Japan's internal affairs industry may introduce artificial intelligence agents at local governments facing labor shortages. Japan's internal affairs ministry has begun considering the introduction of artificial intelligence agents to autonomously perform tasks at local governments facing labor shortages. On Thursday, the ministry held the first meeting of a related study group consisting of relevant experts and local government officials to discuss which tasks could be assigned to AI agents and how local government employees could manage them. The group will compile an interim report by the end of fiscal 2026 and aim to release its final report around summer 2027. According to the ministry, 74% of the country's local governments were using AI in some form as of October 2025. While AI tools to classify data and make predictions and those to generate text and images based on prompts were commonly used, AI agents were rarely used, except in trials at some organizations.

PCWorld explores the risks and benefits of using AI agents like Claude for email management, following Notion Mail's recent shutdown that left users dependent on AI sorting. AI email automation offers appealing benefits including reduced inbox clutter and better organization, but poses operational risks like misfiling or accidental deletion. Privacy concerns remain significant as AI agents access sensitive personal and financial data, requiring users to carefully weigh convenience against potential security risks. When I learned that Notion, the popular online workspace service, was shutting down its Notion Mail product, it wasn't the shutdown itself that got my attention. No, it was this: because so many Notion users had handed over their email sorting duties to AI agents, they'd stopped bothering to open their inboxes . Letting AI agents sort through all your email has long been considered a killer app for AI, although the convenience doesn't come without some serious risks.

Plus: The US House has passed new youth online safety legislation. AI agents are not your "coworkers" Imagine coming in to work to learn that a new underling will report to you. The worker is not a person but an AI tool--one that your company nonetheless calls Alex, an "employee" with a title and defined responsibilities. How well do you think you would work with Alex? If you're anything like the managers studied by Boston University professor Emma Wiles, treating that AI as a coworker would lead you to do a worse job. They caught 18% fewer errors when the work was attributed to an agentic AI employee rather than a chatbot. This is an alarming glimpse of the future Silicon Valley is hurling us toward.

San Francisco's brightest minds are stuffing themselves into hacker houses. The living room of the Accler8 hacker house in San Francisco, where the author stayed for a week. O n a Friday in April, I hopped into an Uber to a fish market in San Francisco with a couple of tech founders on a mission to buy lobsters. Not for dinner, but for science: The duo dreamed of one day altering human consciousness, but they would start by toying around with some crustaceans. They intended to perform neurosurgery on the lobsters in the hopes of controlling them with an AI bot. Leading the way was Elliot Roth, a bearded 32-year-old wearing a black T-shirt with Longevity printed across the chest and a silver chain with a double-helix pendant. To push the boundaries of the five senses, Roth has implanted a magnet in his left ring finger.

AI agents are not your "coworkers" Marketing AI agents as digital employees may make human workers worse at spotting errors and more likely to offload accountability. Imagine coming in to work to learn that a new underling will report to you. The worker is not a person but an AI tool--one that your company nonetheless calls Alex, an "employee" with a title and defined responsibilities. How well do you think you would work with Alex? If you're anything like the managers recently studied by Emma Wiles, a Boston University business professor, treating Alex as a "coworker" and not a software tool would lead you to do a worse job. Wiles found that people caught 18% fewer errors when the work was said to have come from an agentic "AI employee" rather than a chatbot. It turns out that what's in a name matters.

Advanced reasoning models with agentic capabilities (AI agents) are deployed to interact with humans and to solve sequential decision-making problems under (approximate) utility functions and internal models. When such problems have resource or failure constraints where action sequences may be forcibly terminated once resources are exhausted, agents face implicit trade-offs that reshape their utility-driven (rational) behaviour. Additionally, since these agents are typically commissioned by a human principal to act on their behalf, asymmetries in constraint exposure can give rise to previously unanticipated misalignment between human objectives and agent incentives. We formalise this setting through a survival bandit framework, provide theoretical and empirical results that quantify the impact of survival-driven preference shifts, identify conditions under which misalignment emerges and propose mechanisms to mitigate the emergence of risk-seeking or risk-averse behaviours. As a result, this work aims to increase understanding and interpretability of emergent behaviours of AI agents operating under such survival pressure, and offer guidelines for safely deploying such AI systems in critical resource-limited environments.

A new standard called Agentic Resource Discovery (ARD), backed by Google, Microsoft, and Nvidia, aims to create a "Google Search for AI" to help agents find online services. This standardization could transform the chaotic "agentic web" into an efficient system where AI agents perform complex tasks reliably and effectively. AI is coming for us, they keep saying. We'll all have AI agents acting on our behalf, doing everything from our weekly grocery shopping to booking airline tickets. It's gonna change everything, just like the web did!

Spatial Planning is a crucial part in the field of spatial intelligence, which requires the understanding and planning about object arrangements in space perspective. AI agents with the spatial planning ability can better adapt to various real-world applications, including robotic manipulation, automatic assembly, urban planning etc. Recent works have attempted to construct benchmarks for evaluating the spatial intelligence of Multimodal Large Language Models (MLLMs). Nevertheless, these benchmarks primarily focus on spatial reasoning based on typical Visual QuestionAnswering (VQA) forms, which suffers from the gap between abstract spatial understanding and concrete task execution. In this work, we take a step further to build a comprehensive benchmark called MineAnyBuild, aiming to evaluate the spatial planning ability of open-world AI agents in the Minecraft game. Specifically, MineAnyBuild requires an agent to generate executable architecture building plans based on the given multi-modal human instructions.

Recent advances have enabled LLM-powered AI agents to autonomously execute complex tasks by combining language model reasoning with tools, memory, and web access. But can these systems be trusted to follow deployment policies in realistic environments, especially under attack? To investigate, we ran the largest public red-teaming competition to date, targeting 22 frontier AI agents across 44 realistic deployment scenarios. Participants submitted 1.8 million promptinjection attacks, with over 60,000 successfully eliciting policy violations such as unauthorized data access, illicit financial actions, and regulatory noncompliance. We use these results to build the Agent Red Teaming (ART) benchmark--a curated set of high-impact attacks--and evaluate it across 19state-of-the-art models.

Autonomous AI agents that can follow instructions and perform complex multi-step tasks have tremendous potential to boost human productivity. However, to perform many of these tasks, the agents need access to personal information from their users, raising the question of whether they are capable of using it appropriately.