Tootfinder

Addressing the Heterogeneity of Visualization in an Introductory PhD Course in the Swedish Context
Kostiantyn Kucher, Niklas R\"onnberg, Jonas L\"owgren
https://arxiv.org/abs/2508.08958

Addressing the Heterogeneity of Visualization in an Introductory PhD Course in the Swedish Context
Visualization is a heterogeneous field, and this aspect is often reflected by the organizational structures at higher education institutions that academic researchers in visualization and related fields including computer graphics, human-computer interaction, and media design are typically affiliated with. It may thus be a challenge for new PhD students to grasp the fragmented structure of their new workplace, form collegial relations across the institution, and to build a coherent picture of t…

The Signalgate Case is Waiving a Red Flag to All Organizational and Behavioral Cybersecurity Leaders, Practitioners, and Researchers: Are We Receiving the Signal Amidst the Noise?
Paul Benjamin Lowry, Gregory D. Moody, Robert Willison, Clay Posey
https://arxiv.org/abs/2509.07053

The Signalgate Case is Waiving a Red Flag to All Organizational and Behavioral Cybersecurity Leaders, Practitioners, and Researchers: Are We Receiving the Signal Amidst the Noise?
The Signalgate incident of March 2025, wherein senior US national security officials inadvertently disclosed sensitive military operational details via the encrypted messaging platform Signal, highlights critical vulnerabilities in organizational security arising from human error, governance gaps, and the misuse of technology. Although smaller in scale when compared to historical breaches involving billions of records, Signalgate illustrates critical systemic issues often overshadowed by a focu…

Friday Links 25-19
Small selection today. Some good reads, about the job market, corporate job, and a good podcasts about teams & AI.
https://christof.damian.net/2025/09/friday-links-25-19.html

Friday Links 25-19
Small selection today. Some good reads, about the job market, corporate job, and a good podcasts about teams & AI. Leadership Organizational...

Pattern-Based File and Data Access with Python Glob: A Comprehensive Guide for Computational Research
Sidney Shapiro
https://arxiv.org/abs/2509.08843 https://

Pattern-Based File and Data Access with Python Glob: A Comprehensive Guide for Computational Research
Pattern-based file access is a fundamental but often under-documented aspect of computational research. The Python glob module provides a simple yet powerful way to search, filter, and ingest files using wildcard patterns, enabling scalable workflows across disciplines. This paper introduces glob as a versatile tool for data science, business analytics, and artificial intelligence applications. We demonstrate use cases including large-scale data ingestion, organizational data analysis, AI datas…

Before the Super Bowls, the Chiefs were at rock bottom. One blueprint changed everything https://www.nytimes.com/athletic/6210303/2025/08/11/andy-reid-chiefs-leadership-clark-hunt/

"you have to try to build that strong organizational structure; one that isn’t so fragile that when one or two senior leaders change, things fall apart. But it’s very difficult and many organizations have weak management systems..."
https://

Getting In Contract with Large Language Models -- An Agency Theory Perspective On Large Language Model Alignment
Sascha Kaltenpoth, Oliver M\"uller
https://arxiv.org/abs/2509.07642

Getting In Contract with Large Language Models -- An Agency Theory Perspective On Large Language Model Alignment
Adopting Large language models (LLMs) in organizations potentially revolutionizes our lives and work. However, they can generate off-topic, discriminating, or harmful content. This AI alignment problem often stems from misspecifications during the LLM adoption, unnoticed by the principal due to the LLM's black-box nature. While various research disciplines investigated AI alignment, they neither address the information asymmetries between organizational adopters and black-box LLM agents nor con…

Network Contagion in Financial Labor Markets: Predicting Turnover in Hong Kong
Abdulla AlKetbi, Patrick Yam, Gautier Marti, Raed Jaradat
https://arxiv.org/abs/2509.08001 https:/…

Network Contagion in Financial Labor Markets: Predicting Turnover in Hong Kong
Employee turnover is a critical challenge in financial markets, yet little is known about the role of professional networks in shaping career moves. Using the Hong Kong Securities and Futures Commission (SFC) public register (2007-2024), we construct temporal networks of 121,883 professionals and 4,979 firms to analyze and predict employee departures. We introduce a graph-based feature propagation framework that captures peer influence and organizational stability. Our analysis shows a contagio…

Building organisational resilience through ISO 22301
"Today’s world is unpredictable. From cyber threats and pandemics to natural disasters, organizations must be ready to keep running, no matter what happens. A structured Business Continuity Management System – BCMS is no longer a luxury but a necessity. (...)
Understanding ISO 22301: A Framework for Resilience"

Interactions across multiple games: cooperation, corruption, and organizational design
Jonathan Bendor, Lukas Bolte, Nicole Immorlica, Matthew O. Jackson
https://arxiv.org/abs/2507.03030

Interactions across multiple games: cooperation, corruption, and organizational design
It is socially beneficial for teams to cooperate in some situations (``good games'') and not in others (``bad games;'' e.g., those that allow for corruption). A team's cooperation in any given game depends on expectations of cooperation in future iterations of both good and bad games. We identify when sustaining cooperation on good games necessitates cooperation on bad games. We then characterize how a designer should optimally assign workers to teams and teams to tasks that involve varying arr…

Do Ethical AI Principles Matter to Users? A Large-Scale Analysis of User Sentiment and Satisfaction
Stefan Pasch, Min Chul Cha
https://arxiv.org/abs/2508.05913 https://

Do Ethical AI Principles Matter to Users? A Large-Scale Analysis of User Sentiment and Satisfaction
As AI systems become increasingly embedded in organizational workflows and consumer applications, ethical principles such as fairness, transparency, and robustness have been widely endorsed in policy and industry guidelines. However, there is still scarce empirical evidence on whether these principles are recognized, valued, or impactful from the perspective of users. This study investigates the link between ethical AI and user satisfaction by analyzing over 100,000 user reviews of AI products …

Leveraging large language models for SQL behavior-based database intrusion detection
Meital Shlezinger, Shay Akirav, Lei Zhou, Liang Guo, Avi Kessel, Guoliang Li
https://arxiv.org/abs/2508.05690

Leveraging large language models for SQL behavior-based database intrusion detection
Database systems are extensively used to store critical data across various domains. However, the frequency of abnormal database access behaviors, such as database intrusion by internal and external attacks, continues to rise. Internal masqueraders often have greater organizational knowledge, making it easier to mimic employee behavior effectively. In contrast, external masqueraders may behave differently due to their lack of familiarity with the organization. Current approaches lack the granul…

From Model Design to Organizational Design: Complexity Redistribution and Trade-Offs in Generative AI
Sharique Hasan, Alexander Oettl, Sampsa Samila
https://arxiv.org/abs/2506.22440

From Model Design to Organizational Design: Complexity Redistribution and Trade-Offs in Generative AI
This paper introduces the Generality-Accuracy-Simplicity (GAS) framework to analyze how large language models (LLMs) are reshaping organizations and competitive strategy. We argue that viewing AI as a simple reduction in input costs overlooks two critical dynamics: (a) the inherent trade-offs among generality, accuracy, and simplicity, and (b) the redistribution of complexity across stakeholders. While LLMs appear to defy the traditional trade-off by offering high generality and accuracy throug…

Human-Hardware-in-the-Loop simulations for systemic resilience assessment in cyber-socio-technical systems
Francesco Simone, Marco Bortolini, Giovanni Mazzuto, Giulio di Gravio, Riccardo Patriarca
https://arxiv.org/abs/2509.06657

Human-Hardware-in-the-Loop simulations for systemic resilience assessment in cyber-socio-technical systems
Modern industrial systems require updated approaches to safety management, as the tight interplay between cyber-physical, human, and organizational factors has driven their processes toward increasing complexity. In addition to dealing with known risks, managing system resilience acquires great value to address complex behaviors pragmatically. This manuscript starts from the System-Theoretic Accident Model and Processes (STAMP) as a modelling initiative for such complexity. The STAMP can be nat…

FairLangProc: A Python package for fairness in NLP
Arturo P\'erez-Peralta, Sandra Ben\'itez-Pe\~na, Rosa E. Lillo
https://arxiv.org/abs/2508.03677 https://

FairLangProc: A Python package for fairness in NLP
The rise in usage of Large Language Models to near ubiquitousness in recent years has risen societal concern about their applications in decision-making contexts, such as organizational justice or healthcare. This, in turn, poses questions about the fairness of these models in critical settings, which leads to the developement of different procedures to address bias in Natural Language Processing. Although many datasets, metrics and algorithms have been proposed to measure and mitigate harmful …

🦜 Gossip, redefined: Research shows the surprising power of positive talk in teams
#work

Gossip, redefined: Research shows the surprising power of positive talk in teams
Mean Girls and pop culture has taught us to fear gossip as toxic and cruel, the whispered fuel of cliques and drama. But what if we've been getting gossip all wrong? New research from UNM's organizational behavior team suggests that some gossip might actually help teams thrive.

Rediscovering the Standard Model with AI
Aya Abdelhaq, Pellegrino Piantadosi, Fernando Quevedo
https://arxiv.org/abs/2508.04923 https://arxiv.org/pdf/2508.…

Rediscovering the Standard Model with AI
We investigate whether artificial intelligence can autonomously recover known structures of the Standard Model of particle physics using only experimental data and without theoretical inputs. By applying unsupervised machine learning techniques -- including data dimensionality reduction and clustering algorithms -- to intrinsic particle properties and decay modes, we uncover key organizational features of particle physics, such as the relative strength of different interactions and the differen…

Cross-Organizational Analysis of Parliamentary Processes: A Case Study
Paul-Julius Hillmann, Stephan A. Fahrenkrog-Petersen, Jan Mendling
https://arxiv.org/abs/2508.10381 https:…

Cross-Organizational Analysis of Parliamentary Processes: A Case Study
Process Mining has been widely adopted by businesses and has been shown to help organizations analyze and optimize their processes. However, so far, little attention has gone into the cross-organizational comparison of processes, since many companies are hesitant to share their data. In this paper, we explore the processes of German state parliaments that are often legally required to share their data and run the same type of processes for different geographical regions. This paper is the first…

The Midas Project and Tech Oversight Project release The OpenAI Files, a 50 page analysis of OpenAI's governance, leadership, and organizational culture (Hayden Field/The Verge)
https://www.theverge.com/openai/688783/the

The ‘OpenAI Files’ will help you understand how Sam Altman’s company works
Two tech industry watchdog organizations released a research report called the OpenAI Files that covers OpenAI’s corporate structure, its restructuring to a for-profit organization, CEO Sam Altman’s portfolio of investment companies, and more.

Assessing security and privacy
I sometimes get asked how I think about and evaluate the security and privacy of Internet services and applications. For me, a number of factors come into focus when assessing the privacy of an application or service. Some of the factors are technological and some of them are human, social and organizational. Additionally, some of the factors are critical to ensure privacy and some are important but less critical.
 
I think we need a new model …

An Ethically Grounded LLM-Based Approach to Insider Threat Synthesis and Detection
Haywood Gelman, John D. Hastings, David Kenley
https://arxiv.org/abs/2509.06920 https://

An Ethically Grounded LLM-Based Approach to Insider Threat Synthesis and Detection
Insider threats are a growing organizational problem due to the complexity of identifying their technical and behavioral elements. A large research body is dedicated to the study of insider threats from technological, psychological, and educational perspectives. However, research in this domain has been generally dependent on datasets that are static and limited access which restricts the development of adaptive detection models. This study introduces a novel, ethically grounded approach that u…

Agentic AI in 6G Software Businesses: A Layered Maturity Model
Muhammad Zohaib, Muhammad Azeem Akbar, Sami Hyrynsalmi, Arif Ali Khan
https://arxiv.org/abs/2508.03393 https://

Agentic AI in 6G Software Businesses: A Layered Maturity Model
The emergence of agentic AI systems in 6G software businesses presents both strategic opportunities and significant challenges. While such systems promise increased autonomy, scalability, and intelligent decision-making across distributed environments, their adoption raises concerns regarding technical immaturity, integration complexity, organizational readiness, and performance-cost trade-offs. In this study, we conducted a preliminary thematic mapping to identify factors influencing the adopt…

After having looked at eIDAS and the dutch implementation of digital identity, it is very interesting to read this paper, a proposal that tries to improve on various aspects from eiDAS.
"An Architecture for Distributed Digital Identities in the Physical World"
https://arxiv.org/abs/2508.10185

An Architecture for Distributed Digital Identities in the Physical World
Digital identities are increasingly important for mediating not only digital but also physical service transactions. Managing such identities through centralized providers can cause both availability and privacy concerns: single points of failure and control are ideal targets for global attacks on technical, organizational, or legal fronts. We design, analyze, and build a distributed digital identity architecture for physical world transactions in common scenarios like unlocking doors, public t…

This seems like a cry for help from a few remaining honest individuals at #openai:
https://www.openaifiles.org/
This is why I do not use their LLMs, regardless how powerful their models might be. W…

The OpenAI Files
The OpenAI Files is the most comprehensive collection to date of documented concerns with governance practices, leadership integrity, and organizational culture at OpenAI.

Active Filaments on Curved Surfaces: From Single Filaments to Dilute Suspensions
Giulia Janzen, Euan D. Mackay, Rastko Sknepnek, D. A. Matoz-Fernandez
https://arxiv.org/abs/2507.23616

Active Filaments on Curved Surfaces: From Single Filaments to Dilute Suspensions
Curvature plays a central organizational role in active polymer dynamics. Using large-scale Langevin-dynamics simulations, we study active semiflexible filaments confined to smooth curved surfaces and map how curvature, bending rigidity, and activity interact. We find geodesic alignment, curvature lensing, and curvature-induced trapping. In particular, regions of negative Gaussian curvature localize filaments and hinder global surface exploration. These results show how surface geometry can be …

I am very happy to announce that our big architecture paper for the Digidow project on distributed digital identity systems with biometric authentication for physical interaction is now online on arXiv: https://arxiv.org/abs/2508.10185.
While it can't have all the details, it summarizes the main de…

An Architecture for Distributed Digital Identities in the Physical World
Digital identities are increasingly important for mediating not only digital but also physical service transactions. Managing such identities through centralized providers can cause both availability and privacy concerns: single points of failure and control are ideal targets for global attacks on technical, organizational, or legal fronts. We design, analyze, and build a distributed digital identity architecture for physical world transactions in common scenarios like unlocking doors, public t…

Fairness for the People, by the People: Minority Collective Action
Omri Ben-Dov, Samira Samadi, Amartya Sanyal, Alexandru \c{T}ifrea
https://arxiv.org/abs/2508.15374 https://

Fairness for the People, by the People: Minority Collective Action
Machine learning models often preserve biases present in training data, leading to unfair treatment of certain minority groups. Despite an array of existing firm-side bias mitigation techniques, they typically incur utility costs and require organizational buy-in. Recognizing that many models rely on user-contributed data, end-users can induce fairness through the framework of Algorithmic Collective Action, where a coordinated minority group strategically relabels its own data to enhance fairne…

What is digital about abstraction?
Bernhard Rieder
https://arxiv.org/abs/2508.18181 https://arxiv.org/pdf/2508.18181

What is digital about abstraction?
This chapter examines abstraction as a central principle of computing, not merely as a cognitive skill or epistemological category, but as a material and organizational practice that structures how software is built, used, and embedded in society. By tracing abstraction through historical developments in programming, operating systems, and networking, the text highlights its dual role in enabling modularity and layering while simultaneously shaping cultural, economic, and organizational forms. …

...John says if you focus on building the capability in the organization to understand variation and to appreciate how to use #data - then you are on the right path, and can increase your influence in addition.
“You need to build into the organization things like a focus on pleasing the customer instead of pleasing your boss.” When combining all of these methods, that is when your

Advocacy for Physics and for Physicists: Results of an Informal Survey of American Physical Society Members in 2025
Michael B. Bennett (for the Physics Advocacy Collaboration)
https://arxiv.org/abs/2506.24043

Advocacy for Physics and for Physicists: Results of an Informal Survey of American Physical Society Members in 2025
In the wake of a rash of executive orders and administrative actions aimed at shaping the scale, scope, and focus of the scientific enterprise in the United States during the second Trump Presidency, we have undertaken a survey of members of the American Physical Society, the country's pre-eminent physics professional society to investigate their needs, interests, and priorities, and how their interests may differ from organizational leadership's priorities. This report provides detail on the c…

Signed Higher-Order Interactions for Brain Disorder Diagnosis via Multi-Channel Transformers
Dengyi Zhao, Zhiheng Zhou, Guiying Yan, Dongxiao Yu, Xingqi Qi
https://arxiv.org/abs/2507.20205

Signed Higher-Order Interactions for Brain Disorder Diagnosis via Multi-Channel Transformers
Accurately characterizing higher-order interactions of brain regions and extracting interpretable organizational patterns from Functional Magnetic Resonance Imaging data is crucial for brain disease diagnosis. Current graph-based deep learning models primarily focus on pairwise or triadic patterns while neglecting signed higher-order interactions, limiting comprehensive understanding of brain-wide communication. We propose HOI-Brain, a novel computational framework leveraging signed higher-orde…

Why AI can't possibly make you more productive; long
#AI and "productivity", some thoughts:
Edit: fixed some typos.
Productivity is a concept that isn't entirely meaningless outside the context of capitalism, but it's a concept that is heavily inflected in a capitalist context. In many uses today it effectively means "how much you can satisfy and/or exceed your boss' expectations." This is not really what it should mean: even in an anarchist utopia, people would care about things like how many shirts they can produce in a week, although in an "I'd like to voluntarily help more people" way rather than an "I need to meet this quota to earn my survival" way. But let's roll with this definition for a second, because it's almost certainly what your boss means when they say "productivity", and understanding that word in a different (even if truer) sense is therefore inherently dangerous.
Accepting "productivity" to mean "satisfying your boss' expectations," I will now claim: the use of generative AI cannot increase your productivity.
Before I dive in, it's imperative to note that the big generative models which most people think of as constituting "AI" today are evil. They are 1: pouring fuel on our burning planet, 2: psychologically strip-mining a class of data laborers who are exploited for their precarity, 3: enclosing, exploiting, and polluting the digital commons, and 4: stealing labor from broad classes of people many of whom are otherwise glad to give that labor away for free provided they get a simple acknowledgement in return. Any of these four "ethical issues" should be enough *alone* to cause everyone to simply not use the technology. These ethical issues are the reason that I do not use generative AI right now, except for in extremely extenuating circumstances. These issues are also convincing for a wide range of people I talk to, from experts to those with no computer science background. So before I launch into a critique of the effectiveness of generative AI, I want to emphasize that such a critique should be entirely unnecessary.
But back to my thesis: generative AI cannot increase your productivity, where "productivity" has been defined as "how much you can satisfy and/or exceed your boss' expectations."
Why? In fact, what the fuck? Every AI booster I've met has claimed the opposite. They've given me personal examples of time saved by using generative AI. Some of them even truly believe this. Sometimes I even believe they saved time without horribly compromising on quality (and often, your boss doesn't care about quality anyways if the lack of quality is hard to measure of doesn't seem likely to impact short-term sales/feedback/revenue). So if generative AI genuinely lets you write more emails in a shorter period of time, or close more tickets, or something else along these lines, how can I say it isn't increasing your ability to meet your boss' expectations?
The problem is simple: your boss' expectations are not a fixed target. Never have been. In virtue of being someone who oversees and pays wages to others under capitalism, your boss' game has always been: pay you less than the worth of your labor, so that they can accumulate profit and thus more capital to remain in charge instead of being forced into working for a wage themselves. Sure, there are layers of management caught in between who aren't fully in this mode, but they are irrelevant to this analysis. It matters not how much you please your manager if your CEO thinks your work is not worth the wages you are being paid. And using AI actively lowers the value of your work relative to your wages.
Why do I say that? It's actually true in several ways. The most obvious: using generative AI lowers the quality of your work, because the work it produces is shot through with errors, and when your job is reduced to proofreading slop, you are bound to tire a bit, relax your diligence, and let some mistakes through. More than you would have if you are actually doing and taking pride in the work. Examples are innumerable and frequent, from journalists to lawyers to programmers, and we laugh at them "haha how stupid to not check whether the books the AI reviewed for you actually existed!" but on a deeper level if we're honest we know we'd eventually make the same mistake ourselves (bonus game: spot the swipe-typing typos I missed in this post; I'm sure there will be some).
But using generative AI also lowers the value of your work in another much more frightening way: in this era of hype, it demonstrates to your boss that you could be replaced by AI. The more you use it, and no matter how much you can see that your human skills are really necessary to correct its mistakes, the more it appears to your boss that they should hire the AI instead of you. Or perhaps retain 10% of the people in roles like yours to manage the AI doing the other 90% of the work. Paradoxically, the *more* you get done in terms of raw output using generative AI, the more it looks to your boss as if there's an opportunity to get enough work done with even fewer expensive humans. Of course, the decision to fire you and lean more heavily into AI isn't really a good one for long-term profits and success, but the modern boss did not get where they are by considering long-term profits. By using AI, you are merely demonstrating your redundancy, and the more you get done with it, the more redundant you seem.
In fact, there's even a third dimension to this: by using generative AI, you're also providing its purveyors with invaluable training data that allows them to make it better at replacing you. It's generally quite shitty right now, but the more use it gets by competent & clever people, the better it can become at the tasks those specific people use it for. Using the currently-popular algorithm family, there are limits to this; I'm not saying it will eventually transcend the mediocrity it's entwined with. But it can absolutely go from underwhelmingly mediocre to almost-reasonably mediocre with the right training data, and data from prompting sessions is both rarer and more useful than the base datasets it's built on.
For all of these reasons, using generative AI in your job is a mistake that will likely lead to your future unemployment. To reiterate, you should already not be using it because it is evil and causes specific and inexcusable harms, but in case like so many you just don't care about those harms, I've just explained to you why for entirely selfish reasons you should not use it.
If you're in a position where your boss is forcing you to use it, my condolences. I suggest leaning into its failures instead of trying to get the most out of it, and as much as possible, showing your boss very clearly how it wastes your time and makes things slower. Also, point out the dangers of legal liability for its mistakes, and make sure your boss is aware of the degree to which any of your AI-eager coworkers are producing low-quality work that harms organizational goals.
Also, if you've read this far and aren't yet of an anarchist mindset, I encourage you to think about the implications of firing 75% of (at least the white-collar) workforce in order to make more profit while fueling the climate crisis and in most cases also propping up dictatorial figureheads in government. When *either* the AI bubble bursts *or* if the techbros get to live out the beginnings of their worker-replacement fantasies, there are going to be an unimaginable number of economically desperate people living in increasingly expensive times. I'm the kind of optimist who thinks that the resulting social crucible, though perhaps through terrible violence, will lead to deep social changes that effectively unseat from power the ultra-rich that continue to drag us all down this destructive path, and I think its worth some thinking now about what you might want the succeeding stable social configuration to look like so you can advocate towards that during points of malleability.
As others have said more eloquently, generative AI *should* be a technology that makes human lives on average easier, and it would be were it developed & controlled by humanists. The only reason that it's not, is that it's developed and controlled by terrible greedy people who use their unfairly hoarded wealth to immiserate the rest of us in order to maintain their dominance. In the long run, for our very survival, we need to depose them, and I look forward to what the term "generative AI" will mean after that finally happens.

Batched Adaptive Network Formation
Yan Xu, Bo Zhou
https://arxiv.org/abs/2507.18961 https://arxiv.org/pdf/2507.18961

Batched Adaptive Network Formation
Networks are central to many economic and organizational applications, including workplace team formation, social platform recommendations, and classroom friendship development. In these settings, networks are modeled as graphs, with agents as nodes, agent pairs as edges, and edge weights capturing pairwise production or interaction outcomes. This paper develops an adaptive, or \textit{online}, policy that learns to form increasingly effective networks as data accumulates over time, progressive…

Organization Matters: A Qualitative Study of Organizational Dynamics in Red Teaming Practices For Generative AI
Bixuan Ren, EunJeong Cheon, Jianghui Li
https://arxiv.org/abs/2508.12504

Organization Matters: A Qualitative Study of Organizational Dynamics in Red Teaming Practices For Generative AI
The rapid integration of generative artificial intelligence (GenAI) across diverse fields underscores the critical need for red teaming efforts to proactively identify and mitigate associated risks. While previous research primarily addresses technical aspects, this paper highlights organizational factors that hinder the effectiveness of red teaming in real-world settings. Through qualitative analysis of 15 semi-structured interviews with red teamers from various organizations, we uncover chall…

Role-Aware Language Models for Secure and Contextualized Access Control in Organizations
Saeed Almheiri, Yerulan Kongrat, Adrian Santosh, Ruslan Tasmukhanov, Josemaria Vera, Muhammad Dehan Al Kautsar, Fajri Koto
https://arxiv.org/abs/2507.23465

Role-Aware Language Models for Secure and Contextualized Access Control in Organizations
As large language models (LLMs) are increasingly deployed in enterprise settings, controlling model behavior based on user roles becomes an essential requirement. Existing safety methods typically assume uniform access and focus on preventing harmful or toxic outputs, without addressing role-specific access constraints. In this work, we investigate whether LLMs can be fine-tuned to generate responses that reflect the access privileges associated with different organizational roles. We explore t…

Organisational justice moderates the link between leadership, work engagement and innovation work behaviour
Rahmat Sabuhari, Rusman Soleman, Marwan Man Soleman, Johan Fahri, Muhammad Rachmat
https://arxiv.org/abs/2508.20320

Organisational justice moderates the link between leadership, work engagement and innovation work behaviour
Regional civil servants in Indonesia, especially in the eastern regions, are now required to exhibit innovative work behavior (IWB) as mandated by national regulations. While transformational leadership (TFL) and work engagement (WE) are believed to foster such behavior, the impact and the moderating role of organizational justice (OJ) remain underexplored. This study addresses that gap by examining how TFL and WE contribute to IWB development within the context of public sector work, with OJ p…

Non Technical Debt in Agile Software Development
Muhammad Ovais Ahmad, Tomas Gustavsson
https://arxiv.org/abs/2509.01445 https://arxiv.org/pdf/2509.01445…

Non Technical Debt in Agile Software Development
NonTechnical Debt (NTD) is a common challenge in agile software development, manifesting in four critical forms, Process Debt, Social Debt, People Debt, Organizational debt. NODLA project is a collaboration between Karlstad University and four leading Swedish industrial partners, reveals how various debt types disrupt large scale Agile Software Development (ASD) environments. Through extensive surveys, indepth interviews, and statistical analyses involving a diverse group of software profession…

Would I regret being different? The influence of social norms on attitudes toward AI usage
Jaroslaw Kornowicz, Maurice Pape, Kirsten Thommes
https://arxiv.org/abs/2509.04241 htt…

Would I regret being different? The influence of social norms on attitudes toward AI usage
Prior research shows that social norms can reduce algorithm aversion, but little is known about how such norms become established. Most accounts emphasize technological and individual determinants, yet AI adoption unfolds within organizational social contexts shaped by peers and supervisors. We ask whether the source of the norm-peers or supervisors-shapes AI usage behavior. This question is practically relevant for organizations seeking to promote effective AI adoption. We conducted an online …

Modular versus Hierarchical: A Structural Signature of Topic Popularity in Mathematical Research
Brian Hepler
https://arxiv.org/abs/2506.22946 https://

Modular versus Hierarchical: A Structural Signature of Topic Popularity in Mathematical Research
Mathematical researchers, especially those in early-career positions, face critical decisions about topic specialization with limited information about the collaborative environments of different research areas. The aim of this paper is to study how the popularity of a research topic is associated with the structure of that topic's collaboration network, as observed by a suite of measures capturing organizational structure at several scales. We apply these measures to 1,938 algorithmically disc…

From Bits to Boardrooms: A Cutting-Edge Multi-Agent LLM Framework for Business Excellence
Zihao Wang, Junming Zhang
https://arxiv.org/abs/2508.15447 https://

From Bits to Boardrooms: A Cutting-Edge Multi-Agent LLM Framework for Business Excellence
Large Language Models (LLMs) have shown promising potential in business applications, particularly in enterprise decision support and strategic planning, yet current approaches often struggle to reconcile intricate operational analyses with overarching strategic goals across diverse market environments, leading to fragmented workflows and reduced collaboration across organizational levels. This paper introduces BusiAgent, a novel multi-agent framework leveraging LLMs for advanced decision-makin…

Are Enterprises Ready for Quantum-Safe Cybersecurity?
Tran Duc Le, Phuc Hao Do, Truong Duy Dinh, Van Dai Pham
https://arxiv.org/abs/2509.01731 https://arxi…

Are Enterprises Ready for Quantum-Safe Cybersecurity?
Quantum computing threatens to undermine classical cryptography by breaking widely deployed encryption and signature schemes. This paper examines enterprise readiness for quantum-safe cybersecurity through three perspectives: (i) the technologist view, assessing the maturity of post-quantum cryptography (PQC) and quantum key distribution (QKD); (ii) the enterprise (CISO/CIO) view, analyzing organizational awareness, risk management, and operational barriers; and (iii) the threat actor view, eva…

Data-Agnostic Cardinality Learning from Imperfect Workloads
Peizhi Wu, Rong Kang, Tieying Zhang, Jianjun Chen, Ryan Marcus, Zachary G. Ives
https://arxiv.org/abs/2506.16007

Data-Agnostic Cardinality Learning from Imperfect Workloads
Cardinality estimation (CardEst) is a critical aspect of query optimization. Traditionally, it leverages statistics built directly over the data. However, organizational policies (e.g., regulatory compliance) may restrict global data access. Fortunately, query-driven cardinality estimation can learn CardEst models using query workloads. However, existing query-driven models often require access to data or summaries for best performance, and they assume perfect training workloads with complete a…

Exploring Organizational Strategies in Immersive Computational Notebooks
Sungwon In, Ayush Roy, Eric Krokos, Kirsten Whitley, Chris North, Yalong Yang
https://arxiv.org/abs/2508.14346

Exploring Organizational Strategies in Immersive Computational Notebooks
Computational notebooks, which integrate code, documentation, tags, and visualizations into a single document, have become increasingly popular for data analysis tasks. With the advent of immersive technologies, these notebooks have evolved into a new paradigm, enabling more interactive and intuitive ways to perform data analysis. An immersive computational notebook, which integrates computational notebooks within an immersive environment, significantly enhances navigation performance with embo…

Secure coding for web applications: Frameworks, challenges, and the role of LLMs
Kiana Kiashemshaki, Mohammad Jalili Torkamani, Negin Mahmoudi
https://arxiv.org/abs/2507.22223 h…

Secure coding for web applications: Frameworks, challenges, and the role of LLMs
Secure coding is a critical yet often overlooked practice in software development. Despite extensive awareness efforts, real-world adoption remains inconsistent due to organizational, educational, and technical barriers. This paper provides a comprehensive review of secure coding practices across major frameworks and domains, including web development, DevSecOps, and cloud security. It introduces a structured framework comparison and categorizes threats aligned with the OWASP Top 10. Additional…

What Makes AI Applications Acceptable or Unacceptable? A Predictive Moral Framework
Kimmo Eriksson, Simon Karlsson, Irina Vartanova, Pontus Strimling
https://arxiv.org/abs/2508.19317

What Makes AI Applications Acceptable or Unacceptable? A Predictive Moral Framework
As artificial intelligence rapidly transforms society, developers and policymakers struggle to anticipate which applications will face public moral resistance. We propose that these judgments are not idiosyncratic but systematic and predictable. In a large, preregistered study (N = 587, U.S. representative sample), we used a comprehensive taxonomy of 100 AI applications spanning personal and organizational contexts-including both functional uses and the moral treatment of AI itself. In particip…

The Role of Excitatory Parvalbumin-positive Neurons in the Tectofugal Pathway of Pigeon (Columba livia) Hierarchical Visual Processing
Shan Lu, Xiaoteng Zhang, Yueyang Cang, Shihao Pan, Yanyan Peng, Xinwei Li, Shaoju Zeng, Yingjie Zhu, Li Shi
https://arxiv.org/abs/2507.15486

The Role of Excitatory Parvalbumin-positive Neurons in the Tectofugal Pathway of Pigeon (Columba livia) Hierarchical Visual Processing
The visual systems of birds and mammals exhibit remarkable organizational similarities: the dorsal ventricular ridge (DVR) demonstrates a columnar microcircuitry that parallels the cortical architecture observed in mammals. However, the specific neuronal subtypes involved and their functional roles in pigeon hierarchical visual processing remain unclear. This study investigates the role of excitatory parvalbumin (PV+) neurons within the Ento-MVL (entoallium-mesopallium venterolaterale) circuit …

The Accessibility Paradox: How Blind and Low Vision Employees Experience and Negotiate Accessibility in the Technology Industry
Aparajita Marathe, Anne Marie Piper
https://arxiv.org/abs/2508.18492

The Accessibility Paradox: How Blind and Low Vision Employees Experience and Negotiate Accessibility in the Technology Industry
Many technology companies aim to improve access and inclusion not only by making their products accessible but also by bringing people with disabilities into the tech workforce. We know less about how accessibility is experienced and negotiated by disabled workers within these organizations. Through interviews with 20 BLV workers across various tech companies, we uncover a persistent misalignment between organizational attempts at accessibility and the current realities of these employees. We i…

Nonlinear Rank Scaling and Hidden Structure in NHS Expenditure Transparency Data
Animotu Mohammed, Golnaz Shahtahmassebi, Haroldo V. Ribeiro, Jack Sutton, Quentin S. Hanley
https://arxiv.org/abs/2506.19520

Nonlinear Rank Scaling and Hidden Structure in NHS Expenditure Transparency Data
A variety of transparency initiatives have been introduced by governments to reduce corruption and allow citizens to independently evaluate effectiveness and efficiency of spending. In 2010, the UK government mandated transparency for many expenditures exceeding £25,000. The resulting data is dispersed across a range of governmental organizations and presents an opportunity to understand expenditure at scale, interrogate organizational structures and develop transparency measures. Here, we foc…

Network Structures as an Attack Surface: Topology-Based Privacy Leakage in Federated Learning
Murtaza Rangwala, Richard O. Sinnott, Rajkumar Buyya
https://arxiv.org/abs/2506.19260

Network Structures as an Attack Surface: Topology-Based Privacy Leakage in Federated Learning
Federated learning systems increasingly rely on diverse network topologies to address scalability and organizational constraints. While existing privacy research focuses on gradient-based attacks, the privacy implications of network topology knowledge remain critically understudied. We conduct the first comprehensive analysis of topology-based privacy leakage across realistic adversarial knowledge scenarios, demonstrating that adversaries with varying degrees of structural knowledge can infer s…

LLM-Assisted Semantic Alignment and Integration in Collaborative Model-Based Systems Engineering Using SysML v2
Zirui Li, Stephan Husung, Haoze Wang
https://arxiv.org/abs/2508.16181

LLM-Assisted Semantic Alignment and Integration in Collaborative Model-Based Systems Engineering Using SysML v2
Cross-organizational collaboration in Model-Based Systems Engineering (MBSE) faces many challenges in achieving semantic alignment across independently developed system models. SysML v2 introduces enhanced structural modularity and formal semantics, offering a stronger foundation for interoperable modeling. Meanwhile, GPT-based Large Language Models (LLMs) provide new capabilities for assisting model understanding and integration. This paper proposes a structured, prompt-driven approach for LLM…

A Node on the Constellation: The Role of Feminist Makerspaces in Building and Sustaining Alternative Cultures of Technology Production
Erin Gatz, Yasmine Kotturi, Andrea Afua Kwamya, Sarah Fox
https://arxiv.org/abs/2507.22329

A Node on the Constellation: The Role of Feminist Makerspaces in Building and Sustaining Alternative Cultures of Technology Production
Feminist makerspaces offer community led alternatives to dominant tech cultures by centering care, mutual aid, and collective knowledge production. While prior CSCW research has explored their inclusive practices, less is known about how these spaces sustain themselves over time. Drawing on interviews with 18 founders and members across 8 U.S. feminist makerspaces as well as autoethnographic reflection, we examine the organizational and relational practices that support long-term endurance. We …

How Do Community Smells Influence Self-Admitted Technical Debt in Machine Learning Projects?
Shamse Tasnim Cynthia, Nuri Almarimi, Banani Roy
https://arxiv.org/abs/2506.15884

How Do Community Smells Influence Self-Admitted Technical Debt in Machine Learning Projects?
Community smells reflect poor organizational practices that often lead to socio-technical issues and the accumulation of Self-Admitted Technical Debt (SATD). While prior studies have explored these problems in general software systems, their interplay in machine learning (ML)-based projects remains largely underexamined. In this study, we investigated the prevalence of community smells and their relationship with SATD in open-source ML projects, analyzing data at the release level. First, we ex…

The AI-Fraud Diamond: A Novel Lens for Auditing Algorithmic Deception
Benjamin Zweers, Diptish Dey, Debarati Bhaumik
https://arxiv.org/abs/2508.13984 https://

The AI-Fraud Diamond: A Novel Lens for Auditing Algorithmic Deception
As artificial intelligence (AI) systems become increasingly integral to organizational processes, they introduce new forms of fraud that are often subtle, systemic, and concealed within technical complexity. This paper introduces the AI-Fraud Diamond, an extension of the traditional Fraud Triangle that adds technical opacity as a fourth condition alongside pressure, opportunity, and rationalization. Unlike traditional fraud, AI-enabled deception may not involve clear human intent but can arise …

Exploiting AI for Attacks: On the Interplay between Adversarial AI and Offensive AI
Saskia Laura Schr\"oer, Luca Pajola, Alberto Castagnaro, Giovanni Apruzzese, Mauro Conti
https://arxiv.org/abs/2506.12519

Exploiting AI for Attacks: On the Interplay between Adversarial AI and Offensive AI
As Artificial Intelligence (AI) continues to evolve, it has transitioned from a research-focused discipline to a widely adopted technology, enabling intelligent solutions across various sectors. In security, AI's role in strengthening organizational resilience has been studied for over two decades. While much attention has focused on AI's constructive applications, the increasing maturity and integration of AI have also exposed its darker potentials. This article explores two emerging AI-relate…

From Firms to Computation: AI Governance and the Evolution of Institutions
Michael S. Harre
https://arxiv.org/abs/2507.13616 https://…

From Firms to Computation: AI Governance and the Evolution of Institutions
The integration of agential artificial intelligence into socioeconomic systems requires us to reexamine the evolutionary processes that describe changes in our economic institutions. This article synthesizes three frameworks: multi-level selection theory, Aoki's view of firms as computational processes, and Ostrom's design principles for robust institutions. We develop a framework where selection operates concurrently across organizational levels, firms implement distributed inference via game-…

Influencia de fatores organizacionais e sociais na etapa de levantamento de requisitos
Glauber da Rocha Balthazar, Marcia Ito
https://arxiv.org/abs/2508.13134 https://

Influencia de fatores organizacionais e sociais na etapa de levantamento de requisitos
The most critical and fragile stage of a software development project is requirements gathering. Because of this, Requirements Engineering has been evolving its techniques to minimize the challenges faced by Requirements Analysts. However, few studies consider the humanistic relationships and behaviors of those involved in this stage. This article presents a survey of some studies conducted at this stage that consider non-technical factors such as emotions, organizational environment, and socia…

An Architecture for Distributed Digital Identities in the Physical World
Ren\'e Mayrhofer, Michael Roland, Tobias H\"oller, Philipp Hofer, Mario Lins
https://arxiv.org/abs/2508.10185

An Architecture for Distributed Digital Identities in the Physical World
Digital identities are increasingly important for mediating not only digital but also physical service transactions. Managing such identities through centralized providers can cause both availability and privacy concerns: single points of failure and control are ideal targets for global attacks on technical, organizational, or legal fronts. We design, analyze, and build a distributed digital identity architecture for physical world transactions in common scenarios like unlocking doors, public t…