Can Artificial Intelligence Outsmart Cities?

June 06, 2017

Artificial intelligence (AI) is a natural fit for the smart cities movement. Just consider the billions of data points bouncing through a maze of intertwined city departments, magnified exponentially by all aspects of the Internet of Things (IoT).

It could be argued that AI will eventually be the reason cities are truly smart. However, until then, the “smartness” in many cities is more about the capturing data exhaust, rather than gaining insight from it.

The power of AI in the healthcare industry has been in its ability to aggregate billions of data points from medical cases, scholarly journals, drug trials and qualitative input from physicians and surgeons to derive  insights that humans alone could not achieve.

In this setting, success is determined by the health of the patient. In some cases, the improvement is quite dramatic; in others, it’s a matter of extending lifespan with some improvement in quality of life. Whether it’s used to reduce cost or improve treatment, AI is a patient-centric strategy.

So to what degree are cities able to get similar outcomes from AI, changing “patients” to “citizens” looking for improved quality of life in their urban environs?

One could argue that the intelligence needed to make AI work in this situation should include “citizen-generated” information, just as much as other sources. (I know many will argue that IoT feeds indirectly reflect the citizenry. But this is much like saying that my energy bills reflect how much I like cooking versus using my treadmill.)

It also begs the question of where data analytics leaves off and artificial intelligence begins. At what point does a city need to invest in cognitive computing, machine learning and AI?

One city CTO described investing in AI for basic data analytics as the equivalent of using a “chainsaw to carve your turkey.” And in tight economic times, urban taxpayers want to be sure that investments in artificial intelligence provide a tangible return.

Mayors and city councils want to be sure that AI technology can in fact outsmart the human technologists.

Most reasonably minded AI and data science professionals will tell us the biggest challenge is knowing what insights the city wants to gather in advance of the initiative. Some deployments fail because the task simply isn’t feasible, and in some cases, the investment magnifies the fact that data was totally unrelated and would likely remain so.

In other cases the resulting insight can outsmart the city. In this case, the intelligence is good but the city can’t afford to implement the recommended solution, or doesn’t have the skillsets to address the problem.

This goes back to the primary question that needs to be asked: “Will we be prepared to — and can we afford to — execute on the findings in a timely fashion?”

Nary a city official wants to explain to voters that the AI investment produced some extremely compelling findings, but unfortunately, the solutions are financially unattainable.

Frank Cutitta is the Editor-at-Large of Smart & Resilient Cities.

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