We recently published a review article in Current Epidemiology Reports describing the use of machine learning to measure neighborhood environments in epidemiologic studies. Innovations in information technology, initiatives by local governments to share administrative data, and growing inventories of data available from commercial data aggregators have immensely expanded the information available to describe neighborhood environments, supporting an approach to research we call Urban Health Informatics

Increasingly researchers are turning to machine learning based approaches to work with these large pools of data and develop measures of neighborhood environments. Prominent machine learning applications in this field include automated image analysis of archived imagery such as Google Street View images, variable selection methods to identify neighborhood environment factors that predict health outcomes from large pools of exposure variables, and spatial interpolation methods to estimate neighborhood conditions across large geographic areas. In the review we highlighted successes and cautions in the application of machine learning, particularly highlighting the terms of use and possible legal issues in applying machine learning approaches to Google’s geo-spatial data.

Google’s overall terms of use and those of their Google Maps product (including “Geo Guidelines” included in the Google Maps terms) prohibit essentially every step used in common work flows for applying machine learning to image analysis of Google Street View images. The Geo Guidelines explicitly state that nonprofit and academic uses are not exempt from the terms: “these restrictions apply to all academic, nonprofit, and commercial projects,” and further that they will not grant exceptions: “If your use is not allowed, we are not able to grant exceptions, so please do not submit a request.” The enforceability of Terms of Use contracts is an area of active litigation and, as such, is unclear, but has caused our team to avoid applying machine learning techniques to Street View images.