Speech recognition algorithms may also have racial bias

Enlarge / Microphones are how our machines listen to us. (credit: Teddy Mafia / Flickr)

We're outsourcing ever more of our decision making to algorithms, partly as a matter of convenience, and partly because algorithms are ostensibly free of some of the biases that humans suffer from. Ostensibly. As it turns out, algorithms that are trained on data that's already subject to human biases can readily recapitulate them, as we've seen in places like the banking and judicial systems. Other algorithms have just turned out to be not especially good.

Now, researchers at Stanford have identified another area with potential issues: the speech-recognition algorithms that do everything from basic transcription to letting our phones fulfill our requests. These algorithms seem to have more issues with the speech patterns used by African Americans, although there's a chance that geography plays a part, too.

A non-comedy of errors

Voice-recognition systems have become so central to modern technology that most of the large companies in the space have developed their own. For the study, the research team tested systems from Amazon, Apple, Google, IBM, and Microsoft. While some of these systems are sold as services to other businesses, the ones from Apple and Google are as close as your phone. Their growing role in daily life makes their failures intensely frustrating, so the researchers decided to have a look at whether those failures display any sort of bias.

Read 10 remaining paragraphs | Comments

from Ars Technica https://ift.tt/39bhxNq