Transgender, nonbinary and disabled people more likely to view AI negatively, study shows

A more complex picture for race

In contrast to our findings about gender and disability, we found that people of color, and Black participants in particular, held more positive views toward AI than white participants.

This is a surprising and complex finding, considering that prior research has extensively documented racial bias in AI systems, from discriminatory hiring algorithms to disproportionate surveillance.

Our results do not suggest that AI is working well for Black communities. Rather, they may reflect a pragmatic or hopeful openness to technology’s potential, even in the face of harm.

Future research might qualitatively examine Black individuals’ ambivalent balance of critique and optimism around AI.

Policy and technology implications

If marginalized people don’t trust AI – and for good reason – what can policymakers and technology developers do?

First, provide an option for meaningful consent. This would give everyone the opportunity to decide whether and how AI is used in their lives. Meaningful consent would require employers, health care providers and other institutions to disclose when and how they are using AI and provide people with real opportunities to opt out without penalty.

Next, provide data transparency and privacy protections. These protections would help people understand where the data comes from that informs AI systems, what will happen with their data after the AI collects it, and how their data will be protected. Data privacy is especially critical for marginalized people who have already experienced algorithmic surveillance and data misuse.

Further, when building AI systems, developers can take extra steps to test and assess impacts on marginalized groups. This may involve participatory approaches involving affected communities in AI system design. If a community says no to AI, developers should be willing to listen.

Finally, I believe it’s important to recognize what negative AI attitudes among marginalized groups tell us. When people at high risk of algorithmic harm such as trans people and disabled people are also those most wary of AI, that’s an indication for AI designers, developers and policymakers to reassess their efforts. I believe that a future built on AI should account for the people the technology puts at risk.

Oliver L. Haimson, Assistant Professor of Information, University of Michigan

This article is republished from The Conversation under a Creative Commons license. Read the original article.