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The article argues that permitting AI companies to use creative works for training without compensation fundamentally misinterprets fair use and violates the spirit of intellectual property laws. The author contends that AI systems are merely imitative tools that rearrange existing data rather than truly creating new content. Unlike human creators who transform experiences into novel expressions, these algorithms lack the capacity for genuine innovation, risking a cultural environment where art becomes a recursive loop of degraded copies rather than a progressive discipline. Allowing unrestricted data scraping undermines the constitutional purpose of copyright, which is to promote the progress of science and the arts by incentivizing creators. Without financial compensation and permission, the economic incentive for human artists to produce work diminishes significantly. This shift threatens to devalue human labor, potentially leading to a future where cultural output stagnates because fewer individuals can sustain themselves through creative endeavors, thereby halting the natural evolution of art and literature. This perspective is highly relevant to open_data because it challenges the prevailing notion that all data is inherently free for use in open AI development. It highlights the ethical and legal tensions between open access to information and the protection of intellectual property rights. Understanding this conflict is crucial for the open_data community, as it underscores the need to balance technological advancement with the sustainable support of human creators, ensuring that open initiatives do not inadvertently exploit the very cultural resources they seek to utilize.

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Published on 2023-11-08

Open Data

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