Image Credit: Philip Pacheco / Stringer / GETTY 
Stanford University just released a guide designed to eliminate “harmful language” from the school’s websites and computer code.
Notably, under the “imprecise language” section, the guide wants to replace the term “American” with “U.S. citizen.”
“[‘American’] often refers to people from the United States only, thereby insinuating that the US is the most important country in the Americas,” says the index, which goes on to note the region includes 42 countries between North and South America.
The guide was published Monday, but it’s part of a project launched last May known as the Elimination of Harmful Language Initiative (EHLI).
Additionally, the guide is loaded with more terms it wants to replace, ostensibly to tackle things like racism, homophobia, and ableism.
Notable terms the new index wants to replace:
- “Immigrant” with “person who has immigrated” or “non-citizen.”
- “Abort” with “cancel” or “end.”
- “Child prostitute” with “child who has been trafficked.”
- “Karen” with “demanding or entitled White woman.”
- “Handicap parking” with “accessible parking.”
- “Committed suicide” with “died by suicide.”
- “Tone deaf” with “unenlightened.”
- “Addict” with “person with a substance abuse disorder”
- “Slave labor” with “underpaid.”
Click HERE for the full PDF of desired changes the index wants you to “consider using.”
Tech billionaire Elon Musk has since called out the policy:
“Stanford disapproves of saying you’re proud to be an American? Tweeted Musk. “Whoa.”
Stanford disapproves of saying you’re proud to be an American? Whoa.
— Elon Musk (@elonmusk) December 20, 2022
Below are excerpts from the guide that describe its intended purpose:
“The purpose of this website is to educate people about the possible impact of the words we use,” says the guide’s opening message. “Language affects different people in different ways.”
“The goal of the Elimination of Harmful Language Initiative is to eliminate many forms of harmful language, including racist, violent, and biased (e.g., disability bias, ethnic bias, ethnic slurs, gender bias, implicit bias, sexual bias) language in Stanford websites and code.”