In H. G. Wells’ heavily critical review of Fritz Lang’s dystopian classic, Metropolis, he set against the film for its central premise that automation created drudgery instead of relieving it. Wells noted that ’Masterman's (the protagonist) watchword is 'Efficiency,' and you are given to understand it is a very dreadful word, and the contrivers of this idiotic spectacle are so hopelessly ignorant of all the work that has been done upon industrial efficiency that they represent him as working his machine-minders to the point of exhaustion, so that they faint and machines explode and people are scalded to death.’
It is now almost 90 years since the release of Metropolis, and its vision of municipal planning as dominated by the drive for efficiency and automation have proved prescient. Fortunately, Wells has proved similarly correct in decrying the silliness of how the film depicted the consequences of this drive. That being said, with the rise of IoT, and the decision of many of the world’s largest cities to embrace ‘open data’ schemes, it’s safe to say that we are nowhere near our capacity for automation.
According to data.gov, 46 U.S. cities now have their own data portal. Of these, Chicago is arguably leading the way as the most aggressive in its adoption of data and analytics. On December 10, 2012, Mayor Rahm Emanuel issued Executive Order 2012-2 to codify his commitment to open data, in which he outlined the City’s commitments to gather data and make it available to the public en masse. The City’s open data portal now offers user-friendly access to more than 600 data sets, and it is always adding more according to public desire and usefulness.
Last September, Tom Schenk was was appointed Chicago's new Chief Data Officer. Schenk previously served as the the City's director of analytics and its open data portal, and he is overseeing a radical adoption of analytics across every facet of city management. In 2014, Chicago’s Department of Innovation and Technology (DoIT) also began constructing the SmartData Platform, an open-source predictive analytics platform funded with a $1,000,000 award from Bloomberg Philanthropies’ Mayors Challenge.
Schenk has been able to use predictive analytics to leverage the data at his disposal in a number of innovative ways. For example, determining where to place bait for rats by listing which dumpsters are most likely to be overflowing. According to Schenk, this has seen the city become 20% more efficient in controlling rats.
One of the most notable ways that predictive analytics has been used in Chicago is in food inspection. Under Schenk’s leadership, DoIT has collaborated with a number of City departments to put predictive analytics to good use, including the city’s Department of Public Health (CDPH). Chicago, with a population nearing 3 million, has less than three dozen inspectors to oversee the annual checking of the city’s 15,000 food establishments. In order to make the best use of these inspectors, DoIT and CPDH have collaborated to build an app for inspectors that uses predictive analytics to scores food establishments on how likely they are to face a critical violation. This score was based on factors believed to correlate to violations - such as a prior history of critical violations, possession of a tobacco and/or incidental alcohol consumption license, the length of time an establishment has been operating, as well as nearby burglaries, among others. Inspectors can then use this to make sure that they visit those food establishments that most urgently need visiting first. By using this analytics-based procedure, Chicago has been able to discover critical violations an average of seven days earlier than with the traditional inspection method.
Security is another component of Chicago's analytics drive. The city has worked closely with the Chicago Police Department to set up a mobile command team armed with cameras to manage large groups of people at outdoor events, so they can intervene if an area becomes too crowded and a riot seems imminent. The CPD also recently joined forces with the professor of electrical engineering at Illinois Institute of Technology, Miles Wernick, to create a controversial predictive algorithm that generated a ‘heat list’ of 400 individuals that have the highest chance of committing a violent crime. By focussing on likely suspects, the police say that they can concentrate their scarce resources where they are most needed.
Far from the dystopian future shown in Metropolis, this analytics-driven world has already done wonders for the productivity of civil servants, to say nothing of how much they have done for city budgets. Not only this, but it is improving the lives of its citizens as Wells believed it would, rather than seeing them crushed under the yoke of automation and efficiency.