Enterprise IT shops are finding that artificial intelligence (AI) is not just for robotics anymore. Science fiction and blockbuster movies may portray AI technologies as the brains running robots trying to take over the human race, but the technology today is being used for far more benign purposes.
While AI is being used in smart phones and self-driving cars, it is also working its way into the enterprise to filter spam out of email, handle complicated scheduling or detecting fraud in big data deployments.
IT and AI
“I think IT probably needs artificial intelligence,” said Stephen Smith, a professor who specialises in robotics and AI at Carnegie Mellon University. “There are increasing cyberattacks we’re dealing with. We have bigger, more complex problems with all the issues arising out of the explosion of the Web and all of our big data. We’re already using AI It’s already there. I think AI in the enterprise is going to start to cascade.”
At last month’s AAAI-15 conference in Austin, Texas, participants from Xerox Corporation, Ford Motor Company and NASA’s Ames Research Centre demonstrated the artificial intelligence applications that their organisations are using.
Artificial intelligence is about making intelligent computer systems, such as robots or software that handles financials data, that can learn as they go and handle tasks that traditionally required people to get the work done.
Despite fears about the development of AI and its sci-fi reputation, the technology is not new to the enterprise. It has simply been used under different names, such as email filtering or speech recognition, instead of the umbrella term of AI The technology is also appears to be enjoying a growth spurt in the enterprise as executives and IT managers find artificial intelligence well suited to taking on increasingly complex business problems.
AI everywhere
Google uses AI in search. The iPhone’s digital assistant Siri is based on artificial intelligence, as is Internet of Things technology that is starting to be used in homes.
AI researchers and industry analysts say these examples are just early steps in using AI in the enterprise.
For instance, artificial intelligence is being used to prioritise email, for planning and scheduling, culling through big data, speech recognition and security.
“Without a lot of headlines, it’s everywhere from customer service and better routing to finance and fraud detection,” said Oren Etzioni, CEO,Allen Institute for Artificial Intelligence. “It’s actually inevitable that we will have more AI in the enterprise because of several trends coming together, including more compute power, desire for productivity growth and the big data we’re dealing with.”
Enterprises are increasingly turning to artificial intelligence because of the explosion of data they have to manage.
“The notion that a human analyst can look at all of this data unaided becomes more and more implausible,” Etzioni said. “You can’t have a person sitting there watching Twitter to protect your brand. There are just too many tweets. You need help protecting your brand. You need tools. You need AI tools.”
Xerox PARC and AI
Xerox’s well-known PARC lab uses artificial intelligence to detect fraud and abuse in health care data.
Eric Bier, a principal scientist at PARC (Palo Alto Research Centre), which is known for major roles in the development of the Ethernet and laser printing, talked to an audience at the AAAI-15 conference about its Xerox Program Integrity Validator or the XPIV system.
Bier, and the XPIV team, are working with the federal government to find fraud in areas such as Medicare, the government’s health insurance program for those 65 and older.
“There’s a tremendous amount of data to go through,” Bier said. “The old phrase of ‘looking for a needle in a haystack’ comes to mind, but then at least you know what a needle looks like. People are clever. You need algorithms that learn from the data and find behaviours that are odd that will call someone’s attention to something funny going on.”
The PARC AI program culls through enormous data sets looking for patterns that signal what could be suspicious behaviours. For instance, the program looks for repeated instances of patients passing by several pharmacies to go to one on the other side of town, patients who buy nothing but narcotics or patients who continually use different pharmacies.
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