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Mojo cuts the costly Python-to-C++ translation tax in quant finance—delivering 20×–180× faster kernels on Apple Silicon and offering bit-exact reduction primitives to ease auditability—while GPU-scale advantages await measured validation.
low descriptive Full text arxiv
Mojo: A Promising Tool for Scalable Financial AI Efficiency · Henry Han · Jun 14, 2026
U.S. chip export controls coincided with a surge in China's embrace of open-source AI, accelerating an open-model ecosystem that spread through research and developer communities; these open models now underpin research and commercial activity across borders despite limited patent tracing.
medium descriptive Full text arxiv
U.S. Policies Unintentionally Accelerated China's Open AI Ecosystems · Wang Jin, Nadav Kunievsky, Bowen Lou, Tianshu Sun, James Evans · Jun 14, 2026
Biased writing assistants nudge students toward stereotypical career descriptions, cutting expressions of agency in essays about women. Neutral prompts avoid this effect, and male-target essays remain largely unaffected, revealing asymmetric bias transfer.
high rct Full text arxiv
Contaminated Collaboration: Measuring Gender Bias Transfer in LLM-Assisted Student Writing · Ariyan Hossain, Kazi Kamruzzaman Rabbi, Farig Sadeque, S M Taiabul Haque · Jun 14, 2026
Managers are increasingly sharing supervisory authority with algorithms; this paper maps 'algorithmic co‑supervision' into two meta‑dimensions (control collaboration and control enactment) and six classificatory dimensions to enable systematic comparison of hybrid human–algorithm supervisory arrangements.
n/a descriptive Full text openalex
A Taxonomy Of Algorithmic Co-Supervision · Furkan Ozdemir, Armin Alizadeh, Alexander Benlian · Jun 14, 2026
Generative AI is becoming a structural collaborator inside startups, allowing small teams to scale capacity and reconfigure roles and workflows; but the shift also creates new dependencies and coordination challenges that reshape how startups create operational, structural, innovation, and market value.
low descriptive Full text openalex
From Prompt To Process: Qualitative Insights On How Genai Use Rewrites Startup Structures · Melanie Schmidt, Sofia Schöbel · Jun 14, 2026
An agentic multi-agent system speeds product experimentation roughly tenfold in simulations, reducing time-to-validated-learning while keeping statistical rigor and decision traceability. By instrumenting a SaaS codebase and logging feature-level behaviour, the study turns agentic AI into a disciplined experimentation infrastructure rather than a generic assistant.
medium descriptive Full text openalex
Multi Agent Systems In The Lean Startup Cycle: Operationalising Dynamic Capabilities · Elias Jelinek, Hannes Rothe · Jun 14, 2026
A platform-built logo-AI reshapes demand: EPWK logo-design posts request a broader mix of skills after the tool’s launch, and heightened competition among freelancers explains part of the change.
medium quasi_experimental Full text openalex
Exploring The Effect Of Platform-Embedded Generative Ai On Skill Diversity: Evidence From An Online Labour Market · Fang Sun, L Liu · Jun 14, 2026
An LLM-powered forecasting tool cut cafeteria forecast errors by roughly 30% for new dishes while keeping staff in control via override features; qualitative sessions show humans still crucial for unusual or high-uncertainty situations.
medium descriptive Full text openalex
Schnitzel-Prediction: Designing Human-Ai Collaboration For Cafeteria Demand Forecasting · Justus Cappel, Timo Strohmann, Mara Burger, Marleen Voß, Jan vom Brocke · Jun 14, 2026
ML platform strategies split into four enduring archetypes: cloud orchestrators centralize and standardize around hyperscaler logic, while aggregators and niche specialists adopt openness to cultivate innovation and ecosystem diversity; these non‑hyperscaler models offer a viable alternative to hyperscaler dominance in the AI economy.
n/a theoretical Full text openalex
An Ai Economy Beyond Big Tech Hyperscalers? A Taxonomy Of Machine Learning Platform Business Models · Mark de Reuver, Jo Lynn Tan, Hanieh Khodaei · Jun 14, 2026
New York’s mandated bias audits for hiring algorithms are weakened by major demographic data gaps—missingness in audit reports ranges from under 3% to over 50%—undermining the validity of reported fairness metrics. The authors argue many audits risk being symbolic and recommend using audit outputs for red‑teaming, improved data quality, and stronger oversight to make audits meaningful.
low descriptive Full text openalex
Towards Using Ai Bias Audits As Inputs For Red Teaming And Performance · Obi Ogbanufe · Jun 14, 2026
Generative AI shifts M&A IT strategy: LLM affordances let acquirers keep and revive target systems instead of automatically ripping them out, by increasing system transparency, lowering perceived personnel dependence, and cutting conversion costs.
low descriptive Full text openalex
From Knowledge Loss To Knowledge Leverage: How Gen Ai Affordances Transform Post-Merger Is Integration · Lena Erber, Ana Ortiz de Guinea, Dennis M. Steininger · Jun 14, 2026
AI is shifting the role of top executives from sole decision-makers to designers and governors of hybrid human–algorithm decision systems; firms' strategic outcomes will reflect how leaders configure, evaluate, and delegate to algorithmic decision logic.
n/a review_meta Full text openalex
Hybrid Upper Echelons: A Theorizing Review On Ai In Executive Decision-Making · Alisa Mehler, Andreas Hein, Helmut Krcmar · Jun 14, 2026
Platform owners coordinate ecosystems mainly via incentives, control and boundary resources; the arrival of algorithmic governance and generative AI is now reshaping how participation, quality and innovation are governed.
n/a review_meta Full text openalex
Mission: Orchestration – Governance Mechanisms And Future Research Directions In Digital Platform Ecosystems · Robert Woroch, Maximilian Schreieck, Leonardo Banh, Gero Strobel · Jun 14, 2026
Generative AI cuts users' motivation and perceived creative skills even as they rate their outputs the same; a randomized experiment shows GenAI assistance can undermine psychological resources that underlie creativity.
medium rct Full text openalex
When Ai Sparks Less: Generative Ai And The Decline Of Self-Perceived Creativity · Kathrin Endres, Frederik Schöttl, Lisa Baisch · Jun 14, 2026
AI that proposes alternatives and synthesizes (Dialectical Inquiry) yields larger informational gains but raises users' mental workload, while critique-only assistants deliver smaller gains with lower cognitive cost; targeted strategy training lessens the cognitive burden and improves net outcomes.
medium rct Full text openalex
Shaping The Tool Or Shaping The Mind: An Investigation Of Dual Pathways In Human-AI Strategic Decision-Making · Shuqing Liu, Kerr Manson, Thomas Ware, Dennis Galletta, Narayan Ramasubbu · Jun 14, 2026
Employees' willingness to keep using in-house GenAI hinges on managerial authorization: when firms embed AI but don't explicitly permit its use, workers report higher guilt and perceived risk and lower intentions to adopt; formal authorization reverses this effect.
medium quasi_experimental Full text openalex
The Role Of Embeddedness In Generative Ai Adoption: A Perspective On Employee Emotion And Risk Perception · Luisa Barton, Sascha Lichtenberg, Stefan Morana · Jun 14, 2026
Early AI deployment in a Nordic transit agency revealed that institutional control and worker autonomy co-evolve: governance seeks to constrain risks while employees appropriate AI to build capabilities, producing both tensions and synergies that shape organizational resilience.
low descriptive Summary openalex
Tensions And Synergies Between Digital Sovereignties In Ai Adoption · Maryam Washik, Silvia Masiero, Lena Hylving · Jun 14, 2026
Commons-governed AI offers a third institutional route between market and state: shared stewardship of data, compute, models and energy can be organized through Ostrom-style design principles. The paper maps ten archetypes and a maturity matrix, warning that scale, free-riding and sustainability remain core constraints.
low theoretical Full text arxiv
Commons-Governed Artificial Intelligence: A Taxonomy of Collective Governance · Eduardo C. Garrido-Merchán · Jun 13, 2026
Cognitive Trajectory Modeling reframes co-creative human-AI interaction as trajectories across cognitive attractor landscapes, arguing that temporal patterns are only interpretable when states carry directional cognitive meaning; the proposal clarifies conceptual distinctions but remains to be operationalized and empirically validated.
n/a theoretical Full text arxiv
Cognitive Trajectory Modeling: Quantifying Human-AI Co-Creation through Cognitively Grounded Interaction Trajectories · Nicholas Davis · Jun 13, 2026
Smart-farming tools can boost yields and resource efficiency, but uptake in India lags: small plots, weak rural connectivity, scarce digital skills and absent data standards block the promised productivity gains.
n/a review_meta Summary semantic_scholar
Digital Agriculture and Smart Farming: A Review of Emerging Technologies and Their Adoption Barriers · N. K. Singh, R. Divyadarshan, Manisha Shelke, C. Rajesh, N. Panotra, P. Anand, S... · Fetched Jun 13, 2026
Relying on AI as a substitute for human reasoning builds 'cognitive debt' and hidden systemic fragility, leading rational agents to over-adopt AI and trigger boom–bust cycles; even high-skilled users can erode unaided cognition over time.
n/a theoretical Full text arxiv
Cognitive Debt: AI as Intellectual Leverage and the Dynamics of Systemic Fragility · Shuchen Meng · Jun 13, 2026
A perfect proof checker cannot replace taste: formal results show that to cover unrecorded valuable mathematics an AI must produce an infinite stream of certified but trivial statements, and generators face a sharp coverage jump — from α/2 to 1−α/2 — once they allow infinitely many trivia.
n/a theoretical Full text arxiv
Flood and Harvest: The Provable Necessity of Trivia for Generating Valuable Mathematics via the Lens of Language Generation in the Limit · Xiaoyu Li, Andi Han, Dai Shi, Zheng Gao, Jiaojiao Jiang, Junbin Gao · Jun 12, 2026
Open-source projects lack consistent rules for autonomous AI contributors: a comparison of six major organisations finds fragmented policies that fail to cover recurring agent-driven incidents across six governance dimensions, and proposes a tiered, harmonised framework aligned to EU, NIST and ISO guidance.
medium descriptive Full text arxiv
Regulating the Machine Contributor: Governance and Policy Alignment in Open Source · Jassem Manita, Aziz Amari · Jun 12, 2026
LLM nudges help discovery, but only in narrow circumstances: non-local proposals increase yield when hypothesis spaces are compressed, proposals move orthogonally out of the explored span, and the remaining signal aligns with targets; randomly novel jumps or full‑rank hypothesis spaces yield no hybrid advantage.
medium theoretical Full text arxiv
Discovery under Hypothesis Redundancy: A Geometric Theory of Discovery Bottlenecks · Li Xia, Baoxun Wang · Jun 12, 2026
A blueprint for 'canonical' proof-carrying code promises order-of-magnitude cuts in the cost of routine software changes by removing accidental variation, but current evidence is preliminary and stops short of demonstrating preserved behavior, verification at scale, or real cost savings.
low theoretical Full text arxiv
No Accidental Software Agent First Canonical Code for Human Code Entropy Reduction and 30 to 500 times Lower Frontier Model Requirements · Jepson Taylor · Jun 12, 2026