AI Training Data Meets Copyright: How Publishing Can License Content at Scale w/ Julie... скачать в хорошем качестве

AI Training Data Meets Copyright: How Publishing Can License Content at Scale w/ Julie...

AI has been trained on the world’s writing. Now, we have to figure out how creators prove ownership, set permissions, and get paid when their work is used. Julie Trelstad has spent 30 years inside publishing’s biggest technology shifts, from desktop publishing to eBooks to print-on-demand to self-publishing. In this episode, she explains why AI is forcing publishing into a new kind of rights era, one where piracy and fast imitation can flood the market within days of a book launch. Julie is Head of US Publishing at Amlet.ai and runs Paperbacks & Pixels. She walks through what “AI rights” means in practice, why book rights sales already power much of the industry, and how systems like ISCC fingerprinting can make ownership and usage terms machine-readable without exposing the full text. Daniel and Julie also dig into what happens when high-value content moves behind paywalls, why smaller domain models will need licensed, high-quality sources, and what fair compensation could look like when content is used for training, research, or generation. 🔑 What You’ll Learn in This Episode ✅ The six publishing waves Julie has lived through, and why eBooks changed the ecosystem✅ Why AI imitation and piracy hit bestsellers first, and how that changes incentives ✅ What “AI rights” includes beyond training, including research and generative use ✅ How ISCC-based fingerprinting can prove provenance without sharing the full book ✅ Why paywalls and licensing are reshaping what high-quality data is available to models ✅ A practical way to think about “original vs. derivative” in an AI-assisted world🔗 Resources & Links 🤝 Connect with Julie on LinkedIn:   / julietrelstad   🌐 Julie’s work at Paperbacks & Pixels: https://paperbacksandpixels.com/ 🧩 Amlet.ai (AI content registry): https://amlet.ai/ 📚 StreetLib (distribution + registration path mentioned in the episode): https://www.streetlib.com/ 📩 Subscribe to the Artificial Insights newsletter for key takeaways: https://manary.haus/podcast/#haus 👉 Have a guest in mind? Reach out to Daniel at daniel@manary.haus💬 Know a product leader or publisher trying to source high-quality data responsibly? Send them this episode.