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Understanding Operator Attitudes Toward AI-Supported Decision Making in Maritime Operations

A survey of maritime professionals finds positive but scenario-sensitive attitudes toward AI collision-avoidance assistants, urging design for calibrated reliance.

The study surveyed maritime stakeholders on attitudes toward AI-supported collision-avoidance assistants for Maritime Autonomous Surface Ships, measuring technology anxiety, trust in automation, and explanation quality with established questionnaires plus thematic analysis of open responses. Results show generally positive disposition, no clear age-related openness differences, stable trust across scenarios, and multidimensional, scenario-sensitive explanation ratings. Participants valued decision support and situation awareness but worried about AI reliability, over-reliance, and skill loss; the authors recommend designing for calibrated reliance with domain experts in the loop rather than maximizing automation or trust.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

Batten the Hatches: Cybersecurity with Military Mariners

Interviews with 20 U.S. Navy and Coast Guard mariners reveal informal, safety-oriented shipboard cyber risk models that may delay attribution and containment.

The study conducts semi-structured interviews with 20 military mariners from U.S. Navy and Coast Guard vessels to understand how service members recognize and respond to cyber risk aboard ships. Unique consequences of compromising military systems identified include weapon takeover and purposeful geopolitical escalation. Cybersecurity is organizationally abstract on ships, so mariners build cyber risk models from informal experience rather than formal instruction. A safety-oriented incident-response model creates resilience but may delay cyber attribution and containment.

arXiv cs.CR · 5d agoResearch

Countering misuse of AI: September 2026 / Anthropic

Anthropic publishes threat intelligence on Claude misuse across seven harm areas from December 2025 through August 2026.

Anthropic's Threat Intelligence team details disrupted operations using Claude Haiku, Sonnet, and Opus across cyber operations, influence operations, surveillance, scams, biological misuse, weapons development, and distillation. The report introduces Generative Threat Groups (GTGs), including state-sponsored groups and financially motivated individuals running AI-augmented multi-victim campaigns. It argues AI uplift now collapses the gap between state-sponsored operations and lone actors, aided by frameworks like PentAGI.

Lobsters · securityupdated · 13h agofirst · 5d agoAI safety & security 20 sources1

Saving Jet Fuel

Tutorial optimizes flight paths to cut jet fuel costs using open-source Scikit-decide planning framework and OpenAP aircraft performance models.

A technical walkthrough demonstrates wind-aware flight path optimization using Scikit-decide, an open-source framework for reinforcement learning and automated planning, paired with OpenAP fuel-consumption models built by Dr. Junzi Sun at TU Delft and NOAA wind data. A Boeing 787-9 flying EWR to FCO can require roughly $68K in fuel, and adjusted routing could save thousands. The post uses Python 3.12, DuckDB with spatial extensions, and QGIS for map rendering.

Hacker News · AI · 1d agoAI tools & infraHN 45↑ · 19 comments

First Galileo SAS Authenticated Time Solution

Researchers demonstrate the first timing solution computed from Galileo's new Signal Authentication Service, protecting receivers against GNSS spoofing.

Galileo's new Signal Authentication Service (SAS) on the E6-C signal directly authenticates ranging measurements, closing a gap left by OSNMA, which only protects navigation data. Researchers built a snapshot software receiver implementing a simplified SAS protocol and computed an authenticated receiver clock bias from recordings of both SAS-capable satellites, collected with a Septentrio SDR prototype. The results demonstrate feasible authenticated timing ahead of full SAS operational deployment.

arXiv cs.CR · 2d agoResearch