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liked a Space about 19 hours ago
apple/fastvlm-webgpu
reacted to frimelle's post with ❀️ 13 days ago
πŸ—ΊοΈ New blog post πŸ—ΊοΈ Old Maps, New Terrain: Updating Labour Taxonomies for the AI Era For decades, we’ve relied on labour taxonomies like O*NET to understand how technology changes work. These taxonomies break down jobs into tasks and skills, but they were built in a world before most work became digital-first, and long before generative AI could create marketing campaigns, voiceovers, or even whole professions in one step. That leaves us with a mismatch: we’re trying to measure the future of work with tools from the past. With @yjernite we describe why these frameworks are falling increasingly short in the age of generative AI. We argue that instead of discarding taxonomies, we need to adapt them. Imagine taxonomies that: ✨ Capture new AI-native tasks and hybrid human-AI workflows ✨ Evolve dynamically as technology shifts ✨ Give workers a voice in deciding what gets automated and what stays human If we don’t act, we’ll keep measuring the wrong things. If we do, we can design transparent, flexible frameworks that help AI strengthen, not erode, the future of work. Read the full article here: https://huggingface.co/blog/frimelle/ai-labour-taxonomies
reacted to frimelle's post with πŸ”₯ 13 days ago
πŸ—ΊοΈ New blog post πŸ—ΊοΈ Old Maps, New Terrain: Updating Labour Taxonomies for the AI Era For decades, we’ve relied on labour taxonomies like O*NET to understand how technology changes work. These taxonomies break down jobs into tasks and skills, but they were built in a world before most work became digital-first, and long before generative AI could create marketing campaigns, voiceovers, or even whole professions in one step. That leaves us with a mismatch: we’re trying to measure the future of work with tools from the past. With @yjernite we describe why these frameworks are falling increasingly short in the age of generative AI. We argue that instead of discarding taxonomies, we need to adapt them. Imagine taxonomies that: ✨ Capture new AI-native tasks and hybrid human-AI workflows ✨ Evolve dynamically as technology shifts ✨ Give workers a voice in deciding what gets automated and what stays human If we don’t act, we’ll keep measuring the wrong things. If we do, we can design transparent, flexible frameworks that help AI strengthen, not erode, the future of work. Read the full article here: https://huggingface.co/blog/frimelle/ai-labour-taxonomies
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