The search giant says government investigators' demands are "burdensome."

By David Z. Morris
May 27, 2017
May 27, 2017

Apparently Google’s mastery of data doesn’t extend to its own wage information – at least, not when it’s under investigation.

During Friday testimony in a Department of Labor suit accusing Google of widespread and systematic wage discrimination against women, the tech giant’s lawyers argued that continued compliance with government demands for salary records would be too expensive and complicated. Google representatives testified that further reporting would take as much as 500 labor-hours and cost $100,000.

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As reported by The Guardian, Department of Labor lawyers pushed back against Google’s objections, with DoL attorney Ian Eliasoph saying “Google would be able to absorb the cost as easily as a dry kitchen sponge could absorb a single drop of water.”

A Google lawyer claimed that the company had already devoted 2,300 labor hours and $500,000 to complying with parts of the government’s requests for records. A Google manager describing the process said that it had required building new systems while reviewing and revising large amounts of data. Over time, those efforts have become “too burdensome.”

But DoL lawyers pointed out that Google earns millions of dollars annually from government contracts, which require stringent compliance with equal opportunity laws. The Labor Department also attempted to rebuff Google’s claims that these tasks were too complex because of the size of its workforce. Eliasoph said “Google takes routine requests and makes them sound onerous by emphasizing the number of people involved.”

Google’s claims of burden are also odd because the company has previously conducted its own in-depth internal analysis of pay practices, which it says found no gender discrimination. In fact, Google says it has closed both gender and race-based pay gaps in its U.S. workforce. On its page devoted to fair pay best practices, Google describes the analysis behind that conclusion as “a complicated process [that] requires advanced statistics skills and could have serious legal implications for your organization.”

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