Artificial Intelligence Intersects with Smart Cities

In his fourteenth post in the series, Marshall Kirkpatrick focuses on the intersection between artificial intelligence and smart cities. By way of reminder, Marshall launched a 30 day series that explores the intersection between AI and the various innovation components on my emerging futures visual.

As he has in each post, Marshall identifies the key subject matter experts that sit at the intersection of AI and the visual component in question. In the case of smart cities, the key influencers are: Rick Robinson, Patricia Gandit, and Michael Jansen. Here is the foresight and related future scenarios identified at the intersection of Artificial Intelligence and smart cities (taken straight from Marshall’s post):

A Well-Oiled Machine: AI could orchestrate and optimize flow of traffic and allocation of energy throughout a city. That could be through smart traffic control, or it could be through variable energy pricing in your home incentivizing you to consume in ways that maintain the balance city-wide. AI could help analyze a huge amount of behavior and environmental data to know when a population’s behavior is as expected — and when it’s time to sound an alarm.

Emergent Pattern Awareness: AI could be deployed in smart cities to discover correlations between circumstances. Perhaps things about citizens and cities that we may have suspected but didn’t have a clear model of, perhaps unknown unknowns. By dropping the cost of thesis creation to near zero, and evaluating every possible permutation of multiple data sets intersecting, we may learn things about ourselves we never thought to ask. On a human scale, this is reminiscent of the time in US history when census data and housing loan data were both made available for analysis by computers. Researchers discovered a clear pattern of racial discrimination in mortgage lending against African American families in traditionally white neighborhoods. Legislation was then passed. Now imagine that same kind of measurability and analysis of data about civic life scaled up to 21st century Big Data levels.

Note: in a recent post on The Smart City another interesting example of pattern awareness is provided:

“An interesting example is the use of acoustic sensors that are calibrated to detect gunshots. Some cities in the United States have deployed these sensors in areas of gun violence and discovered some shocking information. Police departments had historically assumed that residents called the police 80% of the time when shots were heard. And thus the police thought they had a fairly accurate measure of street gun violence. In San Francisco, after the sensors were in place, the police discovered that residents called the police only 10% of the time when shots were heard. In Oakland, California, the 911 call rate for shots fired was only 22%. Prior to the sensors, these police departments were operating on highly inaccurate information about the level of gun violence in certain neighborhoods. With this new information, police can now plan their patrols differently and better target areas to reduce gun violence.”

AI Empowered Citizenry: Some say a city isn’t really smart until it includes its citizens’ perspectives and participation. Others go further and say a city isn’t smart until it helps its citizens be smarter, themselves. Picture artificial intelligence doing the number crunching to co-ordinate networks of people retrofitting cities into smarter, more sustainable places, or helping individual citizens make wiser choices, not just for themselves, but for the collective whole as well.

In The Smart City post mentioned above, I described the compelling reasons for city leaders to act. For the first time in history, more than 50% of the world’s population lives in cities, and that percentage moves to 70% by 2050. In addition to rapid urbanization, the global population of people over 60 will double by 2050, putting additional stress on supporting the vulnerable. These two trends will amplify the challenges of an already challenged urban environment, increasing the focus on the Smart City agenda. According to a recent study, the number of smart cities across the world is set to quadruple between 2013 and 2025. With this unprecedented access to information, the intersection with artificial intelligence enables the Smart City to deliver new levels of efficiency, effectiveness, safety, reliability, and higher levels of service.

The intersection analysis that Marshall pursues via his posts is a great example of deriving the foresight required to navigate in this emerging future. Future thinking — the rehearsal of our emerging future — is increasingly a critical but complex piece of the equation going forward. The other posts in the series on AI and intersections can be found via the links below: