The claim that the AI community, or society at large, should'democratize AI' has attracted considerable critical attention and controversy. Two core problems have arisen and remain unsolved: conceptual disagreement persists about what democratizing AI means; normative disagreement persists over whether democratizing AI is ethically and politically desirable. We identify eight common AI democratization traps: democratization-skeptical arguments that seem plausible at first glance, but turn out to be misconceptions. We develop arguments about how to resist each trap. We conclude that, while AI democratization may well have drawbacks, we should be cautious about dismissing AI democratization prematurely and for the wrong reasons. We offer a constructive roadmap for developing alternative conceptual and normative approaches to democratizing AI that successfully avoid the traps.

Artificial intelligence (AI) now permeates critical infrastructures and decisionmaking systems where failures produce social, economic, and democratic harm. This position paper challenges the entrenched belief that regulation and innovation are opposites. As evidenced by analogies from aviation, pharmaceuticals, and welfare systems and recent cases of synthetic misinformation, bias and unaccountable decision-making, the absence of well-designed regulation has already created immeasurable damage. Regulation, when thoughtful and adaptive, is not a brake on innovation--it is its foundation. The present position paper examines the EU AIAct as a model of risk-based, responsibility-driven regulation that addresses the Collingridge Dilemma: acting early enough to prevent harm, yet flexibly enough to sustain innovation. Its adaptive mechanisms--regulatory sandboxes, small and medium enterprises (SMEs) support, real-world testing, fundamental rights impact assessment (FRIA)--demonstrate how regulation can accelerate responsibly, rather than delay, technological progress. The position paper summarises how governance tools transform perceived burdens into tangible advantages: legal certainty, consumer trust, and ethical competitiveness.

In AI research and practice, rigor remains largely understood in terms of methodological rigor--such as whether mathematical, statistical, or computational methods are correctly applied. We argue that this narrow conception of rigor has contributed to the concerns raised by the responsible AI community, including overblown claims about the capabilities of AI systems. Our position is that a broader conception of what rigorous AI research and practice should entail is needed. We believe such a conception--in addition to a more expansive understanding of (1) methodological rigor--should include aspects related to (2) what background knowledge informs what to work on (epistemic rigor); (3) how disciplinary, community, or personal norms, standards, or beliefs influence the work (normative rigor); (4) how clearly articulated the theoretical constructs under use are (conceptual rigor); (5) what is reported and how (reporting rigor); and (6) how well-supported the inferences from existing evidence are (interpretative rigor). In doing so, we also provide useful language and a framework for much-needed dialogue about the AI community's work by researchers, policymakers, journalists, and other stakeholders.

Musk's $1.8 trillion SpaceX IPO could be'highly undesirable' for some SpaceX is expected to debut on the United States' public markets on Friday in what will be the largest initial public offering (IPOs). Artificial intelligence (AI) giants OpenAI and Anthropic are also widely expected to go public soon, and thanks to a new rule change by tech stock exchange Nasdaq, individual investors could own stock of these companies when they go public in as soon as 15 business days following its first trading day. SpaceX's IPO is generating buzz among retail investors. The Elon Musk-led company is expected to allocate 20 percent of shares to retail investors and has drawn roughly $70bn in orders, according to the Reuters news agency. Historically, there is a waiting period between when a company goes public and when it is listed on the Nasdaq-100 index and/or S&P 500.

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WhatsApp launches totally private'incognito' conversations with its AI chatbot WhatsApp has introduced private chats with its AI chatbot which not even the tech company will be able to read in a new incognito mode. It means neither the user nor the AI's responses will be monitored if the feature is activated, and past conversations will disappear from the chat for the user. Will Cathcart, the head of WhatsApp, said he felt people wanted to have private conversations with AI on sensitive subjects including health, relationships and finances and didn't want them to be accessible. But a cyber security expert has told the BBC this could lead to a lack of accountability for WhatsApp if things go wrong, as they would have no access to chat history. WhatsApp is owned by Meta, which also owns Instagram, Facebook and Messenger.

The Institute for Primary Facts has compiled more than 3.5 million pages of the Epstein files for public display at the newly opened Donald J. Trump and Jeffrey Epstein Memorial Reading Room. It's an early 2016 email thread between Jeffrey Epstein and a woman whose name is redacted by the Department of Justice . In the thread, Epstein asks the unidentified woman for a "naughty selfie" and later sends her a camera. In late February, he replies with a different ask: "Do you have any friends that might want to work for me?...I will give you money if you find someone willing to travel, 22-25, educated. The exchange carries extra resonance when you consider that Epstein is accused of sex trafficking minors, with the Department of Justice estimating that he had more than 1,200 potential victims.

HCCV datasets constructed through nonconsensual web scraping lack crucial metadata for comprehensive fairness and robustness evaluations. Current remedies are post hoc, lack persuasive justification for adoption, or fail to provide proper contextualization for appropriate application. Our research focuses on proactive, domain-specific recommendations, covering purpose, privacy and consent, and diversity, for curating HCCV evaluation datasets, addressing privacy and bias concerns. We adopt an ante hoc reflective perspective, drawing from current practices, guidelines, dataset withdrawals, and audits, to inform our considerations and recommendations.

Fans want to reclaim the music and myth of Michael Jackson in the new biopic while critics call for accountability. Still from, which opened April 24. Is truth determined by the size of the audience it reaches? If so, --a new film about the pop singer Michael Jackson that is on track to have the biggest-ever opening for a music biopic, with projected earnings of $70 million at the US box office, despite critics saying it sanitizes the reality of who Jackson actually was--intends to supplant the King of Pop as the apotheosis of artistic virtue. The film's release has sparked a familiar but newly intensified civil war online, between those eager to reclaim the music and myth of Jackson, and those who see any celebration of him as a failure of accountability.