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October 30, 2017
The data dilemma: Preparing for the inevitability of AI
By: Nathan Giles

Recently, I was having a serious internal debate about what people think about artificial intelligence (AI) so I did what millions of people do today when faced with a tough question: I asked Siri. Just think how much a part of daily life AI is today as people ask Siri and Alexa questions, check out recommendations from Amazon and Netflix, use live chat for online help, and more.

Facebook, Google, Amazon and Apple are AI pioneers because they have endless data about their customers. After all, AI is completely dependent on the quantity and quality of data available for machines to learn from. The better and deeper the data inputs, the more that machines can recognize patterns, predict responses, adapt to feedback and interact naturally with people and the environment.

The problem for cities? They don’t have the data insight they need for AI. Most major cities have separate ERP systems for different city services and functional areas. There is little to no cross-correlation of data, and the degree of validation and quality within the systems themselves is not uniform. Cities have a long way to go to integrate these various independent databases so that they can train machines on a broader set of data.

There’s also the impact of what I call the “Big Brother” effect. Eighty-five percent of citizens want the same or better digital services from government as they currently receive from the private sector.1 Yet many people resist opening up personal data to any government agency. This is ironic in a world where sharing data with the private sector has become a regular part of life for many of us. Anyone who joins a social media network accepts terms and conditions that give the company broad rights to their personal data and content on the site.

Even so, three-quarters of citizens we surveyed say they lack confidence in government’s ability to safeguard their data.2 This gap between what citizens want and what they are willing to give up to get it could take the oxygen away from AI in cities if it is not resolved. Consider what happened when the City of Portland, Oregon installed vehicle-to-vehicle sensors in city-owned cars and vehicle-to-infrastructure sensors on a three-mile stretch of highway to improve traffic flow and safety. When the city wanted to use anonymous geolocation data from private cell phones in the transportation corridor to improve insights, citizens balked.

There is no denying that AI is here to stay. Of all that cities must do to prepare for AI, changing citizens’ mindsets about data sharing is an urgent priority. It is not too early for education and public relations campaigns that communicate a new value proposition for releasing personal data. The more that cities show the positive impact of AI on daily life—from more efficient public transportation to improvements in public safety—the more likely it is that citizens will begin to see data sharing as a quid pro quo for better quality of life in a modern city.

I would be interested in your views. Please leave a comment or explore other content that covers issues from a cities perspective at https://www.accenture.com/us-en/insight-topic-high-performance-smart-cities.


1 Accenture Public Service Pulse Survey, Digital Expectations, April 2016

2 Accenture Research Survey, A Portrait of Cyber Insecurity, February 2017


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