Named after the hundred-eyed watchman of Greek myth, Argus watches the education landscape: spotting new opportunities, pressure-testing the ventures we're building, and tracing every read back to the real-world signals behind it.
The evidence library: the raw signals the pipeline is watching across the education ecosystem. Every idea is built from these.
arXiv:2604.11430v2 Announce Type: replace-cross Abstract: AI agents that pay for resources via the x402 protocol embed payment metadata - resource URLs, descriptions, and reason strings - in every HTTP payment request. This metadata is transmitted to the payment server and to the centralised facilitator API before any on-chain settlement occurs; neither party is typically bound by a data processing agreement. We present presidio-hardened-x402, the first open-source middleware that intercepts x402 payment requests before transmission to detect and redact personally identifiable information (PII), enforce declarative spending policies, and block duplicate replay attempts. To evaluate the PII filter, we construct a labeled synthetic corpus of 2,000 x402 metadata triples spanning seven use-case categories, and run a 42-configuration precision/recall sweep across two detection modes (regex, NLP) and five confidence thresholds. The recommended configuration (mode=nlp, min_score=0.4, all enti
arXiv:2511.06160v2 Announce Type: replace-cross Abstract: While recent safety guardrails effectively suppress overtly biased outputs, subtler forms of social bias emerge during complex logical reasoning tasks that evade current evaluation benchmarks. To fill this gap, we introduce a new evaluation framework, PRIME (Puzzle Reasoning for Implicit Biases in Model Evaluation), that uses logic grid puzzles to systematically probe the influence of social stereotypes on logical reasoning and decision making in LLMs. Our use of logic puzzles enables automatic generation and verification, as well as variability in complexity and biased settings. PRIME includes stereotypical, anti-stereotypical, and neutral puzzle variants generated from a shared puzzle structure, allowing for controlled and fine-grained comparisons. We evaluate multiple model families across puzzle sizes and test the effectiveness of prompt-based mitigation strategies. Focusing our experiments on gender stereotypes, our finding
arXiv:2601.06038v2 Announce Type: replace Abstract: Methodological innovations have become increasingly critical in the humanities and social sciences (HSS) as researchers confront complex, nonlinear, and rapidly evolving socio-environmental systems. On the other hand, Early Career Researchers (ECRs) continue to face intensified publication pressure, limited resources, and persistent methodological barriers. Employing the GITT-VT analytical paradigm--which integrates worldviews from quantum physics, mathematical logic, and information theory--this study examines the seven-year evolution of the Bayesian Mindsponge Framework (BMF) analytics and the bayesvl R software (hereafter referred to collectively as BMF analytics) and evaluates their contributions to strengthening ECRs' capacity for rigorous and innovative research. Since 2019, the bayesvl R package and BMF analytics have supported more than 160 authors from 22 countries in producing 112 peer-reviewed publications spanning both qua
arXiv:2607.00854v1 Announce Type: cross Abstract: Recent advances in AI have heightened scholars' and policy makers' concern with social influence and behavioral contagion in online communities. We conduct a field experiment on Reddit to investigate the extent to which online users are susceptible to positive behavioral stimuli from other users and artificial agents. We let apparent human and bot accounts give symbolic awards to users with one of four rationales: praising the recipient's logical argument, emotional sensitivity, or moral integrity, or explaining that the award resulted from a random draw in a lottery. We evaluate how the different rationales for the award affect the recipients' subsequent behavior on the platform in terms of volume, impact, and content, as well as the further behavioral contagion to other users. We find that awards do not increase user activity and downstream impact, and awards from bots with the lottery rationale can in fact reduce them. Nevertheless,
arXiv:2607.00523v1 Announce Type: cross Abstract: Artificial intelligence (AI) is becoming ubiquitous, and across domains, increasingly autonomous systems are carrying out tasks which raise significant ethical and legal challenges which demonstrate a need for strong human-machine teams rooted in trust. In this article, I argue that within highly impactful areas (such as medicine or warfighting) there are grounds for us initially treating autonomous and opaque systems as relevantly analogous to dogs (or other animals with which we have close relationships). Under this analogy, humans making use of these systems are not to be viewed as "users" or "deployers" of these systems, but instead take the role of "handlers". This recasting of roles shifts the way we view humans, AI-enabled and autonomous systems, and the relations between them, and moreover clarifies the clear and traceable lines of responsibility humans have for the outcomes brought about when using these systems. In developing
arXiv:2607.00403v1 Announce Type: cross Abstract: Large language models are increasingly used by participants on crowdsourcing platforms when responding to surveys, potentially undermining the validity of collected data. Our study aims to quantify the prevalence of this behavior and investigate methods to detect and prevent it. In a series of surveys (N = 250), we examined conditions such as platform choice, survey length, requests not to use AI, and disabling copy-paste functionality. We were able to identify distinct characteristics of LLM-assisted responses and found that their frequency varied widely, from under 10% on Prolific to over 80% on Mechanical Turk. Mitigation measures reduced LLM usage but did not necessarily improve data quality. No participants employed browser-use agents at the time of our survey, but we report on our own detection experiments. We recommend that researchers actively screen survey responses for LLM usage by recording and analyzing keystroke data and cr
arXiv:2607.00280v1 Announce Type: cross Abstract: Airbnb is a community based on connection and belonging -- many hosts on Airbnb are everyday people who share their worlds to provide guests with the feeling of connection and being at home; Airbnb strives to connect people and places. Among our efforts to connect guests and hosts, we provide tools to enable hosts to set competitive prices, which helps improve affordability for guests while helping hosts get more bookings. We also personalize the guest experience to show them the listings that match their needs. To help inform these efforts, we combine economic modeling and causal inference techniques to understand how guests book stays based on the prices hosts set, among other factors, and how that preference varies across different guests and listings. Such understanding helps us identify opportunities for Airbnb to support the marketplace and better connect guests and hosts. For example, understanding how much guests respond to diff
arXiv:2607.00220v1 Announce Type: cross Abstract: Artificial intelligence (AI) systems are routinely modified after deployment through retraining and changes in their environments. These transformations raise a metaphysical question: under what conditions does an AI system remain the same system over time or across deployments? Earlier work formulates synchronic and diachronic identity propositionally, by relating identity within a fixed AI system type to equality of trustworthiness levels. Such criteria specify when identity statements are true, but leave implicit the structure of the states compared, the transformations connecting them, and the temporal organization of persistence. We develop a category-theoretic formalization of AI identity. An AI system type is specified by a datum consisting of a techno-function, a trustworthiness profile, and a trustworthiness-level function. Profile-relative states are connected by admissible lifecycle paths, which are restricted to trustworthin
arXiv:2607.00002v1 Announce Type: cross Abstract: Moral cognition has traditionally been modeled as adherence to fixed ethical theories--deontology, consequentialism, virtue ethics--implemented as static rules or value functions. We propose Bounded Morality, a formal framework for analyzing the computational demands of moral problems faced by finite agents. Extending Herbert Simon's notion of bounded rationality, we formalize moral situations along two orthogonal dimensions: moral breadth, the scope of entities treated as morally relevant, and moral depth, the inferential integration required to evaluate their interactions. Limited resources impose an unavoidable tradeoff between these dimensions, defining a feasible space of moral computation. Within this space, ethical theories correspond to locally efficient strategies adapted to different demand regimes rather than competing accounts of moral truth. The framework yields a formal notion of moral regret and moral progress under const
arXiv:2607.00001v1 Announce Type: cross Abstract: Most approaches to AI alignment treat human preferences as fixed targets to be inferred and optimized. This assumption conflicts with extensive empirical evidence showing that preferences are layered, dynamic, and constructed through interaction--particularly with adaptive technologies. As AI systems become more persistent, personalized, and socially embedded, they increasingly participate in shaping what people attend to, value, and endorse over time. We introduce Constructive Alignment, a paradigm that reframes alignment as a control problem over evolving human preference trajectories rather than static preference satisfaction. Drawing on behavioral economics, psychology, and constructivist social theory, we model preferences as layered state variables that evolve under interaction with AI systems. We formalize this view using a control-theoretic framework in which system actions and interaction design jointly influence both world sta
arXiv:2607.01113v1 Announce Type: new Abstract: Corporate sponsorship is increasingly prevalent at computer science conferences. However, a quantitative understanding of this phenomenon has yet to be established, let alone insights into the interplay between academic conferences and sponsoring corporations, or how to leverage it. To fill these gaps, this study first explores the landscape of corporate sponsorship across a wide range of high-profile computer science conferences, shedding light on its evolution over a 25-year period from 2000 to 2024. The complex and expansive relationships between these conferences and their corporate sponsors are then systematically organized into a network for structural analysis and conference evaluation. Specifically, after modularity optimization, the network's topological properties are analyzed to identify key conferences and corporations that shape the overall structure, connectivity, and functionality. More importantly, this study makes the fir
arXiv:2607.00941v1 Announce Type: new Abstract: Agentic AI systems generate runtime records, logs, traces, and audit artefacts, but the existence or integrity of such records does not by itself establish that legally operative oversight findings can be recovered from them. This technical report defines an evidentiary-adequacy criterion for a bounded class of determinations: binary findings of fact about specific events and their relations, such as whether protected data crossed a boundary, whether a human could intervene, whether an information barrier held, or whether delegated authority was valid at the moment of use. The criterion states that a runtime record can answer such a determination only if it carries both a typing that maps recorded events to the legally operative category and the relation, such as provenance, authority, derivation, or temporal validity, on which the determination's truth depends. The claim is one of necessity, not sufficiency. The report instantiates the c
arXiv:2607.00641v1 Announce Type: new Abstract: Advances in generative AI are rapidly increasing the quality and commercial value of generated music, and this progress depends on large catalogs of creators' recordings. This raises a central question for platform design: how should creators be compensated when their work is used to train generative AI models that in turn produce commercial outputs? We develop a framework for fairly compensating creators in generative-music markets, where each creator's payment depends on a data-attribution score estimating their contribution to model outputs. Compared to past compensation frameworks, our framework has two unique considerations: (1) attribution is traced to entire creator catalogs, not individual songs, and (2) the informativeness (signal-to-noise ratio) of the attribution score is an input to the payment mechanism. The framework yields a closed-form payment rule per creator and measures the welfare cost of inaccurate attribution for bot
arXiv:2607.00437v1 Announce Type: new Abstract: In the current era of great-power competition and the diffusion of emerging disruptive technologies on the battlefield, NATO's approach to coordinating the development, adoption, and standardization of new technologies is changing from its practices during the Cold War, but the nature of these technologies poses additional challenges for the alliance.
arXiv:2607.00140v1 Announce Type: new Abstract: As computing education expands beyond traditional programming into operational domains such as systems administration and command-line environments, existing pedagogical frameworks struggle to capture a dimension that is critical in these contexts: the real-world consequences of learner actions. Existing cognitive taxonomies classify learning objectives by mental operations but do not account for system impact, leaving a critical gap in command-line education where conceptually simple commands can have severe consequences. This work presents CogTax, a four-level cognitive taxonomy that integrates two dimensions: cognitive complexity, derived from Bloom's Revised Taxonomy, and operational impact, which distinguishes observational, reversible, structural, and administrative operations. The four progressive levels range from safe read-only inspection to advanced system management requiring integration of multiple abstract models. Then, the t
arXiv:2607.00120v1 Announce Type: new Abstract: Emotional bonds between humans and AI companions are growing, and the question of whether a person may marry an AI system will soon move from speculative fiction into law. This chapter examines whether the autonomy-centered logic that has expanded marital choice among human beings can justify extending marital status to superintelligent companions. Following a scenario-envisioning exercise informed by anticipatory ethics, I argue that granting such status leads to socially unjust outcomes, even under the generous assumption of reliable superintelligence. Marriage as a socio-legal institution does more than ratify private agreement; it creates networks of mutual obligation, joins families, and makes each partner vulnerable to the other. A relationship sustained by corporate policy and continued payments is a subscription rather than a bond tested by time. Discussing wholesale marital status is therefore the wrong frame. Law should carve ou
arXiv:2607.00019v1 Announce Type: new Abstract: This paper offers a call to action. We urge our colleagues in the research community to play a greater role in the articulation of our findings to the public. To illustrate the stakes we present a case study on the initial stages of an LLM-based machine translation application's deployment in a real-world context: a text-2-911 system advertising capabilities in 55 languages for use in emergencies in which it may be difficult to call operators directly. We identify a number of common misconceptions about technologies such as these, concluding with a set of concrete recommendations and best practices for stakeholders at every stage of the development and deployment pipeline. While the advancement of scientific research often lies in solving the "hard" problems, we argue it is often the "easy" ones -- problems for which the latest technology is often unnecessary -- that are most overlooked.
arXiv:2607.00018v1 Announce Type: new Abstract: Media coverage of armed conflict is deeply asymmetric: we document a 224$\times$ gap between the most and least covered conflict zones in English-language media across 22 countries (2020--2026). We evaluate zero-shot conflict escalation forecasting across all 22 countries on a 660-case held-out test set, comparing Llama-3.3-70B and GPT-4o against three structured baselines. The central finding is not a performance gradient but a qualitative failure: LLMs do not forecast conflict -- they categorize it. Llama predicts escalation on every under-covered case, matching the trivial Always-YES baseline to three decimals; GPT-4o predicts NO on every over-covered case, missing all five actual escalation events. A logistic regression using only eleven observation-window features with \emph{no country information} achieves F1~=~0.402, outperforming both LLMs in every measurable tier. This failure cannot be resolved at inference time: adding structur
arXiv:2607.00015v1 Announce Type: new Abstract: To improve residents' well-being in Australia's urban areas, governments have introduced policy reforms such as SEPP65, BADS, and SPP7.3 to enhance apartment design quality. These regulations require precise geometric and spatial analysis to evaluate health-related features, including daylight access, natural ventilation, privacy, and space efficiency. However, compliance checking remains challenging due to its manual, time-intensive nature. Additionally, evolving policies limit scalability for large-scale assessments across thousands of apartments. Existing automated floor plan analysis methods are fragmented and typically focus on single apartments, lacking a unified framework for multi-unit compliance checking. This article explores current advancements in automated floor plan analysis, particularly AI-driven approaches, and highlights key challenges in their practical adoption. To address these gaps, a conceptual framework is proposed
Article URL: https://www.niskanencenter.org/the-case-for-shortening-medical-education/ Comments URL: https://news.ycombinator.com/item?id=32679435 Points: 2 # Comments: 2
Article URL: https://medicustech.blogspot.com/2018/01/benefits-of-3d-animation-in-medical.html Comments URL: https://news.ycombinator.com/item?id=16279725 Points: 2 # Comments: 0
Article URL: https://restofworld.org/2026/edtech-funding-collapse-k12-startups-ai-workforce/ Comments URL: https://news.ycombinator.com/item?id=49500207 Points: 3 # Comments: 0
A new report found that while more than 90% of health systems have deployed third-party AI tools, less than half have the infrastructure to properly test and validate them before they become embedded in patient care. The post Hospitals Are All In on AI, but Testing and Oversight Haven’t Caught Up appeared first on MedCity News .
Biohaven is outlicensing to SK Biopharmaceuticals global rights to opakalim, a Kv7-targeting small molecule in pivotal clinical testing for epilepsy. Biohaven gets non-dilutive financing for its pipeline while SK Bio gains another asset to potentially commercialize in the U.S. The post SK Bio Broadens U.S. Prospects, Licensing Late-Stage Epilepsy Drug From Biohaven appeared first on MedCity News .
When the healthcare system defaults to uncertainty, people delay care because it feels safer for their wallets. In some cases, people wait too long, leaving an ER visit as the path of least resistance. The post The Missing Piece in Lowering the Cost of Care: Predictability appeared first on MedCity News .
Crystalys’s dotinurad is currently in pivotal testing for gout, a prevalent inflammatory disorder with few treatment options. The drug has the same mechanism of action as a molecule that Sobi added to its pipeline through a $950 million acquisition. The post Crystalys Therapeutics Tacks On $130M for Pivotal Tests of Gout Drug appeared first on MedCity News .
Candid’s Series D round was led by Sixth Street Growth, with participation from Oak HC/FT, 8VC and Y Combinator. The post Candid Health Snags $120M for AI RCM Platform appeared first on MedCity News .
VBC aligns reimbursements to outcomes, emphasizing the quality and effectiveness, not quantity, of healthcare activities. But the same cost constraints driving interest in VBC can also turn it into a liability. The post Why Value-Based Care Only Works If You’ve Tamed Costs appeared first on MedCity News .
A core principle of trauma-informed care is understanding that past and ongoing exposure to stress and trauma can directly shape health outcomes. But by remaining blind to these histories, the medical community severely limits its ability to address the very drivers of the diseases it is trying to cure. The post Medicine Understands Trauma’s Impact, But Rarely Asks About It appeared first on MedCity News .
Article URL: https://pietersz.co.uk/2026/05/irrational-philistine-education-has-won Comments URL: https://news.ycombinator.com/item?id=48258425 Points: 4 # Comments: 2
A new paper shows Cleveland Clinic’s AI scribe rollout is paying dividends in clinician satisfaction and retention. These are key metrics for hospitals to track, given they spend millions on recruitment and retention efforts amid an ongoing workforce crisis. The post Ambient Scribes Improve Clinician Retention, Cleveland Clinic Research Shows appeared first on MedCity News .
Abcuro will apply the capital to a study that could support a biologics license application in inclusion body myositis, a rare inflammatory disorder that leads to worsening muscle weakness. A Phase 2/3 study failed earlier this year, but Abcuro saw positive trends in patients with less severe disease. The post Abcuro Adds $66M to Try Again in Rare Inflammatory Disorder With No Approved Drugs appeared first on MedCity News .
Cityblock Health plans to acquire rural healthcare provider Homeward Health and has raised $116 million to expand its value-based care model to rural and Medicare Advantage populations. The post Cityblock to Acquire Homeward Health, Secures $116M Series E appeared first on MedCity News .
But the deadline that most people are not tracking, and the most worrisome, is October 1, 2026. It’s the day federal Medicaid funding ends for the country’s most vulnerable populations, including refugees, asylees, and humanitarian parolees. The post How to Prepare Your Hospital Before H.R. 1 Hits in 2027 appeared first on MedCity News .
Merck’s Lipfendra is the first FDA-approved pill in the class of cholesterol-lowering drugs called PCSK9 inhibitors. While peptides are typically injected, Lipfendra is a macrocyclic peptide designed for formulation as an oral drug. The post Merck Pill Becomes First Oral Option in Growing Class of Cholesterol-Lowering Drugs appeared first on MedCity News .
What should life sciences investors and targets focus on for dealmaking success? Here are six actionable steps. The post Hybrid Financing in Life Sciences: Unlocking Growth Amid Market Challenges appeared first on MedCity News .
Here’s what healthcare entities should know about the maturing landscape, what to actually be concerned about, and the next stage of healthcare data evolution as we know it. The post Are We Entering an Interoperability Trust Recession? appeared first on MedCity News .
Women’s health startups should plan for reimbursement early, as limited research and evidence can make securing coverage difficult, a new report explains. The post The Reimbursement Challenges Hurting Women’s Health Companies, Per Milken Institute appeared first on MedCity News .
Vogenx’s mizagliflozin is heading into Phase 2b testing for post-bariatric hypoglycemia (PBH). Amylyx Pharmaceuticals and Recordati are developing injectable peptide drugs for this metabolic disorder, but Vogenx aims to stand apart by offering patients a different mechanism of action and oral dosing. The post Vogenx IPO Raises $81M for Trial in Metabolic Disease With No Approved Drugs appeared first on MedCity News .
The bottleneck in AI-enabled real-world data analysis is not computation, model architecture, or training data volume. It is the semantic layer over which the AI is trying to reason – the place where precise clinical meaning lives. The post Better Models Won’t Fix Pharma’s AI Problem — Better Terminology Will appeared first on MedCity News .
When payors consider only the cost of the medication and not the cost and risk to the patient, doctor, and healthcare system, the irony is that not only is this terrible for patient health, it can be more costly in the end. The post The True Cost of Focusing on Cost Instead of Cost-Effectiveness appeared first on MedCity News .
Article URL: https://12gramsofcarbon.com/p/colleges-have-an-education-problem Comments URL: https://news.ycombinator.com/item?id=48878536 Points: 2 # Comments: 0
Latigo Biotherapeutics will apply the IPO proceeds toward a pipeline that includes a next-generation non-opioid pain drug ready for pivotal testing. BlossomHill Therapeutics also debuted on the Nasdaq, raising cash for cancer drugs designed to address mutations not covered by currently available therapies. The post Latigo Bio’s IPO Lands $346M for Pipeline of Non-Opioid Pain Drugs appeared first on MedCity News .
The problem may not be the investment. It may be the target of the intervention. The post Why Kidney Care’s Biggest Investment Wave Hasn’t Moved Hospital Costs appeared first on MedCity News .
A letter to Medicaid Directors, State Leaders, and other invested collaborators who were awarded Rural Health Transformation (RHT) Grant funding. The post My Wish For Better Care For Americans Living in Rural Areas appeared first on MedCity News .
Apnimed will apply the IPO proceeds toward the regulatory process and launch plans of Oxnimbi, a once-nightly pill developed for obstructive sleep apnea. This drug is under FDA review with a February 2027 target date for a regulatory decision. The post Apnimed’s IPO Bags $192M for What Could Become the First Oral Sleep Apnea Drug appeared first on MedCity News .
Health tech companies made several major funding announcements in July. Here is a list of some of the biggest funding rounds. The post 4 Notable Health Tech Funding Announcements in July appeared first on MedCity News .
The future of value-based care will hinge on empowering providers, and specialists in particular, with the data and strategic partnerships to proactively manage patient health beyond traditional clinical settings. The post The Next Phase of Value-Based Care: Why Specialty-Led Models Will Define the Future of Healthcare appeared first on MedCity News .
Hope is a catalyst for scientific ambition. It encourages researchers, clinicians, investors, and innovators to pursue solutions where none currently exist. In oncology, many major breakthroughs begin with the belief that a better answer is possible. The post Hope Is Not a Soft Concept, It’s a Strategic Imperative in Cancer Innovation appeared first on MedCity News .
Article URL: https://www.journals.uchicago.edu/doi/abs/10.1086/665536 Comments URL: https://news.ycombinator.com/item?id=34203098 Points: 48 # Comments: 61