"We must ensure creators are fairly compensated for data used to train AI models." - Sam Altman, CEO, OpenAI
What do policymakers really want in India
India is weighing an AI framework mirroring past restrictive oversight. Unlike Western nations, India proposes a centralized system. This plan differs sharply from flexible policies in Singapore and Japan. The model introduces a pay and use requirement. Developers must pay owners even with lawful access. This makes India a pioneer in enforcing mandatory payments for AI training data.
Global revenue sharing demands
The committee suggests developers share worldwide earnings once products are commercialized. This applies to models trained on Indian material, creating financial barriers for startups and international firms. Experts question the plan's constitutionality. The body, CRCAT, would set royalty rates for private property. Indian courts previously rejected government attempts to fix prices for intellectual property.
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Impact on local innovation
These regulations might drive developers toward pirated content. Enforcement remains difficult in India. The proposal risks stifling innovation while failing to provide practical protection for copyright owners.
Summary
India's proposed AI framework mandates payments and revenue sharing for training data. By centralizing royalty control, the plan risks being unconstitutional and difficult to enforce. These heavy regulations could hinder domestic growth and inadvertently encourage use of pirated content.Food for thought
Can a government-led royalty system coexist with a global AI market?AI concept to learn: AI Training Data Controversy
The AI training data controversy
centers on how large models are trained on massive internet-scale
datasets that often include copyrighted, proprietary, or personal
content without explicit consent. Creators argue this amounts to
uncompensated use of their work, while AI firms claim fair use, public
availability, or transformative learning. Concerns also include data
bias, privacy leakage, cultural misrepresentation, and lack of
transparency about sources. Governments are struggling to balance
innovation with creator rights, leading to lawsuits, regulatory
proposals, opt-out mechanisms, and calls for licensing frameworks. At
stake is trust, fairness, and the long-term legitimacy of AI
development.
[The Billion Hopes Research Team shares the latest AI updates for learning and awareness. Various sources are used. All copyrights acknowledged. This is not a professional, financial, personal or medical advice. Please consult domain experts before making decisions. Feedback welcome!]
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