A team from Arizona State University's Center for Policy Informatics (CPI), led by Network Associate Member Justin Longo and including Network member Erik Johnston, has just published their research on the concept of “digitally invisible” in the journal Policy & Internet (open access is available here).
With the emergence of “policy analytics” – involving the combination of new data sources (e.g., from mobile smartphones, Internet of Everything (IoE) devices, and electronic payment cards) with new data analytics techniques – as a powerful force for informing and directing public policy, the team explored the possibility that a new type of digital divide was also possible: where those who do not use or own devices like smartphones, IoE devices, and transaction cards do not show up in the “big data” sets that policy analytics presumes. If true, this may result in policy analytics being biased, and policy interventions being misdirected as a result.
Along with CPI colleagues Evan Kuras, Holly Smith, and David Hondula, Longo and Johnson set out to determine whether the concept of the digitally invisible could be shown empirically through an exploratory study with the participation of homeless individuals in Phoenix and the Phoenix Rescue Mission, in the context of extreme heat exposure.
“For those without a smartphone, without a bank account or credit card, without regular and ubiquitous Internet-connected computer access, living beneath and beyond the network of sensors, monitors and data capture points, their existence is being rendered increasingly invisible, with policy developed using a policy analytics approach biased against them, even if unintentionally”, Longo said in a recent blog post. “As a result, policymaking will be blind to their existence and policy based on incomplete evidence will not reflect their reality.”
Abstract: Policy analytics combines new data sources, such as from mobile smartphones, Internet of Everything devices, and electronic payment cards, with new data analytics techniques for informing and directing public policy. However, those who do not own these devices may be rendered digitally invisible if data from their daily actions are not captured. We explore the digitally invisible through an exploratory study of homeless individuals in Phoenix, Arizona, in the context of extreme heat exposure. Ten homeless research participants carried a temperature-sensing device during an extreme heat week, with their individually experienced temperatures (IETs) compared to outdoor ambient temperatures. A nonhomeless, digitally connected sample of 10 university students was also observed, with their IETs analyzed in the same way. Surveys of participants complement the temperature measures. We found that homeless individuals and university students interact differently with the physical environment, experiencing substantial differences in individual temperatures relative to outdoor conditions, potentially leading to differentiated health risks and outcomes. They also interact differently with technology, with the homeless having fewer opportunities to benefit from digital services and lower likelihood to generate digital data that might influence policy analytics. Failing to account for these differences may result in biased policy analytics and misdirected policy interventions.