So the challenge isn’t “make AI explainable.” The challenge is: → When should you trust AI?
→ When should you doubt it?
→ How do you judge quality in a system you can’t dissect?
REGULATION
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Trusting AI: When and How to Judge It
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EU Launches International Digital Strategy Framework
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The EU sets out its International Digital Strategy https://
ec.europa.eu/commission/pre
sscorner/detail/en/ip_25_1370
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#digitaleu #digital #strategy #innovation #technology @BetaMoroney @CurieuxExplorer @Shi4Tech @smaksked @mvollmer1 @mikeflache @Fabriziobustama @Khulood_Almani @Hana_ElSayyed @Timothy_Hughes @enilev -
Scientists Must Restore Academic Integrity and Combat Ideological Drift
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Why is there no loud and powerful movement of leading scientists to restore the integrity of scientific institutions? And equally concerning: why do principled scientific leaders don't use the changed political climate to eject the professional ideological grift from academia?
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Appeal Strategies for Information Access Requests and Agency Compliance
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Another cheat code here is sending in an appeal to the constructive denial of the original request. In some jurisdictions, appeals are mandatorily CCed to a watchdog and count against the agency’s score in a way that they perceive matters. Following the law matters too… a bit.
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Customer Control and AI Model Deployment Decisions
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I'm just a customer. I have no way to influence how these models are served to me.
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Waymo Driverless Taxis Targeted by Protesters in Los Angeles
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Waymo Driverless Taxis Become Protesters’ New Favorite Target Robot-operated electric vehicles were summoned to downtown Los Angeles and set alight
#RiseoftheRobots https://
wsj.com/us-news/waymo-
driverless-taxis-become-protesters-new-favorite-target-23405f0a?st=Qbw4D6
… via @WSJ -
Karen Hao Discusses Empire of AI Book on NewsHour
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A dream come true to talk about my book Empire of AI on @NewsHour. I discuss OpenAI, Sam Altman, and why we do not have to accept the extraordinary harms of the current trajectory of AI development. Thank you to Ali Rogan for having me!
— Karen Hao (@_KarenHao) 9 juin 2025
Order my book: https://t.co/i5rNJ44HXQ. https://t.co/DS0KgfDcmEA dream come true to talk about my book Empire of AI on @NewsHour
. I discuss OpenAI, Sam Altman, and why we do not have to accept the extraordinary harms of the current trajectory of AI development. Thank you to Ali Rogan for having me! Order my book: http://
empireofai.com. -
DLBacktrace: Model-Agnostic Explainability Method for LLMs
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Just dropped: Our webinar on DLBacktrace (DLB) — a model-agnostic explainability method for LLMs & deep learning models.
— Arya.ai (@arya_ai1) 9 juin 2025
✅ Works across any architecture
✅ No model retraining needed
✅ Designed for compliance & audit use-cases
📺 Watch now → https://t.co/3Dfq5sI6sg pic.twitter.com/jqrbx0jJgOJust dropped: Our webinar on DLBacktrace (DLB) — a model-agnostic explainability method for LLMs & deep learning models. ✅ Works across any architecture ✅ No model retraining needed ✅ Designed for compliance & audit use-cases 📺 Watch now → aryaxai.com/videos/inside-th…
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India AI Impact Summit 2026 Seeks Global Input on Priorities
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The @OfficialINDIAai Mission invites your suggestions and inputs regarding the India – AI Impact Summit 2026—themes, outcomes, priorities, and more. Your views will help shape a global conversation where AI drives inclusive growth, social development, and a healthier planet.
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Common Pile v0.1: 8TB Open Licensed Text Dataset for LLM Training
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8. Common Pile v0.1 The Common Pile v0.1 is an 8TB dataset of openly licensed text designed for LLM pretraining, addressing legal and ethical concerns of unlicensed data use.