The Internal Revenue Service’s practice of social media data mining to determine audit targets could violate federal law on data collection, according to a report.
In a post on Pepperdine Law Dean Paul L. Caron’s Tax Professor blog, a report from Washington State University’s Kimberly A. Houser and Debra Sanders is quoted on the IRS practice of using data from social media posts to help determine who is audited.
“Although historically, the IRS chose tax returns to audit based on internal mathematical mistakes or mismatches with third party reports (such as W-2s), the IRS is now engaging in data mining of public and commercial data pools (including social media) and creating highly detailed profiles of taxpayers upon which to run data analytics,” Houser and Sanders claimed. “This Article argues that current IRS practices, mostly unknown to the general public are violating fair information practices. This lack of transparency and accountability not only violates federal law regarding the government’s data collection activities and use of predictive algorithms, but may also result in discrimination.”
“While the potential efficiencies that big data analytics provides may appear to be a panacea for the IRS’s budget woes, unchecked, these activities are a significant threat to privacy,” they continued. “Other concerns regarding the IRS’s entrée into big data are raised including the potential for political targeting, data breaches, and the misuse of such information. This Article intends to bring attention to these privacy concerns and contribute to the academic and policy discussions about the risks presented by the IRS’s data collection, mining and analytics activities.”
The report also claims that social media pictures showing people at the beach, or with a new vehicle, could be attracting attention from the IRS, who could use such “evidence” against them in an audit.
You can read the full post at TaxProf.