Democrats Push ‘Racial Equity Audits’ To Cement Control of Tech Companies: Audits call for abolition of standards of 'merit'

A small group of organizations with close ties to Democratic politicians and progressive donors conducts the majority of these audits, which advocates say are needed to promote racial justice. But in practice, equity auditors often push companies to hire more left-wing activists and former Democratic party officials, often from the auditing organizations themselves. The audits also call for the abolition of standards of "merit" and the ability for a special executive to veto any company project.

Racial equity audits are the chief service offered by "diversity, equity, and inclusion" consultants, a cottage industry connected by a revolving door of Democratic staffers and funded by liberal donors. Equity auditors have made a killing from school districts that pay handsomely for consultants to revamp curricula, the Washington Free Beacon has reported. Now, racial equity auditors are setting their sights on corporate America.

Democratic officials have called for audits of major companies. One proposal from House Democrats would fine companies $20,000 a day for not completing biennial, independent "racial equity audits." In June, five Democratic senators called on Google parent company Alphabet to conduct an audit. The Democratic letter cited Color of Change, a left-wing nonprofit pushing for audits.

Last week, Color of Change president Rashad Robinson was invited to testify to Congress and called for "independent auditors" to vet new products from tech companies before they’re released. Robinson did not mention that the "independent auditors" are closely affiliated with Color of Change.

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Color of Change also calls on tech companies to evaluate every employee in "anti-discrimination accountability systems" in performance reviews. According to Color of Change, tech companies should be required to avoid the use of any dataset that "is the product of real-world prejudice or further perpetuates discrimination," a vague definition that could be used to shut down almost any machine-learning research.