IEEE Technology Time Machine Explores Big-Picture Ideas

Conference covered what’s next in big data, cybersecurity, and the Internet of Things

4 November 2016

At this year’s IEEE Technology Time Machine conference, technologists got the opportunity to imagine an ideal future—one in which all diseases have been cured, every country has a stable economy, and telepresence is commonplace. The event encouraged attendees to think big, then step back to figure out how to make lofty goals possible.

Hosted by the IEEE Future Directions Committee, the organization’s R&D arm, the event was held on 20 and 21 October in San Diego. Its theme was “Making the Future.”

The conference kicked off with remarks from 2016 IEEE President-Elect Karen Bartleson, followed by a keynote presentation from Alicia Abella, assistant vice president of cloud technologies and services research organization at AT&T, in Bedminster, N.J. Abella encouraged attendees to reflect on what big-picture goal they want to achieve and who else they need to make it happen.

Participants then attended panel sessions focused on what’s next in technology. Here’s what the future likely has in store in big data, cybersecurity, and the Internet of Things.


Data mining is used for many different purposes, including to help cure diseases and to sell products to targeted customers.

Ritu Chadha, senior research director at Vencore Labs, a communications and information research and engineering company in Basking Ridge, N.J., spoke about her work in analyzing health insurance data to find patients who have rare medical conditions. Not only can that help pharmaceutical companies find patients who could benefit from their treatments, but the data also could help the companies develop new medications. The companies also could use the information to better understand the characteristics of a patient with a specific medical condition—the better to home in on a cure.

Joe Weinman, author of Digital Disciplines: Attaining Market Leadership via the Cloud, Big Data, Social, Mobile, and the Internet of Things, gave examples of how big data could be used to benefit companies and consumers. The makers of the home-based genetic testing kit 23andMe collected data on their more than 1 million customers’ test results, then sold that data for US $60 million to biotechnology company Genentech, of South San Francisco. Genentech is working on a cure for Parkinson’s disease. The data transaction earned 23andMe more money than the annual sales of its kits, which sell for $99 each.

In another example, a utility company conducted a social experiment, issuing reports to its customers that compared their electricity consumption with the average of comparable households nearby. Households dramatically reduced their consumption to compete with neighbors.

Whereas companies used to rely solely on customer demographics to make business decisions, Weinman told attendees that thanks to big data, they now have information about customers’ values, behaviors, and social networks to better understand what motivates them.


A panel on increasing the cybersecurity workforce focused on the need to encourage more young people to join the field. Winnie Callahan, founding director of the University of San Diego’s Center for Cyber Security Engineering and Technology, talked about how cybersecurity is not a typical career choice. “It’s job security,” she said. “It doesn’t matter where you want to work. Every field needs a cybersecurity specialist.”

Callahan stressed the need for cybersecurity educators to continue their own education or to take jobs in industry so they stay up to date.

“The time to admire problems in cybersecurity has come to an end,” she said. With new technologies emerging, including artificial intelligence and the Internet of Things, it’s more important than ever to secure systems and machines, she adds.


At a panel on IoT that looked ahead to the next 20 years, IEEE Fellow Yen-Kuang Chen, principal engineer at Intel, said billions of devices connected to a smartphone is just a baby step in the development of the field. The next level is for those devices to make intelligent decisions on their own by analyzing a situation. If your car breaks down, for example, your smartphone could automatically call for assistance, or request a rental or car service. Eventually all your connected devices will communicate with one another, Chen says. “They will work together to make life simpler for humans,” he said. Take, for example, a personal-assistant robot that does chores. It would know when it’s time to take clothes out of the dryer to fold them, and when dinner cooking in the oven is ready to be served.

“The goal is a higher level of intelligence for each device,” he said, adding, “The key is getting their algorithms right.” One of the challenges is teaching autonomous systems what consumers want when they don’t all want the same thing. One person in a household might prefer the dryer be set on the permanent press cycle, while another might like his air-dried on a clothesline. Research is being done on how devices can address various preferences.

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