Transgender, nonbinary and disabled people more likely to view AI negatively, study shows
And yet, while AI now influences high-stakes decisions such as what kinds of medical care people receive, who gets hired and what news people see, these decisions are not always made equitably. Research has shown that algorithmic bias often harms marginalized groups. Facial recognition systems often misclassify transgender and nonbinary people, AI used in law enforcement can lead to the unwarranted arrest of Black people at disproportionately high rates, and algorithmic diagnostic systems can prevent disabled people from accessing necessary health care.
These inequalities raise a question: Do gender and racial minorities and disabled people have more negative attitudes toward AI than the general US population?
I'm a social computing scholar who studies how marginalized people and communities use social technologies. In a new study, my colleague Samuel Reiji Mayworm, Alexis Shore Ingber, Nazanin Andalibi and I surveyed over 700 people in the US, including a nationally representative sample and an intentional oversample of trans, nonbinary, disabled and racial minority individuals.
We asked participants about their general attitudes toward AI: whether they believed it would improve their lives or work, whether they viewed it positively, and whether they expected to use it themselves in the future.
The results reveal a striking divide. Transgender, nonbinary and disabled participants reported, on average, significantly more negative attitudes toward AI than their cisgender and nondisabled counterparts.
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