It's the 50th anniversary of hip hop, and that’s a great opportunity for Bridget to dig into one of her favorite subjects to nerd out about: trends in audio. In this episode, she breaks down the history of auto-tune. Today it’s incredibly common, but when musicians first started using it there was a huge backlash. Prominent musicians said it was ruining music, and Time Magazine put it on their list of “50 Worst Inventions.” Yet artists like T-Pain and Cher used it to create new sounds that listeners loved, and today it is widely accepted as a valuable tool for legitimate artists to use for making music. The disruptive history of auto-tune, originally derided as a toy before innovators embraced it to create something new, offers lessons for how we should understand AI in 2023. 

<p>It's the 50th anniversary of hip hop, and that’s a great opportunity for Bridget to dig into one of her favorite subjects to nerd out about: trends in audio. In this episode, she breaks down the history of auto-tune. Today it’s incredibly common, but when musicians first started using it there was a huge backlash. Prominent musicians said it was ruining music, and Time Magazine put it on their list of “50 Worst Inventions.” Yet artists like T-Pain and Cher used it to create new sounds that listeners loved, and today it is widely accepted as a valuable tool for legitimate artists to use for making music. The disruptive history of auto-tune, originally derided as a toy before innovators embraced it to create something new, offers lessons for how we should understand AI in 2023. </p>

Marginalized voices have always been at the forefront of the internet, yet our stories often go overlooked. Bridget Todd chronicles our experiences online, and the ways marginalized voices have shaped the internet from the very beginning. We need monuments to all of the identities that make being online what it is. So let’s build them.

There Are No Girls on the Internet

What the History of Autotune Tells Us About the Future of AI

https://api.omny.fm/orgs/e73c998e-6e60-432f-8610-ae210140c5b1/clips/6caadd88-7797-4e0e-b984-b0460155ac20/transcript

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