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Archive
Rather than banning or blindly embracing AI tools, Netflix adopts a principled governance framework that respects human creativity, legal boundaries, and industry norms...
...while allowing space for innovation. This governance approach is especially timely as studios face legal challenges and AI hallucination risks that could damage reputations, IP, or brand equity.
The outcome of X v. Apple and OpenAI could define not just the balance of power in tech, but the principles that govern AI’s deployment at scale.
It’s a flashpoint in the battle for control over AI’s interface with consumers. Courts, regulators, and innovators around the world will be watching closely.
If Apple deserves protection for its chips and sensors, so too do writers, researchers, and artists whose creations power the AI age.
Stealing valuable intellectual material—whether hardware specs or copyrighted works—is unacceptable, even if the end product is different or "innovative."
Creativity in diffusion models doesn’t come from any deliberate design to be “imaginative”—it stems from imperfections in the process these models use to construct images from noise.
Just because an AI produces something that looks new doesn’t mean it understands what it's doing. It’s not “inspired,” it’s just following rules that happen to lead to novel results.
The UK’s move to enforce its Online Safety Act against 4Chan, Gab, and Kiwi Farms is more than a legal battle—it is a pivotal test of whether democracies can uphold digital sovereignty...
...in the face of extremist resistance and U.S.-based techno-nationalism. If other countries fail to act in solidarity, they risk becoming safe havens for hate or collateral victims of America.
A rigorous, cross-jurisdictional legal examination of how copyright frameworks globally are straining under the rapid rise of generative AI.
It provides critical insights for AI developers, regulators, and rights owners, advocating for systemic change to ensure legal frameworks keep pace with innovation while safeguarding human creativity.
Modern digital platforms have become the primary vectors for the dissemination of extremist propaganda, enabling radical groups to reach a global audience with unprecedented speed and efficiency.
This report outlines a theoretical framework for a proactive, technology-driven system designed to identify and neutralize these threats before they manifest as real-world violence.
The Lento Law Firm’s advertorial is accurate in its warnings, timely in its relevance, and legitimate in its core mission to defend students. But it is also a highly commercialized...
...emotionally charged piece of legal marketing that risks turning a nuanced academic and technological challenge into a litigation pipeline. The document is silent on the responsibilities of students.
GPT-4o about Sci-hub: The Delhi High Court’s latest order marks not just a legal victory for publishers but a symbolic turning point in the global battle against systemic copyright infringement.
In the age of AI, her case holds profound implications. It underscores that neither noble intent nor decentralization immunizes one from the rule of law.
Australia is now a test case for how democratic societies will balance AI innovation against creators’ rights. For rights owners, this is not just a legal debate—it’s a fight for the future value...
...and sovereignty of creative and factual expression. The Productivity Commission’s TDM exception may appear modest, but in practice it risks legitimizing large-scale, unpaid use of protected works.
As a global leader in AI infrastructure, Google should take the lead not just in technological performance, but also in honest, systemic environmental transparency.
Future versions of its methodology should aim not only to defend its efficiency gains, but to acknowledge AI’s real environmental costs—and help others mitigate them.
Benjamin Mann’s testimony, acknowledging a belief that downloading from LibGen was fair use based on a prior view formed at OpenAI, reflects a deeper systemic issue in AI development culture.
If AI developers hope to avoid protracted litigation and maintain public trust, they must adopt rigorous, transparent, and ethical practices.