AI ethics on Saturday, 11 July 2026

Anthony Albanese will deliver a landmark speech on AI this week as MPs are torn between attracting datacentre investment and protecting the rights of creatives Follow our Australia news live blog for latest updates When Anna Funder stood before a pack of journalists at Parliament House this month, she presented herself not just as a writer but also a “victim of crime”. The Stasiland author was using the analogy to illustrate how technology companies have flagrantly “hoovered up” her literary wor

Microsoft, Amazon and Google say they still aim to achieve net zero output despite construction boom Microsoft, Amazon and Google’s collective carbon emissions have increased by nearly a fifth in the past year, driven largely by datacentre construction. In the financial year ending March 2026, the three tech companies emitted 119m mTCO₂e (metric tonnes of carbon dioxide equivalent), or about a third of those of France. Continue reading...

Experts say there will still be opportunities ahead in everything from teaching to hotels and the law Entering the world of work often brings some uncertainty, but now there is another question: how can I AI-proof my career? We asked people from across various industries what they think the impact of AI will be on careers, and which jobs may be less affected. While it is still early days for the tech, many had ideas about how you can best prepare yourself for a successful career in this new

Meta was criticised for feature launched on Tuesday that automatically lets users generate images using content from public Instagram accounts Meta has said ⁠it is discontinuing an AI feature launched this week that allowed users to generate images using public Instagram ⁠accounts, after drawing widespread ⁠criticism over ​privacy concerns, including from a Hollywood union. “Our intent was to provide a useful creative tool and to give people control ⁠over whether their public content could be re

ChatGPT is hiring a dedicated product manager to build experiences for families, caregivers, and older adults, according to a job posting.

A cryptocurrency regulation bill is facing a make-or-break moment as senators seek to resolve remaining policy disputes in the next four-week stretch, which experts warn is likely the last window to pass the legislation before the midterm elections. Bipartisan negotiations over the Clarity Act, which aims to provide a regulatory framework for the digital assets...

A merge is a contract. The moment a change lands on main, every other team in the organization starts building The post Your merge gate was a compromise. Coding agents are making it a liability. appeared first on The New Stack .

Walk into any college library and you will likely see students wearing headphones and listening to music. The idea that music can improve learning has been around for decades. The “Mozart Effect,” is the pop psychology myth, first hypothesized in a 1993 paper, that listening to classical music can help people retain and process new […]

ETF Action's Mike Akins is encouraging investors to boost exposure to groups that underperformed compared with major artificial intelligence stocks.

Go has emerged as the lingua franca for cloud infrastructure, used for everything from container orchestration and CI/CD pipelines to The post Microsoft joins Google in backing Go for AI agents — OpenAI and Anthropic lag appeared first on The New Stack .

Zhang Qi, a ride-hailing driver based in Guangzhou, has turned to artificial intelligence this year to help his son make one of the most important decisions of his young life: choosing a university degree programme. Like millions of 18-year-olds across China, Zhang’s son recently received his university entrance exam results and had to navigate the country’s labyrinthine admissions system – choosing from thousands of programmes at hundreds of schools. Many middle-class families hire expensive...

You should take calorie data with a grain of salt. Here's what I learned after testing the Fitbit Air's heart rate data against a gold standard heart rate monitor.

Users and Hollywood agencies raised privacy and copyright concerns about the new tool, Muse Image.

Upbeat on-hold music blared from Jerrica Mickens’ cellphone for nearly 50 minutes as she searched on her laptop for affordable housing for a parent in Detroit. Mickens was on a three-way call with a mother and a legal aide hotline the morning of April 21 in her Central High School office. As the two waited […]

Apple Inc. today sued OpenAI Group PBC for allegedly stealing intellectual property related to its consumer devices. The iPhone maker filed the complaint with the U.S. District Court for the Northern District of California. OpenAI entered the consumer electronics market last year when it bought io Products Inc., a startup founded by former Apple executives. […] The post Apple sues OpenAI, former employees over alleged intellectual property theft appeared first on SiliconANGLE .

Alors que l’intelligence artificielle permet désormais de créer des morceaux entiers, parfois difficiles à distinguer de productions humaines, des organisations professionnelles plaident pour davantage de transparence sur l’origine de ces titres.

GENEVA, July 10, 2026 - The AI for Good Global Summit concluded following four days of sessions that demonstrated the widespread application of artificial intelligence in a variety of sectors, including health and agriculture, mobility, education, creative industries, and public policy. The summit also raised awareness of quantum technologies, robotics, and the standards and infrastructure required to facilitate their widespread deployment. The post Day 4 at the AI for Good Global Summit: Women’

Release: sqlite-utils 4.1 The first dot-release since 4.0 a few days ago , introducing a number of minor new features. sqlite-utils insert and sqlite-utils upsert now accept a --code option for providing a block of Python code (or a path to a .py file) that defines a rows() function or rows iterable of rows to insert, as an alternative to importing from a file. ( #684 ) sqlite-utils already had features that allow you to pass blocks of Python code as CLI arguments, for example this one for the s

Here at the National Academy of Sciences, it seems that my first job is to serve on the selection committee for the prestigious Michael and Sheila Held Prize in combinatorial and discrete optimization and related areas. The committee chair, my former MIT colleague Madhu Sudan (now at Harvard), invited me to share the following message […]

Five frames for seeing how AI is reshaping decisions, accountability, and knowledge.

Today's links Workplace "flexibility" isn't: What the gig economy calls flexibility is just risk-shifting. Hey look at this: Delights to delectate. Object permanence: "Alanya to Alanya"; ToS are the internet's biggest lie; Soviet jokes; Fox rapists v gag orders; GBAO is the future; "Fun Family"; Sacklers get to keep the loot. Upcoming appearances: London, Edinburgh, Sydney, Melbourne, Brighton, London, South Bend. Recent appearances: Where I've been. Latest books: You keep readin' em, I'll keep

Today, 38% of primary school–age children in South Asia and 14% in Sub-Saharan Africa attend private schools. Given the increasing prevalence of private schooling, what should governments, donors and ...

From local communities to the global stage, a diverse group of young leaders from Thailand is helping shape conversations on public policy, climate action, inclusion, indigenous rights, disability ...

Across a range of fast growing urban markets, private developers are constructing a version of the smart city that operates largely outside the purview of municipal government, often at the explicit invitation of city officials seeking to shift the cost and complexity of digital infrastructure onto private capital. Gated residential and mixed use developments are increasingly marketed not merely on the basis of security and amenity, but on their smartness: integrated home automation, app mediate

Layout-based 3D scene synthesizers place each object using two human-annotated channels: a categorical class label and a canonical-pose convention. We ask whether a single self-supervised token derived from object geometry can replace both, and study such tokens directly as a representation, decoupled from any synthesizer. A Finite Scalar Quantization (FSQ) point-cloud autoencoder is chamfer-trained on placed 3D-FUTURE furniture with no labels or pose annotations. Diagnostic probes recover fine-

Autonomous CLI agents can now execute hundreds of actions across multi-hour sessions: writing code, executing shell commands, browsing the web, and managing cloud infrastructure, all with minimal human oversight. Does greater autonomy invite greater risk? We introduce ANCHOR, an automated auditing framework that stress-tests CLI agents on illegal tasks grounded in public US court cases. ANCHOR deploys an auditor agent fine-tuned on dark personality data using supervised and reinforcement fine tu

Large Language Models (LLMs) are increasingly used for code smell detection tasks due to their ability to interpret program semantics. However, their reliability in this context remains poorly explored, particularly under varying prompt conditions where model predictions may be influenced by external cues rather than code characteristics. One such limitation is sycophancy bias, where models tend to align their outputs with user-provided assumptions instead of performing objective analysis. In th

Tree crowns are a challenging target for resilient AI because they are not static objects: their spectral response, internal texture, translucency, and apparent boundaries change substantially across the growing season. We develop PhenoEmbed, a self-supervised crown-centric temporal embedding model trained with contrastive and masked reconstruction objectives on HeideBench, an 18-date UAV multispectral time-series benchmark for forest crown phenology in D{ö}lauer Heide. The model treats seasonal

We evaluate when sparse autoencoder (SAE) features act as localized control handles for safety-relevant behavior. This question is difficult because apparent success can arise from weak interventions, mismatched baselines, model robustness, or degenerate outputs that automated safety judges mark as unsafe without representing meaningful harmful compliance. We introduce a matched coherence-gated evaluation protocol for runtime safety interventions: methods are compared at matched target-effect po

Knowledge Graphs (KGs) are increasingly constructed through automated extraction pipelines; however, such systems often introduce spurious or incomplete triples, which degrade downstream performance. Existing evaluation practices rely heavily on task-specific metrics or small-scale manual verification, offering limited insight into the structural and semantic fidelity of extracted graphs. We propose a novel, interpretable metric for intrinsic KG quality assessment that measures how closely an au

Equitable renewable-energy planning is a sequential decision problem, but the decision variables available to a public planner differ sharply between mature and emerging economies. In the former the government largely builds generation, while in the latter it steers private investment through incentives and quotas. We formulate socially-equitable renewable-energy budget allocation as a Markov Decision Process (MDP) and, using a single problem-agnostic solver interface, compare the same policies

We introduce ActiveFly-Bench, the first benchmark to bridge cyberspace reasoning and physical-world interaction for UAV embodied perception. The benchmark decomposes active perception into three hierarchical tasks: Aerial Embodied Question Answering (Air-EQA), Observation Behavior Planning (OBP), and Fine-grained Language-guided UAV Control (FLUC), explicitly connecting high-level task understanding, behavior planning, and low-level control. The datasets are collected from both real-world and si

Emotion-aware artistic image generation requires an image to match the input prompt, follow the specified artistic style, and convey the target emotion. In this challenge, the main difficulty is that the visual and affective attributes available in the training data are not explicitly provided at test time. Without these attributes, the generator has to decide not only what to depict, but also how the target emotion should be expressed through color, lighting, brushwork, composition, line, and l

Scientific research is a complex, multi-stage workflow rather than a single act of text generation. The ideation process typically emerges through literature search, paper reading, tool use, claim checking, cross-paper synthesis, brainstorming, rejection of weak directions, and iterative writing. Existing resources capture individual components of this process, but datasets that jointly record tool use, evidence acquisition, intermediate artifact evolution, and idea- or proposal-level endpoints

Evolutionary program search guided by Large Language Models (LLMs) has emerged as a powerful paradigm for automated scientific discovery. However, current approaches are fundamentally constrained by three bottlenecks: structurally blind parent selection, sparse whole-program evaluation rewards, and static mutation operators that fail to adapt during search. We present GAE (Graph-Augmented Evolution), a framework that resolves these limitations through a tightly coupled, three-pillar architecture

Large language model agents increasingly store reusable procedures outside the model. These reusable procedures are often called \emph{skills}: they may be code functions, natural-language instructions, SKILL.md packages, workflow graphs, or learned adapters that a future agent can retrieve and invoke. This taxonomy-driven survey asks how such skill libraries change over time. Across a $124$-paper $2023$--$2026$ audit set, we synthesize dynamic skill systems as \emph{lifecycle-managed, verified,

Safety alignment in large language models remains brittle across languages: prompts reliably refused in English can elicit harmful compliance in non-English and low-resource settings. We introduce \textsc{Minionese}, a multilingual jailbreak benchmark spanning 18 languages, 4 resource tiers, and 4 perturbation types (standard translation, code-switching, transliteration, and translationese), paired with a geometric mechanistic analysis of refusal failure across language tiers. We show that each

Semantic caching defines answer reuse on embedding similarity: two utterances share a stored answer when a similarity score clears a threshold, with no notion of authorization, versioning, or of what makes two demands the same. This note changes the object on which reuse is defined: in a governed domain, reuse should operate on a mathematically characterized quotient of resolved conversational demands, not on a similarity heuristic. Three independently defined relations on resolved utterances --

Network alignment identifies node correspondences across different networks and is a fundamental primitive in many data science applications, including social network analysis, fraud detection, and knowledge graph integration. However, state-of-the-art network alignment methods often achieve high accuracy by repeatedly constructing and updating dense matrices, sacrificing scalability in the process. To address this scalability limitation without compromising alignment accuracy, we present FastAl

Large language model (LLM) agents are beginning to automate machine learning engineering (MLE) by coupling planning, code execution, debugging, and empirical feedback. Translating this capability to medical imaging remains difficult because each task imposes modality-specific experimentation and strict requirements for validation protocols and prediction artifacts. Here we introduce AMID, an autonomous multi-agent framework for medical imaging model development. AMID first proposes Data-Conditio

Reinforcement learning for large language models (LLMs) typically relies on trust-region masks to stabilize off-policy updates. The dominant PPO-style approach uses the sampled-token importance ratio for two criteria: a proximity criterion, which asks whether the policy has moved too far from the behavior policy, and a direction criterion, which asks whether the update pushes it farther away. Recent work DPPO improves the proximity criterion by replacing PPO's ratio-based test with a probability

Vision Transformers (ViTs) are difficult to interpret because current methods of relevance propagation and attention flow do not fully consider some key architectural features, such as the uneven importance of attention heads and residual connections. Prior approaches typically assume uniform importance across attention heads; furthermore, they model skip connections as identity paths, leading to inaccurate relevance attribution. To address these issues, we introduce GradSkip, a novel relevance

Recent advances in large-scale multimodal models have drivenremarkable progress in vision-language tasks; however, comprehensiveomni-modal understanding remains under-explored, largely due to thescarcity of datasets with rich, explicitly aligned auditory cues. To bridgethis gap, we present AVDC (Audio-Visual Decoupled Captions), a large-scaledataset designed to disentangle visual and auditory semantics. Specifi-cally, we propose an automated pipeline that leverages off-the-shelf mod-els to annot

Visual Language Navigation foundation models aim to unify deep reasoning for grounded spatial decisions with broad versatility for diverse embodied tasks. Current approaches typically achieve this integration via monolithic policies that map observations directly to actions, yet they often suffer from coordinate drift and poor handling of long-tail semantics. Furthermore, these black-box mappings lack interpretability, hindering the simultaneous achievement of generality, robustness, and transpa

Recent VLM and VLA systems have improved robotic perception and action prediction, yet long-horizon embodied agents still require a general runtime layer for reasoning, memory, tool use, verification, and cross-embodiment execution. We present ABot-AgentOS, a general robotic Agent Operating System that sits above low-level controllers and provides a deliberative agent layer for scene-conditioned planning, context-isolated skill execution, multi-stage verification, multi-modal memory, and edge-cl

In the rapidly evolving landscape of technology, Blockchain (BC), Artificial Intelligence (AI), and Smart Industrial Internet of Things (IIoT) are leading and promising technologies in the world that facilitate the current society to develop the quality of living and make it simpler for users. However, these technologies have been applied in various domains for different purposes. These technologies successfully assist in developing the desired system, such as smart cities, homes, education, and

Influence maximization in social networks has received increasing attention, particularly in applications where fairness among demographic groups is an important concern. However, many existing approaches either overlook group-level disparities or primarily optimize influence spread without explicitly modeling fairness-related trade-offs. In this paper, we propose a group-aware multi-objective evolutionary framework that decomposes seed sets into group-specific sub-solutions. Each demographic gr

Artificial intelligence is reshaping hospital care delivery through federated learning pipelines, edge-cloud inference architectures, and AI-driven clinical decision support. Yet the translation of these AI capabilities into patient-centred, institutionally governable, and humanised hospital systems remains fragmented across the literature. This paper addresses that gap through a PRISMA-compliant systematic evidence synthesis of 116 included studies and reports (inter-rater reliability $$\kappa

Brain-computer interfaces (BCIs) are a class of diverse hardware modalities, associated software, and connected devices which are widely used in a variety of fields, including neurosurgery, biomedical data analysis, and neuroimaging. Recent years have seen rapid advancements in BCI technology, and neurotechnology more broadly, with the first devices now passing clinical trials, early examples of consumer hardware entering the market, and many variants of consumer and medical hardware with increa

Dr Jillian Terry SFHEA is Associate Professor (Education) and Co-Director of LSE100, the sector-leading flagship interdisciplinary course taken by all undergraduate students at the London School of ...

Safe and socially compliant navigation remains a fundamental challenge for autonomous robots operating in human-populated environments. Beyond collision avoidance, robots must anticipate human motion and respect personal space to ensure human comfort. Model Predictive Control (MPC) offers a robust alternative to classical and data-driven methods, although its effectiveness strongly depends on accurate human motion prediction and efficient computation. This paper introduces SFM-NMPC, a Social For