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Enregistrement W7106734384 · doi:10.5281/zenodo.17708435

Case Notes: Asian News International (ANI) v. OpenAi

2025· article· en· W7106734384 sur OpenAlexaboutno aff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Langueen
DomaineComputer Science
ThématiqueLaw, AI, and Intellectual Property
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIntellectual propertyReputationFair useJurisdictionOrder (exchange)Public domainCopyright ActGovernment (linguistics)Digital contentCopyright infringement

Résumé

récupéré en direct d'OpenAlex

CASE NOTES ON: ASIAN NEWS INTERNATIONAL (ANI) v. OPEN AI - CITATION: CS(COMM) 1028/2024 INTRODUCTION: The swift growth of artificial intelligence (AI), especially huge language models like OpenAI’s ChatGPT, has brought up important legal and ethical questions around ownership, data consumption, and intellectual property. On November 19, 2024, ANI, an esteemed Indian news group, filed a claim against OpenAI and its founders in the Hon’ble Delhi High Court, asserting copyright infringement, content misappropriation, and false attribution. In a rapidly transforming digital environment, this case poses significant problems regarding the relationship between artificial intelligence, data ownership, and intellectual property rights. Similar cases have been reported by media outlets in the United States, Canada, and Europe, and this case is part of a larger global controversy about the use of restricted materials in AI model training. ISSUES: • Does copyright infringement under Indian law apply when an AI model works on copyrighted content without a licence? • Could the defendants’ use of the plaintiff’s copyrighted data in order to generate responses for its users represent a copyright violation? • Can the Defendant’s use of the Plaintiff’s copyrighted data comply with Section 52 of the Copyright Act of 1957’s reference to “fair use”? • Given that OpenAI’s servers reside elsewhere and that ChatGPT is accessible in India and is said to have an impact on ANI’s operations and reputation thereby, do Indian courts have jurisdiction over this case? KEY ALLEGATIONS AGAINST OpenAI: • ANI claims that three main sources of data are accessed by ChatGPT, OpenAI’s large language model for AI machine learning: public data, data from third-party partners, and data that OpenAI directly examines. According to ANI, OpenAI inappropriately exploited its knowledge to train its AI model because it fits into these categories. • While part of its content may be available to the public, ANI argues that certain headlines, interviews, and reports are only available to subscribers. Because OpenAI lacks a license to copy, keep, or utilize these materials for training, ANI argues that OpenAI has no right to use them. • ANI, meanwhile, asks for ₹2 crore in damages and a permanent injunction to prevent OpenAI from using its intellectual property going beyond. ANI’s THREE MAIN CAUSES OF ACTION: • ANI asserts that by retaining, applying, and transferring its copyrighted assets for training purposes without authorization, OpenAI violated its copyright. Even if the content belongs to the public, OpenAI still needs a license to use it. • As indicated by ANI, ChatGPT delivers answers that are either replicates of its own content or somewhat similar to it. This raises questions about suspected copyright law illegalities and prohibited usage of ANI’s intellectual property. • ANI cites occasions in which ChatGPT accomplished answers that falsely or inaccurately affiliated news or interviews with people or organizations. OPENAI’s DEFENCE: • Because ANI’s ideas are open to the public, OpenAI contends that its activities are legally justified. ANI has access to the “Robots.txt” protocol, a common strategy for preventing web crawlers from indexing content, to prevent OpenAI’s web crawlers from interacting with its content. • OpenAI focused on that although the prospect of the goal of multiple legal cases in the US, Canada, and Germany, no court has issued an injunction or suspected that OpenAI has violated anyone’s copyright. This includes chances in which other media outlets have made comparable accusations. • OpenAI believes itself to be open about its business tools, including sharing information about how it uses data on its website. It defends that the AI creates responses based on a variety of data sources, including publicly accessible content, rather than preserving ANI’s content verbatim. • OpenAI contends that ANI fails to provide proof of any specific instances of infringement and disputes the imitation of ANI’ s content that was copied. OpenAI states that the training equipment is not saved in a way that makes it possible to generate the same information when communicating with ChatGPT. • OpenAI has denied monitoring any content. This includes ANI’s exclusive content that is either behind pay rules or only accessible through a subscription. According to the defense, OpenAI’s technology does not access licensed or subscription-based content until it is accessible to the public as a whole. • Furthermore, OpenAI contradicts the allegations of illicit attribution, asserting that ANI has not filed any complaints about attribution flaws. According to OpenAI, any errors found have been swiftly resolved. The defense declares that although the model might sometimes yield inadequate outcomes, these sorts of scenarios are seldom and are usually addressed. • Consequently, OpenAI, ANI currently intends to resort to the “blocklist” feature to discourage its crawlers from scraping ANI’s website, and OpenAI adhered to this request. OpenAI assumes that its systems remain the source of content that appears to be relevant to ANI’s content despite ANI’s attempts to impede access, even though this could come from other public data or third-party partners. THE COURT RULED: The court recorded that ANI had placed OpenAI’s web crawlers on a blocklist, promising that OpenAI’s web crawlers would no longer be eligible to access ANI’s website. The court understood the objection regarding territorial jurisdiction but agreed with the case to proceed, with the jurisdiction issue to be addressed in future hearings. To facilitate ensuring that the case is reviewed from all relevant angles, the court has also appointed an Amicus curiae to help in the legal process. ROLE OF AMICUS CURIAE: Two amicus curiae, Mr. Adarsh Ramanujan and Dr. Arul George Scaria, were picked by the Delhi High Court to render an objective expert counsel on the applicable copyright and innovation concerns. Their position is to assist with the court negotiate the complex connection underlying digital rights, copyright law, and robotics. Their participation is important, especially after the advent of artificial intelligence wasn’t anticipated when India’s copyright and intellectual property rules were first enacted. As a result, Indian jurisprudence on AI is still growing, and these laws lack particular provisions solving the legal barriers brought on by AI technologies. IMPLICATIONS: The case highlights essential issues around media business rights in the era of artificial intelligence. ANI’s allegations underline the complexity of data usage, copyright, and attribution in the digital age, while OpenAI believes that its techniques are lawful and open. This case might establish major precedents for AI regulation and media industry intellectual property protection. More legal issues that require explanation on how content can be used, shared, and associated in an increasingly related world are expected to occur as AI technology improves. This is about the rules and regulations that will supervise India’s rising AI ecosystem, which is estimated to be valuable around $22 billion by 2027, not merely ChatGPT or ANI. Nowadays, courts need to balance protecting creators with stimulating innovation. And they have to do this in the absence of current laws regarding AI. LEGAL PROVISIONS: In accordance with Section 62 of the Indian Copyright Act, 1957, a copyright owner may file a lawsuit in any place where they live or conduct business, which helps ANI even though the data processing is done elsewhere due to its Delhi headquarters. Based on OpenAI, lawsuits must be filed in the defendant’s home or premises because of the cause of action under Section 20 of the Code of Civil Procedure. Indian courts typically do not have jurisdiction over OpenAI because its servers reside elsewhere, and the company does not have a physical presence in India. The court has postponed its final jurisdictional decision, but it is inclined to recognize jurisdiction under Section 62 given ANI’s actions in Delhi and ChatGPT’s accessibility throughout India. Support from Dr. Arul George Scaria and Adarsh Ramanujan can be observed in Amicus Curiae, which highlights that Indian law regulates digital services in the country. The Information Technology Act, 2000’s Section 75 makes it clear that its provisions apply to commit by anyone outside of India, as long as they involve Indian computer systems or networks. LIABILITY OF OUTPUTS CREATED BY AI: • Whether ChatGPT’s output, which periodically approaches ANI’s original content, violates copyright. OpenAI adopts an entirely distinct view than ANI, which continues to argue that any rendition of its content, even if it is converted into AI output, contravenes its exclusive rights. • OpenAI indicates that the model does not “store” or obtain the original articles in a recognized or retrievable form via virtualization and subsequent processing. Therefore, even if outputs occasionally show similarities, they are not instances of direct copying but rather an emergent part of the model’s learning process. • In response to ANI Media’s copyright assertions, OpenAI defended its decisions by accentuating its “opt-out” mechanism, that allows content owners to disable its web crawlers via robots.txt directives or domain blocklisting. ANI’s legal team countered that the issue was not entirely determined by censoring its domain in October 2024 because its news content could still be accessed indirectly through mirror sites or third-party platforms that replicate its articles, thereby permitting unauthorized use. CONCLUSION: With the nation’s market expected to reach USD 17 billion by 2027, India has already established itself as an influential pla

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Communication savante, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,985
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,000
Communication savante0,0020,001
Science ouverte0,0030,003
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0070,007

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,046
Tête enseignante GPT0,262
Écart entre enseignants0,217 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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