Learning desk

MultiAgent EDU StackGather good sources. Teach what matters.
T5TauricResearch/TradingAgentsT5A Man Who Invented Modern AI (Before Everyone Else) – Jürgen Schmidhuber [video]T5GPT-4 finished training four years ago todayT5AI Settles a 25 Year-Old Problem We Left BehindT5What it was like working on LLMs and security at Meta (2022-2026)T5Ask HN: How do you go from writing code to deploying with agents?T5What Happened: OpenAI and HuggingFaceT5Apple says Mac users in China can connect to Alibaba's Qwen AI serviceT5Show HN: Try Benzi – A coding harness/agent beating Claude Code itself on SonnetT5The AI Apocalypse Is HereT3Auto mode is now the default in Claude Code for Pro, Max, and Team plansT5Show HN: Tura – Build agent that uses 80% less token and delivers better resultsT5TauricResearch/TradingAgentsT5A Man Who Invented Modern AI (Before Everyone Else) – Jürgen Schmidhuber [video]T5GPT-4 finished training four years ago todayT5AI Settles a 25 Year-Old Problem We Left BehindT5What it was like working on LLMs and security at Meta (2022-2026)T5Ask HN: How do you go from writing code to deploying with agents?T5What Happened: OpenAI and HuggingFaceT5Apple says Mac users in China can connect to Alibaba's Qwen AI serviceT5Show HN: Try Benzi – A coding harness/agent beating Claude Code itself on SonnetT5The AI Apocalypse Is HereT3Auto mode is now the default in Claude Code for Pro, Max, and Team plansT5Show HN: Tura – Build agent that uses 80% less token and delivers better results
← Dispatches

Assessing the feasibility of collective licensing of in-copyright works as training data for generative AI systems.

Primary research

#652

T1new
Topic
unassigned (set during synthesis)
First seen
2026-07-23 07:15:51
Last seen
2026-07-23 07:15:51

Source raw items (1)

  • Semantic Scholar2026-07-23 07:15:18
    Assessing the feasibility of collective licensing of in-copyright works as training data for generative AI systems.

    Copyright owners have sued several developers of large-scale generative AI systems for copyright infringement because of their uses of massive quantities of in-copyright works as training data for building AI models. Fair use will be the main defense against these charges. If fair use defenses succeed, developers will be free to continue to commercially exploit models already built on copyrighted data as well as to use these data to train new models or fine-tune existing ones. If copyright owners prevail, developers may be liable for billions of dollars of damages. Developers could also be enjoined from further model development on in-copyright works and even ordered to destroy models trained on infringing works. Numerous commentators have proposed collective licensing as a compromise solution to the copyright-training-data dilemma. Other commentators have questioned the feasibility of such a compromise. This article discusses several proposals for collective licensing to enable development of generative AI systems while providing some compensation to copyright owners. It assesses the complex normative, economic, and practical problems that must be addressed if such a regime is to become feasible. It discusses the implications of a licensing mandate not only for the large firms whose models are widely used today, but also for start-ups, research centers, and higher education developers of generative AI systems, as well as the general public.