The value of GIS in Big Data and AI to empower civic decision makers
Originally published in GIS Professional, December 2016 issue
I first encountered GIS while studying geo-collaborative decision-making for crisis management over a decade ago. Back then, GIS seemed liked an obscure field and its software used by a select few who could install and navigate the various menus / sub-menus to produce some results.
A lot has changed since then. When I re-entered graduate school a few years back to study cities using data at NYU’s Center for Urban Science and Progress, I re-discovered GIS. Except this time, almost everything was on the web and the cloud.
Platforms such as Carto, Tableau, Mapbox, an ever present and often dismissed open source movement has exponentially improved usability and made GIS accessible to masses of non-native technology users.
The ability to rapidly create accurate, functional and customizable data-driven narratives is a powerful skill that is actively shaping decision-making at various levels of government. GIS is an enabling medium for this.
A concept that I have found helpful to bridge the worlds of urban operations, public policy and GIS development is the Common Operational Picture or COP. This is a concept that originated in the US military and relies heavily on a GIS to allow many stakeholders make decisions using a common platform.
Simply put, a COP offers a “bird’s eye view” of changing data landscapes.
The COP is an ideal use-case for many GIS platforms used in data-intensive and collaborative environments. The COP is “first and foremost, a visual representation of relevant information characterizing a situation” (USJFCOM, 2008). It represents a centralization of information to allow shared understanding. This definition has many similarities with the ethos of the professional GIS community. The COP is an ideal sense-making tool to help decision makers avoid being overwhelmed by the fire-hose effect that big data usually has.
Ben Northrop, a prolific software blogger writes that “software development is fundamentally about making decisions” and so I extend that by stating that geographically situated software development should focus on decision making that much more because location, navigation and spatial thinking are unique elements of higher order cognition.
Geographically situated software development should focus on decision making that much more because location, navigation and spatial thinking are unique elements of higher order cognition.
ARGO actively uses the the common operational picture concept in urban and municipal settings.
Our Street Quality Identification Device / SQUID project uses a low-cost approach to collect hundreds of thousands of images of streets, combine it with ride quality data, and present this data on a map to allow cities make a simple decision in as open and equitable manner as possible.
Which city streets to repair sooner than others?
The COP is also useful to implement equitable decision-making.
Creating a GIS powered COP lowers barriers to create shared goals and manufactures common ground, a vital need in contested and bureaucratic settings.
A usable GIS and situation awareness through COP development is therefore vital to reduce the frictions between generating data and generating good decisions.
This is something that ought to be standard in future government operations at any level.
Walter Kirn, says this about Artificial Intelligence in a 2016 essay in Harper’s magazine:
“In a field where reality testing is difficult under the best of circumstances, where inauthenticity can be assumed, an AI takeover may prove undetectable”.
The hope and hype of AI to automate decision-making in difficult information environments is a powerful signal guiding technology development and adoption. Yet, there is evidence to suggest that in such settings, AI is better applied to complement rather than substitute human decisions. Again, GIS through the COP lens offers many solutions.
A component of our work with the California Data Collaborative, a collaborative coalition of public water managers, combines earth observations and satellite imagery with image classification techniques to classify irrigable and landscape area, a key missing data point for CA water managers.
We actively work to carefully combine advanced analysis with decision making tools in municipal contexts to identify potential efficiencies that, not only assist better delivery of critical public services, but also help guide informed and fair policy-making.
To conclude, some of this may just seem like a rebranding of well-understood GIS concepts. At ARGO, we believe that it is important to translate entrenched vocabularies or technical jargon from one world (GIS) to another (Public policy, planning and municipal operations).
To this end, the “COP” is useful to organize collective energies around generating shared understanding and empowering decision makers. The GIS community has overcome many technical and organizational challenges around geographical data that if abstracted can be helpful to un-tangle similar yet obscure challenges in the public domain.
