AI Copyright Quietly Redrawing Legal Lines
Twelve consolidated copyright suits filed by US authors and news outlets against OpenAI and Microsoft have landed in the Southern District of New York, elevating the question of whether the extent of human input in AI training crosses the threshold of lawful fair use. The judicial panel cited shared legal and technical claims involving unauthorised use of copyrighted material, notably books and newspapers, as justifying centralised legal proceedings.
The US Copyright Office added its authoritative voice in May, questioning whether AI training on copyrighted texts can be deemed fair use, particularly in commercial contexts. The Office clarified that while transformative use may be permissible in research, mass replication or competition with original works likely exceeds established boundaries. Its report highlighted that the crux lies in purpose, source, market impact and guards on output — variables which may render AI models liable under copyright law.
A pivotal case involving Thomson Reuters and Ross Intelligence offers early legal clarity: a court ruled that Ross improperly used Westlaw content, rejecting its fair use defence. The judgement centred on the need for AI systems to 'add something new' and avoid copying wholesale, reinforcing the rights of content owners. This ruling is being cited alongside the US Copyright Office's latest guidance as foundational in shaping how courts may assess generative AI.
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Legal practitioners are now navigating uncharted terrain. Lawyers such as Brenda Sharton from Dechert and Andy Gass of Latham & Watkins are at the cutting edge in helping judges understand core AI mechanics — from training data ingestion to output generation — while balancing copyright protection and technological progress. Their work emphasises that this lifetime of litigation may not be resolvable in a single sweeping judgment, but will evolve incrementally.
At the heart of many discussions lies the condition for copyright protection: human authorship. The US Copyright Office reaffirmed in a February report that merely issuing a prompt does not satisfy the originality requirement. It stated that current systems offer insufficient control for human authors to claim sole credit, and that copyright should be considered case‑by‑case, grounded in Feist's minimum creativity standard. Critics argue this stance lacks clarity, as no clear threshold for the level of human input has been defined.
Certain jurisdictions are taking diverse approaches. China's Beijing Internet Court recently ruled in Li v Liu that an AI–generated image was copyrightable because the plaintiff had provided substantial prompts and adjustments — around 30 prompts and over 120 negative prompts — demonstrating skill, judgment and aesthetic choice. In the United Kingdom, the Copyright, Designs and Patents Act 1988 attributes authorship to the person who undertakes 'arrangements necessary' for a computer‑generated work, hinting that both programmers and users may qualify as authors depending on context.
In contrast, India's legal framework remains unsettled. Courts have emphasised human creativity in ruling on computer‑generated works, as seen in Rupendra Kashyap v Jiwan Publishing and Navigators Logistics Ltd v Kashif Qureshi. ANI, India's largest news agency, has brought forward a high‑profile case against OpenAI, with hearings held on 19 November 2024 and 28 January 2025. The Delhi High Court has appointed an amicus curiae to navigate this untested area of copyright, with Indian lawyers emphasising that the outcome could shape licensing practices and data‑mining norms.
India reserves copyright protection for creations exhibiting 'minimal degree of creativity' under its Supreme Court rulings such as Eastern Book Co v Modak. In February 2025, experts noted that determining whether AI training qualifies as fair dealing or whether generative AI outputs amount to derivative works will be pivotal. Currently, scraping content for AI training falls outside clear exemptions under Indian law, though the Delhi case could catalyse policy reform.
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Amid these legal fires, signs point toward statutory intervention. In the US, the Generative AI Copyright Disclosure Act would require developers to notify the Copyright Office of copyrighted works used in training models at least 30 days before public release. While UK policymakers are consulting on a specialised code of practice, India lacks similar formal mechanisms.
The evolving legal framework confronts a fundamental philosophical and commercial dilemma: making space for generative AI's potential innovation without undermining creators' rights. AI developers contest that mass text and data mining fuels advanced models, while authors and journalists argue such training must be controlled to safeguard original expression. Courts appear poised to strike a balance by scrutinising the nuance of human input, purpose and impact — not by enacting sweeping exclusions.
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