- Pascal's Chatbot Q&As
- Archive
- Page 1
Archive
The New York State Unified Court System (UCS) has introduced one of the most comprehensive and forward-looking interim policies for the use of AI within a government institution.
Other entities that handle sensitive data, depend on trust, or make consequential decisions should adopt similar AI governance frameworks.
If “everything is searchable,” then everything is stealable if adversaries or insiders reach the index: passwords briefly visible on screen, previews of legal docs, health results, private chats...
OS-wide AI monitoring creates a single, dense, forensically perfect dossier on each of us. In open societies, that dossier magnifies breach impact, employer overreach, and chilling effects.
GPT-4o: By prohibiting questions about how Anthropic obtained training datasets — including whether it engaged in torrenting or downloaded from shadow libraries — the court has erected a wall...
...that prevents plaintiffs from fully investigating one of the most critical aspects of AI model training: source provenance. This limits the ability to prove willful infringement.
GPT-5: These billionaires’ interconnected gains illustrate how AI infrastructure has evolved into a self-reinforcing oligopoly spanning hardware, cloud, and capital markets.
While U.S., EU, and UK regulators have the tools to act, the economic gravity and political utility of these firms make serious enforcement unlikely in the near term.
The 2025 State of AI Report. Scholarly publishers are no longer just gatekeepers of human-generated content—they must become curators and verifiers of machine-derived knowledge.
The future of scientific publishing hinges on how swiftly and wisely publishers embrace this new paradigm. AI not only assists with knowledge production but also generates, validates, and teaches it.
Regulators must treat AI-generated political disinformation as a matter of national security and democratic survival.
Anything less than robust, coordinated, and enforceable safeguards would be an invitation for future abuses, more sophisticated deepfake operations, and the gradual erosion of truth itself.
For Silicon Valley to be truly patriotic its actions must transcend rhetoric. True patriotism for corporations of this scale & influence isn't measured in press releases or philanthropic contributions.
The future prosperity & security of the United States may well depend on whether these corporate titans can evolve from being disruptive adolescents to responsible stewards of the American enterprise.
Mekic v. X: the case is a microcosm of broader tensions: corporate secrecy vs. democratic oversight, algorithmic power vs. individual rights, and platform control vs. journalistic freedom.
Mekic was “shadowbanned” by X—his communications were limited without explanation. He demanded to know why, citing GDPR rights to personal data and to transparency about automated decision-making.
Report: Detachment of scientific conclusions from human authorship or oversight, especially with generative models, raises questions about accountability, originality, and reproducibility.
Over-reliance on AI may lead to the narrowing of scientific questions explored, favouring well-documented areas where AI performs better. AI may radically change what counts as scientific knowledge.
GPT-4o: The Apostolic Exhortation Dilexi Te is more than a theological document. The Trump administration’s policies, when viewed through this lens, fall grievously short of the Gospel ideal.
Invoking divine blessing while enacting laws that harm the poor, ignore the sick, criminalize the migrant, and reward the powerful, amounts to a betrayal of the very faith it claims to defend.
GPT-4o: Martinez-Conde v. Apple is a meticulously constructed and potentially explosive copyright infringement case that places Apple’s AI ambitions under judicial scrutiny.
Given the strength of evidence, the precedent of similar cases, and the reputational risks at stake, the likely outcome is either a plaintiff-friendly settlement or a partial win for the class...
Attackers can exploit these latency variations to infer sensitive information, including: Training data membership (e.g., whether a particular input was part of the training set).
GateBleed can serve as a forensic tool for litigants to demonstrate improper model training practices, shifting the burden of proof onto AI companies.