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Artificial Intelligence is Nothing Without Human Ingenuity. Here's Why.

Anything’s possible with the right mix of machines and people working together.

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It’s long been the stuff of sci fi, but increasingly, the practical side of artificial intelligence (AI) is very real. On the consumer side, personal assistants such as Siri, Alexa, and Cortana help automate the simplest of tasks. Meanwhile, AI adoption is also accelerating within the workspace.

According to a recent Spiceworks survey of more than 500 IT professionals, nearly a quarter of large companies have already implemented digital assistants and another 40% expect to follow suit by 2019. For small and medium businesses, that number is closer to 25%.

It’s virtually indisputable that AI (in the form of natural-language processing, machine learning, and deep learning) has tremendous potential to reduce  costs and increase productivity for the enterprise.But its true impact comes to life when combined with human ingenuity.

Just ask David Gutelius, partner and co-founder of the Data Guild, a San Francisco-based venture studio focused on AI, machine learning, and data analytics. Gutelius experienced an AI epiphany in 2006, while part of the DARPA Cognitive Assistant that Learns and Organizes (CALO) at SRI International’s Artificial Intelligence Center in Menlo Park, CA.

DARPA’s goal was to help Army officers save time by automating some of the menial, work-related tasks that filled their day. What Gutelius and his colleagues discovered was the exponential power of AI and humans working together.

“The project really opened my eyes to what’s possible with the right mix of machines and humans,” Gutelius says. “You can do some pretty amazing things—and it’s not just about helping office workers get more done. It’s about helping individuals and teams be more effective.”

One CALO product that was especially formative used machine learning to monitor communications patterns within a community of officers. Called iLink, it “learned” who had expertise on a given subject, how that person’s expertise changed over time, and who trusted whom on a given topic. Using that information, iLink recommended who should be in a virtual room together when new issues or requests arose. It also improved the existing model of communications, which relied heavily on web-based search, redundant broadcast requests for help, and the happenstance of hallway conversations.

That vision for the ultimate potential of AI has stuck with Gutelius and is still a key theme of much of his current work. But creating the perfect blend of human and machine power doesn’t happen by chance. Read on for a few examples of how some organizations are using AI for real benefit.

Look for the Right Opportunities

Healthcare IT start-up Evid Science developed a solution that uses machine learning and natural language processing to pore over hundreds of peer-reviewed articles about drugs in the trial phase. Then it pulls out the essential data points of a drug’s effectiveness, and generates “landscape” reports that compare the efficacy of different treatments. Doctors take it from there, using the AI outputs to inform care decisions. Since medical professionals are often hard pressed to read medical literature on their own time, reports like this provide critical knowledge and automatically serve up different treatment options for their patients.

Evid Science’s solution is particularly effective because it uses AI’s core strengths: performing repetitive tasks flawlessly and having a keen eye for the details.

The real-life implications of applied AI are significant: It would take a doctor up to a year to finish reading a report that Evid Science can complete 500 times faster, without the interruptions. Having access to that intelligence could be revolutionary in providing patients with more effective, evidence-based care.

Solve, Measure, and Expand

AI has also proven useful in HR, as companies look for ways to streamline their screening and hiring, and develop more effective methods of attracting and retaining talent.

For example, ADP DataCloud provides HR professionals with insights and predictive analytics about the performance of individual teams and their company overall. Using customer and third-party data, ADP generates and disseminates reports, and flags concerns such as a team experiencing particularly high turnover, or a star employee whose pay rate is lower than the market rate. ADP DataCloud also calls out reports that other HR professionals have found useful and, over time, learns each customer’s preferences and adjusts accordingly.

ADP DataCloud demonstrates AI’s ability to learn, adjust,and optimize, which is key in amplifying the intelligence and effectiveness of individuals and teams.   

In summing up the effectiveness of ADP DataCloud, ADP Chief Data Scientist Marc Rind says the “insights it generates can provide HR professionals with a better sense of what conversations need to take place, and with whom. It makes them better managers, and better humans.”

Accessible AI to Speed up Operations

AI has clearly become more accessible to organizations: low-cost tools, for example, can help implement AI directly into workflows to speed up operations. Other tools can help automate business processes—taking orders, applying sales discounts, soliciting feedback, managing procurement, tracking content approvals, and more—without a single line of code, complex formulas, or help from IT.

Companies like Disney and Whole Foods, for example, are building and implementing intelligent chatbots into their workflows to streamline repetitive, manual tasks that can increase time savings and productivity.

Whether you’re planning to go big, or just test the AI waters, Gutelius offers this parting advice:“Start with defining and deconstructing the problem, and develop a culture of experimentation and measurement so that you can learn what works and what doesn’t.“

For another example how businesses are using next-gen tools to speed up operations, read how Colliers International used automation to reduce a key business process from 6 months to a week.



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