Google tackles phone spam for US contest


Google has unveiled a new tool that could block nuisance phone calls, in a similar way to email spam filters.

The search giant won a contest run by the US Federal Trade Commission to stop automated telemarketing calls, which are becoming an increasing annoyance.

Google’s scheme uses a computer algorithm to automatically identify the nuisance calls and add numbers to its blacklist.

The search giant says that it has no plans to introduce the system itself, saying it was up to the US authorities to implement the solution.

Google said: 'Robocalls are unpleasant, and our engineers have some ideas for combating the problem.
'At this point, it's simply a proposal for the FTC to consider.'

'The solutions that our winners came up with have the potential to turn the tide on illegal robocalls, and they show the wisdom of tapping into the genius and technical expertise of the public,' said Charles Harwood, Acting Director, FTC’s Bureau of Consumer Protection.

The Federal Trade Commission, the US communications watchdog, says it receives hundreds of thousands of complaints about robocalls every month.

'We’re hoping these winning proposals find their way to the marketplace soon, and will provide relief to millions of American consumers harassed by these calls.'

The contest has also funded individuals to come up with solutions.
Serdar Danis and Aaron Foss will each receive $25,000 for their proposals, which both focus on intercepting and filtering out illegal prerecorded calls using technology to 'blacklist' robocaller phone numbers and 'whitelist' numbers associated with acceptable incoming calls.

Their system could also work as a mobile phone app.

Both proposals also would filter out unapproved robocallers using a CAPTCHA-style test to prevent illegal calls from ringing through to a user.

The judges, FTC Chief Technologist Steve Bellovin, FCC Chief Technologist Henning Schulzrinne, and Kara Swisher, Co-Executive Editor of All Things D, focused on technical considerations alone. They evaluated submissions based on the following criteria: Does it work? (50 percent); Is it easy to use? (25 percent); and Can it be rolled out? (25 percent).

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