The Canada Revenue Agency is monitoring social media posts of Canadian taxpayers who could be cheating on their taxes. The agency is now focusing on collecting and analyzing many kinds of data for its use, including information publically available online.

“The CRA does practice risk-based compliance, so for taxpayers identified as high risk, any relevant, publicly available information relating to the specific risk-based factors for the taxpayer may be consulted as part of our fact-gathering processes,” spokesperson David Walters told the CBC recently.

Wealthy Canadians who may have offshore bank accounts are among those considered high risk, sources said. The publically available information for such individuals is usually scrutinized.

The privacy commissioner is in the know. The CRA has notified it of its plan to collect publicly available information from social media in connection with “tax fraud and non-compliance risk analysis, audits and investigations.” Tobi Cohen, a spokesman for the privacy commissioner, told the same network.

However, campaigners for privacy such as David Christopher, of the advocacy group Open Media, said his organization opposes government agencies monitoring what Canadians are saying on social media.

“When Canadians post something on Facebook, they believe that they are sharing that with their friends and with their family. They don’t believe that they are sharing that with some government bureaucrat in Ottawa,” he said. Facebook’s privacy settings made the matter more complicated, he added. The Canada Revenue Agency’s use of social media to monitor tax evaders comes even as it continues to use new and improved technology and data analysis to deal with tax fraud.

A report by CBC also talks about an internal document by the CRA, which outlines the agency’s plans to use business intelligence techniques, including using predictive analytics. Predictive analytics is the branch of the advanced analytics which is used to make predictions about the unknown future using many techniques from data mining, statistics, modelling, machine learning, and artificial intelligence to analyze current data to make predictions about future.

The agency is also using other techniques like text mining which can determine high-quality information derived through the devising of patterns and trends through means such as statistical pattern learning. However, as these new techniques are revealed, advocates for privacy remain unimpressed. Privacy experts have long voiced that even if the information is publically available online, it doesn’t mean the owner of the data has authorized anyone to use it.