Tootfinder

Yet it comes with a big risk. That is, the incredible dependence of US stock market growth on the performance of a handful of tech giants. The Magnificent 7 - Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla - collectively comprise one third of the valuation of America's entire S&P 500.
BBC News - The Silicon Valley 'AI factory' at the heart of the tech race - BBC News

Blackstone President Jonathan Gray says AI risk is "top of our list" when evaluating deals; sources: the firm backed down from buying companies vulnerable to AI (Financial Times)
https://www.ft.com/content/35d80b4d-eecd-424b-9350-8da138036d7e

European Commission ‘simplification’ proposal would weaken GDPR, AI regulations https://therecord.media/european-commission-proposal-gdpr-ai-simplification

Privacy advocates see risk in new Meta policy that uses AI chats to serve targeted ads https://therecord.media/privacy-advocates-see-risks-meta-ai-ad-targeting

Despite worries by some that vendor reports on AI cyber threats are merely hype to sell new defensive tools, most cyber defenders and threat intel experts say CISOs who dismiss AI in the attack chain do so at their own risk.
Check out my latest CSO piece.
Many thanks to Marcus Hutchins, Steve Stone of SentinelOne, Billy Leonard of Google Threat Intelligence Group, the folks at Anthropic, Rob T. Lee of SANS Institute, Morgan Adamski of PwC, Joe Levy and Alexandra Rose of Sophos, …

Ignoring AI in the threat chain could be a costly mistake, experts warn
While some researchers dismiss reports of AI-driven cyberattacks as merely marketing messages, threat intel experts counter that CISOs ignore mounting evidence of AI use in the threat chain at their own peril.

LinkedIn notifications.
(I’d rather my air carrier not be using AI but here we are.)

Can Risk-taking AI-Assistants suitably represent entities
Ali Mazyaki, Mohammad Naghizadeh, Samaneh Ranjkhah Zonouzaghi, Amirhossein Farshi Sotoudeh
https://arxiv.org/abs/2510.08114

Can Risk-taking AI-Assistants suitably represent entities
Responsible AI demands systems whose behavioral tendencies can be effectively measured, audited, and adjusted to prevent inadvertently nudging users toward risky decisions or embedding hidden biases in risk aversion. As language models (LMs) are increasingly incorporated into AI-driven decision support systems, understanding their risk behaviors is crucial for their responsible deployment. This study investigates the manipulability of risk aversion (MoRA) in LMs, examining their ability to repl…

Summarised by my partner as "The bank of England is saying WATCH OUT CHAPS"...
https://www.theguardian.com/business/2025/oct/08/bank-of-england-warns-of-growing-risk-that-ai-bubble-could-burst

AI and Human Oversight: A Risk-Based Framework for Alignment
Laxmiraju Kandikatla, Branislav Radeljic
https://arxiv.org/abs/2510.09090 https://arxiv.org/pd…

AI and Human Oversight: A Risk-Based Framework for Alignment
As Artificial Intelligence (AI) technologies continue to advance, protecting human autonomy and promoting ethical decision-making are essential to fostering trust and accountability. Human agency (the capacity of individuals to make informed decisions) should be actively preserved and reinforced by AI systems. This paper examines strategies for designing AI systems that uphold fundamental rights, strengthen human agency, and embed effective human oversight mechanisms. It discusses key oversight…

Google's New AI Health Tool: Opt in or Risk Losing Benefits - Business Insider
https://www.businessinsider.com/google-ai-health-tool-opt-in-risk-losing-benefits-2025-10

New OpenAI models likely to pose "high" cybersecurity risk
OpenAI says the cyber capabilities of its frontier AI models are accelerating and warns Wednesday that upcoming models are likely to pose a "high" risk […]
😶‍🌫️ https://www.axios.com/2025/12/10/openai-ne

Exclusive: New OpenAI models likely pose "high" cybersecurity risk, company says
OpenAI says it's stepping up efforts to protect against attacks.

GiveDirectly plans to pilot a program using Google's AI-based Flood Hub, which provides forecast warnings, to send early aid to at-risk families in Bangladesh (Rest of World)
https://restofworld.org/2025/google-flood-hub-cash-aid/

AI flood forecasting allows aid to reach farmers before disaster strikes
Using Google’s Flood Hub, nonprofit trial program sends early warning and unconditional cash to workers.

Uncertainty-Aware, Risk-Adaptive Access Control for Agentic Systems using an LLM-Judged TBAC Model
Charles Fleming, Ashish Kundu, Ramana Kompella
https://arxiv.org/abs/2510.11414

Uncertainty-Aware, Risk-Adaptive Access Control for Agentic Systems using an LLM-Judged TBAC Model
The proliferation of autonomous AI agents within enterprise environments introduces a critical security challenge: managing access control for emergent, novel tasks for which no predefined policies exist. This paper introduces an advanced security framework that extends the Task-Based Access Control (TBAC) model by using a Large Language Model (LLM) as an autonomous, risk-aware judge. This model makes access control decisions not only based on an agent's intent but also by explicitly considerin…

If you ever wanted to know how these #AI datacenters can be financed, here is the explanation:
A creditworthy tech company (Meta, in this example) creates a "special purpose vehicle" #SPV, a box, where they put all the risk and all the debts coming with it.
Then they create a financia…

Geospatial Reasoning fuses weather, satellite and population
data with Gemini AI for risk analysis
It runs in Google's Trusted Tester program for early access
(That ain't you)
https://www.testingcatalog.com/google-laun…

Google launches geospatial reasoning system for disaster aid
What's new? Geospatial Reasoning fuses weather, satellite and population data with Gemini AI for risk analysis; it runs in Google's Trusted Tester program for early access;

Bias-Aware AI Chatbot for Engineering Advising at the University of Maryland A. James Clark School of Engineering
Prarthana P. Kartholy, Thandi M. Labor, Neil N. Panchal, Sean H. Wang, Hillary N. Owusu
https://arxiv.org/abs/2510.09636

Bias-Aware AI Chatbot for Engineering Advising at the University of Maryland A. James Clark School of Engineering
Selecting a college major is a difficult decision for many incoming freshmen. Traditional academic advising is often hindered by long wait times, intimidating environments, and limited personalization. AI Chatbots present an opportunity to address these challenges. However, AI systems also have the potential to generate biased responses, prejudices related to race, gender, socioeconomic status, and disability. These biases risk turning away potential students and undermining reliability of AI s…

"We are not Future-ready": Understanding AI Privacy Risks and Existing Mitigation Strategies from the Perspective of AI Developers in Europe
Alexandra Klymenko, Stephen Meisenbacher, Patrick Gage Kelley, Sai Teja Peddinti, Kurt Thomas, Florian Matthes
https://arxiv.org/abs/2510.00909

"We are not Future-ready": Understanding AI Privacy Risks and Existing Mitigation Strategies from the Perspective of AI Developers in Europe
The proliferation of AI has sparked privacy concerns related to training data, model interfaces, downstream applications, and more. We interviewed 25 AI developers based in Europe to understand which privacy threats they believe pose the greatest risk to users, developers, and businesses and what protective strategies, if any, would help to mitigate them. We find that there is little consensus among AI developers on the relative ranking of privacy risks. These differences stem from salient reas…

Police in Edmonton, Canada partner with Axon to test body cameras with AI facial recognition, and say the results will be verified by human officers (Associated Press)
https://apnews.com/article/ai-facial-recognition-axon-edmonton-21f319ce806a0…

AI-equipped police body cameras in Canada's Edmonton spark ethical concerns
Police in Edmonton, Canada, have started a pilot project using AI-equipped body cameras to detect faces on a "high risk" watch list. The move by Axon Enterprise, Inc. has raised ethical concerns, especially since the company previously paused facial recognition due to privacy issues. The pilot aims to enhance officer and public safety by identifying individuals flagged for a history of serious offenses. However, critics worry about societal risks and the lack of public debate. Axon CEO Rick Smi…

Responsible AI Technical Report
KT, :, Soonmin Bae, Wanjin Park, Jeongyeop Kim, Yunjin Park, Jungwon Yoon, Junhyung Moon, Myunggyo Oh, Wonhyuk Lee, Junseo Jang, Dongyoung Jung, Minwook Ju, Eunmi Kim, Sujin Kim, Youngchol Kim, Somin Lee, Wonyoung Lee, Minsung Noh, Hyoungjun Park, Eunyoung Shin
https://arxiv.org/abs/2509.20057

Responsible AI Technical Report
KT developed a Responsible AI (RAI) assessment methodology and risk mitigation technologies to ensure the safety and reliability of AI services. By analyzing the Basic Act on AI implementation and global AI governance trends, we established a unique approach for regulatory compliance and systematically identify and manage all potential risk factors from AI development to operation. We present a reliable assessment methodology that systematically verifies model safety and robustness based on KT'…

»Are AI browsers worth the security risk? Why experts are worried.
There are a lot of 'what ifs' surrounding AI browsers right now.«
Unfortunately, many people do not see this in my opinion and voluntarily allow themselves to be excluded by their laziness.
👉 https://www.

Are AI browsers worth the security risk? Why experts are worried
There are a lot of 'what ifs' surrounding AI browsers right now.

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/8]:
- Leveraging Large Language Models for Cybersecurity Risk Assessment -- A Case from Forestry Cyber-...
Fikret Mert G\"ultekin, Oscar Lilja, Ranim Khojah, Rebekka Wohlrab, Marvin Damschen, Mazen Mohamad

Ethical AI prompt recommendations in large language models using collaborative filtering
Jordan Nelson, Almas Baimagambetov, Konstantinos Avgerinakis, Nikolaos Polatidis
https://arxiv.org/abs/2510.06924

Ethical AI prompt recommendations in large language models using collaborative filtering
As large language models (LLMs) shape AI development, ensuring ethical prompt recommendations is crucial. LLMs offer innovation but risk bias, fairness issues, and accountability concerns. Traditional oversight methods struggle with scalability, necessitating dynamic solutions. This paper proposes using collaborative filtering, a technique from recommendation systems, to enhance ethical prompt selection. By leveraging user interactions, it promotes ethical guidelines while reducing bias. Contri…

Wow. I've dealt with various toxic personalities in software development, but a good portion of the time those toxic personalities were at least extremely knowledgeable in their (often, very limited) domain.
AI, however, seems to be enabling toxic personalities *who are completely clueless*. Impressive!
https://github…

Shadow Escape 0-Click Attack in AI Assistants Puts Trillions of Records at Risk
Operant AI reveals Shadow Escape, a zero-click attack using the MCP flaw in ChatGPT, Gemini, and Claude to secretly steal trillions of SSNs and financial data. Traditional security is blind to this new AI threat.
😶‍🌫️ https://

Shadow Escape 0-Click Attack in AI Assistants Puts Trillions of Records at Risk
Follow us on Bluesky, Twitter (X), Mastodon and Facebook at @Hackread

Replaced article(s) found for q-fin.PM. https://arxiv.org/list/q-fin.PM/new
[1/1]:
- Increase Alpha: Performance and Risk of an AI-Driven Trading Framework
Sid Ghatak, Arman Khaledian, Navid Parvini, Nariman Khaledian

Non-Invasive Detection of PROState Cancer with Novel Time-Dependent Diffusion MRI and AI-Enhanced Quantitative Radiological Interpretation: PROS-TD-AI
Baltasar Ramos, Cristian Garrido, Paulette Narv'aez, Santiago Gelerstein Claro, Haotian Li, Rafael Salvador, Constanza V'asquez-Venegas, Iv'an Gallegos, Yi Zhang, V'ictor Casta~neda, Cristian Acevedo, Dan Wu, Gonzalo C'ardenas, Camilo G. Sotomayor

Non-Invasive Detection of PROState Cancer with Novel Time-Dependent Diffusion MRI and AI-Enhanced Quantitative Radiological Interpretation: PROS-TD-AI
Prostate cancer (PCa) is the most frequently diagnosed malignancy in men and the eighth leading cause of cancer death worldwide. Multiparametric MRI (mpMRI) has become central to the diagnostic pathway for men at intermediate risk, improving de-tection of clinically significant PCa (csPCa) while reducing unnecessary biopsies and over-diagnosis. However, mpMRI remains limited by false positives, false negatives, and moderate to substantial interobserver agreement. Time-dependent diffusion (TDD) …

#SMBC on the risk that #AI is going to ruin #socialmedia: https://www.

#TIL GPT4o gibt täglich anhand veröffentlichter Artikel ein Ranking der globalen Krisen ab.
https://panthrisk.com/

Google DeepMind updates its Frontier Safety Framework to account for new risks, including the potential for models to resist shutdown or modification by humans (Ina Fried/Axios)
https://www.axios.com/2025/09/22/google-ai-risk-models-resist-shutdown

Google AI risk document spotlights risk of models resisting shutdown
Some advanced AI models have plotted or deceived users in order to achieve their goals.

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[8/13]:
- Improved Sample Complexity For Diffusion Model Training Without Empirical Risk Minimizer Access
Mudit Gaur, Prashant Trivedi, Sasidhar Kunapuli, Amrit Singh Bedi, Vaneet Aggarwal

AI is transforming how we predict hurricanes. NOAA is now using machine learning to analyze billions of data points, making forecasts more accurate than ever.
The results? Better rapid intensification predictions and stronger decision support for coastal communities at risk. As hurricane season wraps, this tech could be a game-changer for saving lives.

NOAA chief plugs AI in forecasting as hurricane season wraps
While no hurricanes struck the U.S., Hurricane Melissa left behind devastation in the Caribbean.

The 2025 OpenAI Preparedness Framework does not guarantee any AI risk mitigation practices: a proof-of-concept for affordance analyses of AI safety policies
Sam Coggins, Alex Saeri, Katherine A. Daniell, Lorenn P. Ruster, Jessie Liu, Jenny L. Davis
https://arxiv.org/abs/2509.24394

The 2025 OpenAI Preparedness Framework does not guarantee any AI risk mitigation practices: a proof-of-concept for affordance analyses of AI safety policies
Prominent AI companies are producing 'safety frameworks' as a type of voluntary self-governance. These statements purport to establish risk thresholds and safety procedures for the development and deployment of highly capable AI. Understanding which AI risks are covered and what actions are allowed, refused, demanded, encouraged, or discouraged by these statements is vital for assessing how these frameworks actually govern AI development and deployment. We draw on affordance theory to analyse t…

OpenAI says the cyber capabilities of its frontier AI models are accelerating and warns that upcoming models are likely to pose a "high" risk (Ina Fried/Axios)
https://www.axios.com/2025/12/10/openai-new-models-cybersecurity-risks

Exclusive: New OpenAI models likely pose "high" cybersecurity risk, company says
OpenAI says it's stepping up efforts to protect against attacks.

US CISA
Publication 3.12.2025
Principles for the Secure Integration of Artificial Intelligence in Operational Technology
https://www.cisa.gov/resources-tools/resources/principles-secure-integration-artificial…

Generative AI-Downscaling of Large Ensembles Project Unprecedented Future Droughts
Hamish Lewis, Neelesh Rampal, Peter B. Gibson, Luke J. Harrington, Chiara M. Holgate, Anna Ukkola, Nicola M. Maher
https://arxiv.org/abs/2509.21844

Generative AI-Downscaling of Large Ensembles Project Unprecedented Future Droughts
Understanding how droughts may change in the future is essential for anticipating and mitigating their adverse impacts. However, robust climate projections require large amounts of high-resolution climate simulations, particularly for assessing extreme events. Here, we use a novel dataset, multiple large-ensembles of Global Climate Models (GCMs), downscaled to 12km using generative AI, to quantify the future risk of meteorological drought across New Zealand. The ensembles consists of 20 GCMs, i…

Coverbase, an AI procurement and risk platform provider, raised a $16.5M Series A led by Canapi Ventures, bringing its total funding to $20M (Mary Ann Azevedo/Crunchbase News)
https://news.crunchbase.com/venture/coverbase-raise-ai-powered-procurement/

Exclusive: With Customers Like Okta And Coinbase, Coverbase Raises $16M To Grow AI-Powered Procurement...
Coverbase, an AI-powered procurement platform, has raised $16 million in a Series A round led by Canapi Ventures, the startup tells Crunchbase News exclusively.

Student Development Agent: Risk-free Simulation for Evaluating AIED Innovations
Jianxiao Jiang, Yu Zhang
https://arxiv.org/abs/2510.09183 https://arxiv.org…

Student Development Agent: Risk-free Simulation for Evaluating AIED Innovations
In the age of AI-powered educational (AIED) innovation, evaluating the developmental consequences of novel designs before they are exposed to students has become both essential and challenging. Since such interventions may carry irreversible effects, it is critical to anticipate not only potential benefits but also possible harms. This study proposes a student development agent framework based on large language models (LLMs), designed to simulate how students with diverse characteristics may ev…

BloomAPR: A Bloom's Taxonomy-based Framework for Assessing the Capabilities of LLM-Powered APR Solutions
Yinghang Ma (Jack), Jiho Shin (Jack), Leuson Da Silva (Jack), Zhen Ming (Jack), Jiang, Song Wang, Foutse Khomh, Shin Hwei Tan
https://arxiv.org/abs/2509.25465

BloomAPR: A Bloom's Taxonomy-based Framework for Assessing the Capabilities of LLM-Powered APR Solutions
Recent advances in large language models (LLMs) have accelerated the development of AI-driven automated program repair (APR) solutions. However, these solutions are typically evaluated using static benchmarks such as Defects4J and SWE-bench, which suffer from two key limitations: (1) the risk of data contamination, potentially inflating evaluation results due to overlap with LLM training data, and (2) limited ability to assess the APR capabilities in dynamic and diverse contexts. In this paper,…

Even More Kawaii than Real-Person-Driven VTubers? Understanding How Viewers Perceive AI-Driven VTubers
Yiluo Wei, Yupeng He, Gareth Tyson
https://arxiv.org/abs/2509.20817 https:…

Even More Kawaii than Real-Person-Driven VTubers? Understanding How Viewers Perceive AI-Driven VTubers
VTubers, digital personas represented by animated avatars, have gained massive popularity. Traditionally, VTubers are operated and voiced by human controllers known as Nakanohito. The reliance on Nakanohito, however, poses risks due to potential personal controversies and operational disruptions. The emergence of AI-driven VTubers offers a new model free from these human constraints. While AI-driven VTubers present benefits such as continuous operation and reduced scandal risk, they also raise …

A look at NY's RAISE Act, requiring AI companies to publish safety protocols and disclose serious incidents, as its co-sponsor is targeted by a pro-AI super PAC (Ashley Capoot/CNBC)
https://www.cnbc.com/2025/11/24/raise-act-new-yo…

Here's what's in the RAISE Act, a state-level AI bill opposed by Trump and industry leaders
The RAISE Act would require large AI companies to publish safety and risk protocols and disclose serious safety incidents. 

Assessment of deep learning models integrated with weather and environmental variables for wildfire spread prediction and a case study of the 2023 Maui fires
Jiyeon Kim, Yingjie Hu, Negar Elhami-Khorasani, Kai Sun, Ryan Zhenqi Zhou
https://arxiv.org/abs/2509.21327

Assessment of deep learning models integrated with weather and environmental variables for wildfire spread prediction and a case study of the 2023 Maui fires
Predicting the spread of wildfires is essential for effective fire management and risk assessment. With the fast advancements of artificial intelligence (AI), various deep learning models have been developed and utilized for wildfire spread prediction. However, there is limited understanding of the advantages and limitations of these models, and it is also unclear how deep learning-based fire spread models can be compared with existing non-AI fire models. In this work, we assess the ability of …

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[10/17]:
- Improved Sample Complexity For Diffusion Model Training Without Empirical Risk Minimizer Access
Mudit Gaur, Prashant Trivedi, Sasidhar Kunapuli, Amrit Singh Bedi, Vaneet Aggarwal

Societal Capacity Assessment Framework: Measuring Resilience to Inform Advanced AI Risk Management
Milan Gandhi, Peter Cihon, Owen Larter, Rebecca Anselmetti
https://arxiv.org/abs/2509.22742

Societal Capacity Assessment Framework: Measuring Resilience to Inform Advanced AI Risk Management
Risk assessments for advanced AI systems require evaluating both the models themselves and their deployment contexts. We introduce the Societal Capacity Assessment Framework (SCAF), an indicators-based approach to measuring a society's vulnerability, coping capacity, and adaptive capacity in response to AI-related risks. SCAF adapts established resilience analysis methodologies to AI, enabling organisations to ground risk management in insights about country-level deployment conditions. It can …

A look at CoreWeave, whose financing strategy involves using GPUs as collateral for large loans, which enabled rapid expansion but resulted in $11.2B in debt (Rashi Shrivastava/Forbes)
https://www.forbes.com/sites/rashishrivast

How CoreWeave’s GPU Bet Made Four Risk-Loving Cryptominers AI Billionaires
Creative financing and an enormous appetite for risk helped CoreWeave’s Michael Intrator ride the AI data center boom to a $6.7 billion personal fortune. But as bubble fears mount, his reliance on billions in debt to supply advanced chips to major AI players puts him in a powerful position.

A Comparative Analysis of Ensemble-Based Machine Learning Approaches with Explainable AI for Multi-Class Intrusion Detection in Drone Networks
Md. Alamgir Hossain, Waqas Ishtiaq, Md. Samiul Islam
https://arxiv.org/abs/2509.20391

A Comparative Analysis of Ensemble-Based Machine Learning Approaches with Explainable AI for Multi-Class Intrusion Detection in Drone Networks
The growing integration of drones into civilian, commercial, and defense sectors introduces significant cybersecurity concerns, particularly with the increased risk of network-based intrusions targeting drone communication protocols. Detecting and classifying these intrusions is inherently challenging due to the dynamic nature of drone traffic and the presence of multiple sophisticated attack vectors such as spoofing, injection, replay, and man-in-the-middle (MITM) attacks. This research aims t…

Assessing Human Rights Risks in AI: A Framework for Model Evaluation
Vyoma Raman, Camille Chabot, Betsy Popken
https://arxiv.org/abs/2510.05519 https://arx…

Assessing Human Rights Risks in AI: A Framework for Model Evaluation
The Universal Declaration of Human Rights and other international agreements outline numerous inalienable rights that apply across geopolitical boundaries. As generative AI becomes increasingly prevalent, it poses risks to human rights such as non-discrimination, health, and security, which are also central concerns for AI researchers focused on fairness and safety. We contribute to the field of algorithmic auditing by presenting a framework to computationally assess human rights risk. Drawing …

AnchoredAI: Contextual Anchoring of AI Comments Improves Writer Agency and Ownership
Martin Lou, Jackie Crowley, Samuel Dodson, Dongwook Yoon
https://arxiv.org/abs/2509.16128 ht…

AnchoredAI: Contextual Anchoring of AI Comments Improves Writer Agency and Ownership
Generative AI is increasingly integrated into writing support, yet current chat-based interfaces often obscure referential context and risk amplifying automation bias and overreliance. We introduce AnchoredAI, a novel system that anchors AI feedback directly to relevant text spans. AnchoredAI implements two key mechanisms: (1) an Anchoring Context Window (ACW) that maintains unique, context-rich references, and (2) an update-aware context retrieval method that preserves the intent of prior comm…

Cascade! Human in the loop shortcomings can increase the risk of failures in recommender systems
Wm. Matthew Kennedy, Nishanshi Shukla, Cigdem Patlak, Blake Chambers, Theodora Skeadas, Tuesday, Kingsley Owadara, Aayush Dhanotiya
https://arxiv.org/abs/2509.20099

Cascade! Human in the loop shortcomings can increase the risk of failures in recommender systems
Recommender systems are among the most commonly deployed systems today. Systems design approaches to AI-powered recommender systems have done well to urge recommender system developers to follow more intentional data collection, curation, and management procedures. So too has the "human-in-the-loop" paradigm been widely adopted, primarily to address the issue of accountability. However, in this paper, we take the position that human oversight in recommender system design also entails novel risk…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[6/6]:
- On the Security of Tool-Invocation Prompts for LLM-Based Agentic Systems: An Empirical Risk Asses...
Xie, Luo, Liu, Zhang, Zhang, Liu, Li, Chen, Wang, She

PISA: An AI Pipeline for Interpretable-by-design Survival Analysis Providing Multiple Complexity-Accuracy Trade-off Models
Thalea Schlender, Catharina J. A. Romme, Yvette M. van der Linden, Luc R. C. W. van Lonkhuijzen, Peter A. N. Bosman, Tanja Alderliesten
https://arxiv.org/abs/2509.22673

PISA: An AI Pipeline for Interpretable-by-design Survival Analysis Providing Multiple Complexity-Accuracy Trade-off Models
Survival analysis is central to clinical research, informing patient prognoses, guiding treatment decisions, and optimising resource allocation. Accurate time-to-event predictions not only improve quality of life but also reveal risk factors that shape clinical practice. For these models to be relevant in healthcare, interpretability is critical: predictions must be traceable to patient-specific characteristics, and risk factors should be identifiable to generate actionable insights for both cl…

A look at the social debates in Chile over AI investments, emblematic of clashes happening globally over balancing economic growth with environmental concerns (Paul Mozur/New York Times)
https://www.nytimes.com/2025/10/20/technology/chile-ai-politics.html

How Chile Embodies A.I.’s No-Win Politics
Political debates have flared across Chile over artificial intelligence. Should the nation pour billions into A.I. and risk public backlash, or risk being left behind?

An Analysis of the New EU AI Act and A Proposed Standardization Framework for Machine Learning Fairness
Mike Teodorescu, Yongxu Sun, Haren N. Bhatia, Christos Makridis
https://arxiv.org/abs/2510.01281 …

An Analysis of the New EU AI Act and A Proposed Standardization Framework for Machine Learning Fairness
The European Union's AI Act represents a crucial step towards regulating ethical and responsible AI systems. However, we find an absence of quantifiable fairness metrics and the ambiguity in terminology, particularly the interchangeable use of the keywords transparency, explainability, and interpretability in the new EU AI Act and no reference of transparency of ethical compliance. We argue that this ambiguity creates substantial liability risk that would deter investment. Fairness transparency…

Source: Trump allowed Nvidia to sell H200s to China after concluding the move carried a lower security risk as Huawei offers systems with comparable performance (Bloomberg)
https://www.bloomberg.com/news/articles/2025-12-09/t…

Increase Alpha: Performance and Risk of an AI-Driven Trading Framework
Sid Ghatak, Arman Khaledian, Navid Parvini, Nariman Khaledian
https://arxiv.org/abs/2509.16707 https://

Increase Alpha: Performance and Risk of an AI-Driven Trading Framework
There are inefficiencies in financial markets, with unexploited patterns in price, volume, and cross-sectional relationships. While many approaches use large-scale transformers, we take a domain-focused path: feed-forward and recurrent networks with curated features to capture subtle regularities in noisy financial data. This smaller-footprint design is computationally lean and reliable under low signal-to-noise, crucial for daily production at scale. At Increase Alpha, we built a deep-learning…

In an interview, Dario Amodei suggests some AI companies are taking on too much risk by "YOLO-ing" and committing to spend hundreds of billions on data centers (Shirin Ghaffary/Bloomberg)
https://www.bloomberg.com/news/articles/20

Invisible Saboteurs: Sycophantic LLMs Mislead Novices in Problem-Solving Tasks
Jessica Y. Bo, Majeed Kazemitabaar, Mengqing Deng, Michael Inzlicht, Ashton Anderson
https://arxiv.org/abs/2510.03667

Invisible Saboteurs: Sycophantic LLMs Mislead Novices in Problem-Solving Tasks
Sycophancy, the tendency of LLM-based chatbots to express excessive enthusiasm, agreement, flattery, and a lack of disagreement, is emerging as a significant risk in human-AI interactions. However, the extent to which this affects human-LLM collaboration in complex problem-solving tasks is not well quantified, especially among novices who are prone to misconceptions. We created two LLM chatbots, one with high sycophancy and one with low sycophancy, and conducted a within-subjects experiment (n=…

When MCP Servers Attack: Taxonomy, Feasibility, and Mitigation
Weibo Zhao, Jiahao Liu, Bonan Ruan, Shaofei Li, Zhenkai Liang
https://arxiv.org/abs/2509.24272 https://

When MCP Servers Attack: Taxonomy, Feasibility, and Mitigation
Model Context Protocol (MCP) servers enable AI applications to connect to external systems in a plug-and-play manner, but their rapid proliferation also introduces severe security risks. Unlike mature software ecosystems with rigorous vetting, MCP servers still lack standardized review mechanisms, giving adversaries opportunities to distribute malicious implementations. Despite this pressing risk, the security implications of MCP servers remain underexplored. To address this gap, we present the…

The UK's Cabinet Office says its Fraud Risk Assessment Accelerator AI tool helped the government recover £480M from fraud in the 12 months from April 2024 (Jack Fenwick/BBC)
https://www.bbc.com/news/articles/cpd92gpld0go

AI tool used to recover £500m lost to fraud, government says
Ministers say software developed by the Cabinet Office has helped to ramp up fraud detection.

Longitudinal and Multimodal Recording System to Capture Real-World Patient-Clinician Conversations for AI and Encounter Research: Protocol
Misk Al Zahidy, Kerly Guevara Maldonado, Luis Vilatuna Andrango, Ana Cristina Proano, Ana Gabriela Claros, Maria Lizarazo Jimenez, David Toro-Tobon, Oscar J. Ponce-Ponce, Juan P. Brito
https://arxiv.org…

Longitudinal and Multimodal Recording System to Capture Real-World Patient-Clinician Conversations for AI and Encounter Research: Protocol
The promise of AI in medicine depends on learning from data that reflect what matters to patients and clinicians. Most existing models are trained on electronic health records (EHRs), which capture biological measures but rarely patient-clinician interactions. These relationships, central to care, unfold across voice, text, and video, yet remain absent from datasets. As a result, AI systems trained solely on EHRs risk perpetuating a narrow biomedical view of medicine and overlooking the lived e…

Israeli startup Zafran, an AI-native threat exposure management service, raised a $60M Series C led by Menlo Ventures, bringing its total funding to $130M (Globes)
https://en.globes.co.il/en/article-israeli-startup-zafran-security-raises-60m-100152808…

Israeli startup Zafran Security raises $60m
Zafran has also launched its agentic exposure management suite, positioning it to complete the entire end-to-end lifecycle across asset inventory, vulnerability detection, risk assessment, and autonomous remediation workflows.

An in-depth look at TPUv7 Ironwood, the latest generation of Google's TPU, and how it positions Google as a serious challenger to Nvidia's AI chip dominance (Dylan Patel/SemiAnalysis)
https://newsletter.semianalysis.com/p/tpuv7-google-takes-a-swing-at-the

Google TPUv7: The 900lb Gorilla In the Room
Anthropic’s 1GW+ TPUs, New customers Meta/SSI/xAI/OAI, Full Stack Review of v7 Ironwood, CUDA Moat at risk, Next Generation TPUv8AX and TPUv8X versus Vera Rubin

Education software company EdSights, which uses SMS texting and AI to reach students and identify those at risk of dropping out, raised $80M from JMI Equity (Chris Metinko/Axios)
https://www.axios.com/pro/enterprise-software-deals/…

Exclusive: EdSights raises $80M from JMI Equity
The company is growing revenue 70% year to year.

London-based media monitoring and risk management company Signal AI raised $165M led by Battery Ventures, which will hold a majority stake after the investment (Daniel Thomas/Financial Times)
https://www.ft.com/content/d2913fba-a867-4b63-9fed-1dd2e1c65453