![]() The education industry has long grappled with conscious and subconscious bias against students from certain language backgrounds, as demonstrated by efforts to ban the teaching of black English vernacular in several states.ĪI has the potential to exacerbate discrimination, experts say. states utilize automated essay scoring systems, according to a Motherboard investigation. “And not only will these machine learning programs pick up bias in the training sets, they’ll amplify it.”Īn interactive map shows which U.S. Bender, a professor of computational linguistics at the University of Washington. “The problem is that bias is another kind of pattern, and so these machine learning systems are also going to pick it up,” said Emily M. ![]() They then predict what score a human would assign an essay, based on those patterns. They’re trained on sets of hundreds of example essays to recognize patterns that correlate with higher or lower human-assigned grades. And as a Motherboard experiment demonstrated, some of the systems can be fooled by nonsense essays with sophisticated vocabulary.Įssay-scoring engines don’t actually analyze the quality of writing. But in the remaining 18 states, only a small percentage of students’ essays-it varies between 5 to 20 percent-will be randomly selected for a human grader to double check the machine’s work.īut research from psychometricians-professionals who study testing-and AI experts, as well as documents obtained by Motherboard, show that these tools are susceptible to a flaw that has repeatedly sprung up in the AI world: bias against certain demographic groups. Of those 21 states, three said every essay is also graded by a human. Three states didn’t respond to the questions. Natural language processing (NLP) artificial intelligence systems-often called automated essay scoring engines-are now either the primary or secondary grader on standardized tests in at least 21 states, according to a survey conducted by Motherboard.
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