Google has rolled out a new “inclusive language” function that is intended to steer its users away from what it deems to be politically incorrect words, like “landlord” and “mankind.”
Google Docs introduced the “woke” feature this month that shows pop-up warnings to people typing in words or phrases considered to be non-inclusive, such as “policeman,” “fireman” or “housewife.”
The online word processor’s algorithm will alert them that their chosen terms “may not be inclusive to all readers” and then goes a step further by suggesting alternative, more inclusive words to use.
For example, it might suggest “humankind” instead of the gendered “mankind,” or “police officer” instead of “policeman.”
The new AI-powered language feature, called “assistive writing,” has been widely panned by critics, who have accused the search engine of being both intrusive and preachy.
Vice writers found that when they attempted to type in the words “annoyed” and “Motherboard,” these seemingly innocuous terms were flagged for being insufficiently inclusive.
Meanwhile, a transcription of an interview with former Ku Klux Klan leader David Duke, where he uses the n-word and says a host of other reprehensible things about black people, raised no red flags.
Google’s popular free online document editor raised issues with Martin Luther King Jr’s iconic “I Have a Dream” speech, suggesting that the civil rights leader should have replaced “the fierce urgency of now” with “the intense urgency of now.”
Google Docs’ algorithm also took issue with President John F. Kennedy’s use of the phrase “for all mankind” in his inaugural address, and helpfully suggested swapping it for “for all humankind.”
And even Jesus Christ did not get a pass from the search engine, with the writing feature taking a swipe at the use of the word “marvelous” in the Sermon on the Mount, and suggesting that the Son of God should have used “lovely” instead.
A Google spokesperson said that its controversial assisted writing feature is undergoing “ongoing evolution.”
“Assisted writing uses language understanding models, which rely on millions of common phrases and sentences to automatically learn how people communicate,” the representative said. “This also means they can reflect some human cognitive biases. “Our technology is always improving, and we don’t yet (and may never) have a complete solution to identifying and mitigating all unwanted word associations and biases.”