The Double-Edged Sword of Open AI: MLCommons and Hugging Face's Massive Speech Dataset and Its Ethical Implications
Massive AI speech dataset raises bias and ethical concerns.
Matilda
The Double-Edged Sword of Open AI: MLCommons and Hugging Face's Massive Speech Dataset and Its Ethical Implications
The democratization of artificial intelligence (AI) hinges on accessible, high-quality data. Recently, MLCommons, a prominent AI safety working group, partnered with Hugging Face, a leading AI development platform, to unveil a groundbreaking initiative: the Unsupervised People's Speech dataset. This ambitious project aims to provide researchers with an unprecedented volume of voice recordings, potentially revolutionizing speech technology. While the potential benefits are undeniable, the release of such a massive dataset raises critical ethical questions about bias, consent, and the responsible development of AI. The Unsupervised People's Speech dataset boasts over a million hours of audio, encompassing at least 89 languages. MLCommons explicitly states its goal is to fuel research and development across various facets of speech technology, with a particular emphasis on expanding natural language processing (NLP) capabilities beyond English. The organization envisions this …
