University of Washington computer science professor Pedro Domingos is developing CALO, a massive, four-year-old artificial intelligence project to help computers understand human intentions. The DARPA-funded project involves researchers from 25 universities and corporations focusing on many areas of artificial intelligence, including machine learning, natural-language processing, and Semantic Web technologies. CALO, which stands for “cognitive assistant that learns and organizes,” tries to help users by managing information about key people and projects, understanding and organizing information from meetings, and learning and automating routine tasks. For example, CALO can learn about projects and who is involved in those projects, so emails from those people can be given priority and categorized based on subject matter. CALO can also be used to make transcripts of meetings through voice recognition, or perform routine tasks such as purchasing books online, searching for a hotel that meets specific criteria, scheduling meetings, and coordinating people’s schedules. The ultimate goal is to build an artificial intelligence that can serve as a personal assistant that can learn about a user’s needs and preferences and adapt to them without having to be reprogrammed. “It’s an amazingly large thing, and it’s insanely ambitious,” Domingos says. “But if CALO succeeds, it’ll be quite a revolution.”
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The explosion of digital information has brought with it major benefits as well as drawbacks, and among the latter is the paucity of storage space to house all that data and the increasing difficulty of guaranteeing data security and shielding privacy. Factors underlying the surfeit of information include technological innovations, coupled with plummeting prices for digital devices. The volume of digital information increases by a factor of 10 every five years, and Cisco projects that the amount of traffic streaming over the Internet annually will balloon to 667 exabytes by 2013. Accompanying the growth of data is the advent of data scientists, who combine the talents of software programmers, statisticians, and storytellers/artists to sift meaning out of the information deluge. Although the increasing digitization of the world is likely to bring advantages to all kinds of fields and industries via data aggregation and analysis, currently the data flood has greatly contributed to major problems such as the recent financial crisis, where it became apparent that banks and rating agencies were long reliant on models which, although they required a massive amount of data to be fed in, did not mirror actual financial risk.
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Recently discovered problems with the paper records produced by electronic voting machines in Cuyahoga Country, Ohio, could make a recount after next year’s presidential election a disaster. More than 20 percent of the paper printouts from touch-screen voting machines were found to be unreadable. The recount was necessary because the vote counting software crashed twice on election night and the margin of victory was one-half of one percent or less. Election workers found the unreadable ballots while conducting a recount of two races, which involved only 17 of the county’s 1,436 precincts. Board of Elections director Jane Platten says recounting the ballots for the entire county in the 2008 presidential election could take more than a week. Cuyahoga County uses Premier Elections Solutions (formerly Diebold) touch-screen voting machines that store votes on a memory card inside each machine. During the election a paper record of each vote is printed on a long reel of paper that is stored inside the machine. The paper record is used during recounts, but can be damaged or unreadable, usually because of a paper jam while printing. Premier Elections Solutions’ Chris Riggall says the company will investigate the situation.
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