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Unobserved counterfactuals in sequential decision systems systematically under-expose marginalized groups and can amplify exclusion; modelling model- and feedback-uncertainty and using uncertainty-aware exploration reduces outcome variance for disadvantaged groups without sacrificing expected institutional utility.
low theoretical Full text arxiv
Fairness under uncertainty in sequential decisions · Michelle Seng Ah Lee, Kirtan Padh, David Watson, Niki Kilbertus, Jatinder Singh · Apr 23, 2026
Agentic AI promises sharper market efficiency and liquidity but brings new systemic and regulatory risks; unless governance, monitoring and interpretability tools keep pace, autonomous trading systems could amplify instability.
n/a review_meta Full text arxiv
Agentic Artificial Intelligence in Finance: A Comprehensive Survey · Irene Aldridge, Jolie An, Riley Burke, Michael Cao, Chia-Yi Chien, Kexin Deng, R... · Apr 23, 2026
Coupling LSTM demand forecasts with MILP optimization meaningfully improves supply‑chain performance: forecasting errors fall ~12–15%, inventory cost drops 5.4%, stockouts decline 27.5% and service levels rise to 97.8% in textile and PPE datasets.
medium descriptive Full text arxiv
Hybrid Deep Learning Approach for Coupled Demand Forecasting and Supply Chain Optimization · Nusrat Yasmin Nadia, Md Habibul Arif, Habibor Rahman Rabby, Md Iftekhar Monzur T... · Apr 23, 2026
A Probabilistic Innovation Methodology proposes that organised, real-time crowdsourced R&D can convert open-ended uncertainty into governable probabilistic search, shifting innovation from opaque guessing toward testable, steerable discovery; as AI reduces ideation costs, the paper argues, the primary bottlenecks become coordination, adjudication and validation.
n/a theoretical Summary semantic_scholar
Probabilistic Innovation Methodology: A Scientific Methodology for Real-Time Problem Solving in Complex Systems. Formalising Crowdsourced R&D, Hackathon-Type Search, and Epistemic Mode Transitions · Christian Callaghan · Fetched Apr 23, 2026
Agentic AI could speed chip and physical-design R&D by automating workflow, heuristic discovery and tool use; current evidence is promising but largely limited to prototypes, benchmark fragments and lab demonstrations.
n/a review_meta Summary semantic_scholar
Invited: Agentic AI for Physical Design R&D: Status and Prospects · Amur Ghose, Andrew B. Kahng, Sayak Kundu, Bodhisatta Pramanik · Fetched Apr 23, 2026
Large language models tilt toward government-intervention explanations: across 1,056 ideology-contested economic cases, 18 of 20 models are more accurate when the true effect aligns with intervention-friendly expectations and, when wrong, disproportionately predict intervention-oriented effects, a bias that one-shot prompting does not remove.
medium descriptive Full text arxiv
Ideological Bias in LLMs' Economic Causal Reasoning · Donggyu Lee, Hyeok Yun, Jungwon Kim, Junsik Min, Sungwon Park, Sangyoon Park, Ji... · Apr 23, 2026
As machines become autonomous, market efficiency must be redefined: the authors show that competitive markets can remain Pareto optimal only after welfare is conditioned on agents' autonomy and appropriate delegation and verification institutions are in place; the standard theorem appears as the special case when AI autonomy is negligible.
n/a theoretical Full text arxiv
Post-AGI Economies: Autonomy and the First Fundamental Theorem of Welfare Economics · Elija Perrier · Apr 23, 2026
Digital tools — from IoT to AI — materially strengthen supply-chain resilience by improving visibility, which accounts for roughly two-thirds of the resilience gains; the benefits are largest in complex, technology-intensive industries.
medium quasi_experimental Full text openalex
The Role of Digital Technologies in Enhancing Supply Chain Visibility and Resilience · Selorm Aniwa · Apr 23, 2026
China’s AI pilot zones lift manufacturers’ ESG performance by spurring R&D and tighter environmental compliance; gains are strongest among private and high‑tech firms and where firms allocate resources and operate efficiently.
medium quasi_experimental Summary openalex
The Impact of National New-Generation Artificial Intelligence Innovation and Development Pilot Zone Construction on ESG Performance of Manufacturing Enterprises · Yi Cao, Zhou Lan, Jie Dong, Ling Cao · Apr 23, 2026
AI's impact on jobs is uneven: routine-heavy industries face the greatest automation risk, whereas knowledge sectors see augmentation and rising skill demands. Policymakers and firms must prioritize targeted re-skilling and sectoral risk assessments to manage workforce transitions.
medium review_meta Full text openalex
AI and the Future of Job Profiles: A systematic Review of Sectoral Job Transformation, Risks and Future Impacts · Shrivastava Anshul, P Rohit Kumar, Sharma Anil Kumar · Apr 23, 2026
Intelligent management systems are recasting firms as 'algorithmic enterprises' that can optimize strategy and operations in real time, but they concentrate data power and blur lines of accountability.
n/a theoretical Full text openalex
Algorithmic Enterprises: Rethinking Firm Strategy in the Age of Intelligent Management Systems · Swaraj Dash · Apr 23, 2026
Gender-diverse boards curb corporate tax avoidance, and firms that deploy AI see a larger governance effect; AI capability amplifies the tax‑compliance role of diverse boards in developing‑country firms.
medium quasi_experimental Summary openalex
AI-Enabled Governance: Board Gender Diversity and Corporate Tax Avoidance · Marwan Mansour, Mo’taz Al Zobi, Ahmad Marei, Luay Daoud, Nour Ibrahim Kurdi · Apr 23, 2026
Microsoft 365 Copilot is seen as user-friendly and reliable and yields clear efficiency gains for administrative work in a research institute, while researchers' productivity views improve only with role-specific training and governance measures.
low descriptive Full text openalex
Generative KI in der Wissensarbeit: Wahrnehmung, Nutzen und Akzeptanz von Microsoft 365 Copilot · Carsten F. Schmidt, Sophie Petzolt, Wolfgang Beinhauer, Ingo Weber, Stefan Lange... · Apr 23, 2026
Generative AI can erode its own value: individually rational use drives model collapse that lowers social welfare, with habits spreading harmless-seeming use into high‑value tasks and magnifying damage.
n/a theoretical Full text openalex
Generative artificial intelligence reduces social welfare through model collapse · Fabian Baumann, Erol Akçay, Joshua B. Plotkin · Apr 23, 2026
A four-pillar governance framework (Accountability, Transparency, Fairness, Compliance) offers a practical route for fintechs and regulators to curb algorithmic bias in SME lending; expert validators gave the model strong relevance (mean 4.6/5), though the framework still needs empirical field testing to confirm impacts on inclusion and credit outcomes.
medium review_meta Summary openalex
Corporate-Governance-Driven Algorithmic Fairness in SME Fintech Lending: A Systematic Literature Review with Expert Validation · Chloe Victoria, Daniel Müller · Apr 23, 2026
A two‑level 'harness evolution' framework promises to eliminate manual prompt, tool and orchestration engineering by auto‑evolving agent harnesses and the protocol that evolves them, enabling rapid adaptation of AI agents to new domain workflows.
n/a theoretical Full text arxiv
The Last Harness You'll Ever Build · Haebin Seong, Li Yin, Haoran Zhang · Apr 22, 2026
Value alignment is a governance problem, not just an engineering puzzle: misalignment stems from objective-setting, information flows and whose interests count, so durable solutions require institutions and contested decision‑making rather than only model tweaks.
n/a theoretical Full text arxiv
Relative Principals, Pluralistic Alignment, and the Structural Value Alignment Problem · Travis LaCroix · Apr 22, 2026
A large study of 6,000 live coding-agent sessions finds agents either write almost all or none of committed code — 41% 'vibe coding' versus 23% human-only — yet only 44% of agent-produced code survives into commits and agent contributions carry more security flaws, with users pushing back in 44% of interactions.
medium descriptive Full text arxiv
SWE-chat: Coding Agent Interactions From Real Users in the Wild · Joachim Baumann, Vishakh Padmakumar, Xiang Li, John Yang, Diyi Yang, Sanmi Koyej... · Apr 22, 2026
AI-assisted government summaries underrepresent dissent: Canada's 2025–26 AI Strategy consultation summaries excluded 15–17% of participants and performed 8–9 percentage points worse than a random-participant baseline, with critics of AI facing the highest exclusion rates.
medium correlational Full text arxiv
Participatory provenance as representational auditing for AI-mediated public consultation · Sachit Mahajan · Apr 22, 2026
Large language models reliably flag fraudulent investment opportunities and resist motivated persuasion more than lay humans; in controlled tests humans endorsed fraud ~13–14% of the time while tested LLMs never did, and motivated framing did not suppress — and slightly increased — AI warnings.
high rct Full text arxiv
Large Language Models Outperform Humans in Fraud Detection and Resistance to Motivated Investor Pressure · Nattavudh Powdthavee · Apr 22, 2026
Structuring GenAI-driven development with executable requirements and architectural artifacts curbs agent drift and moves engineers from line-by-line coding to higher-level design work; early lab tests on a web app show improved traceability and maintainability compared with unstructured vibe coding.
low descriptive Full text arxiv
Shift-Up: A Framework for Software Engineering Guardrails in AI-native Software Development -- Initial Findings · Petrus Lipsanen, Liisa Rannikko, François Christophe, Konsta Kalliokoski, Vlad S... · Apr 22, 2026
Firms that disclose using AI in financial reporting show better audit outcomes in Nigeria — fewer restatements and audit-fee patterns consistent with higher audit quality — partly because AI disclosure correlates with greater transparency and stronger internal controls.
medium correlational Full text semantic_scholar
Artificial Intelligence Adoption in Financial Reporting and Audit Quality: Evidence from Nigerian Listed Firms · Akomolehin Fo, Oluwaremi Jb, Aluko Or, Famoroti Jo · Fetched Apr 22, 2026
AI deployments depress operating margins initially for KOSDAQ firms — consistent with short‑term transition costs — while investors value AI as a growth option in ICT firms, which show significant increases in market valuation.
medium quasi_experimental Summary semantic_scholar
The Dynamic Causal Effects of Corporate AI Adoption on Profitability and Market Value : An Empirical Analysis of KOSDAQ Panel Data · Jungsoo Kim, Bong-Gi Baek · Fetched Apr 22, 2026
Industry-level national-account analysis suggests AI adoption raises measured productivity and reduces input and labor intensity while tilting employment toward younger, less-educated workers; however, estimates depend importantly on how and when AI pervasiveness is dated, highlighting substantial measurement uncertainty.
medium quasi_experimental Full text semantic_scholar
Early Estimates of the Impact of AI Within BEA’s Industry Economic Accounts · Tina Highfill, Jon D. Samuels · Fetched Apr 22, 2026
Selective forgetting makes LLM agents leaner, cleaner and safer: in controlled tests, memory-pruning mechanisms raised access efficiency by ~8.5% and improved content signal-to-noise by ~29%, while eliminating tested security risks; the paper argues forgetting is as important as remembering for deployed agents.
medium descriptive Full text arxiv
FSFM: A Biologically-Inspired Framework for Selective Forgetting of Agent Memory · Yingjie Gu, Wenjian Xiong, Liqiang Wang, Pengcheng Ren, Chao Li, Xiaojing Zhang,... · Apr 22, 2026