public attention when between January and March 2015 479 refugees drowned or went missing in the Mediterranean Sea (UNHCR 2015). Novack calls upon the IT community to ‘step up - big time’ and use its ability to analyse ‘incredible amounts of data’ and build ‘predictive models’: we should be able to know when and where the next migration will occur. We should be able to predict how many people it will affect and the impact on surrounding areas. We have the technology - right here, right now - to create a new, agile, insightful model that will predict mass migrations and help us better serve displaced families even before they are displaced. We can do all this now. And we must. (Novack 2015) Such hopes that IT experts can construct machine or algorithmic ‘intelligence’ to analyse patterns, trends, anomalies within the vast amounts of data or ‘intelligence about’ people’s and objects’ everyday life, are widespread. They index complex intersections of different forms of intelligence and motivations for using them.