Skip to content

Category

explainable ai

2,749 papers

#explainable ai Book Open access Oct 2026

The Self-Undermining Assurance Problem: simulation notebook, results and reproducibility materials

Computational companion to The Self-Undermining Assurance Problem: Preserving Certifiability in Human–AI Knowledge Work. This release contains an executed simulation notebook, recorded dependencies, run records, tables, sensitivity and budget sweeps, analytical checks, and framework/figure generation scripts. The publi...

Habib Hamam · 0 citations
#explainable ai Conference Open access Oct 2026

Mediational Opacity: How AI Reshapes Our Epistemic Environments, and How to Audit It

AI systems do more than operate within our epistemic environments. They actively reshape them by modifying what users treat as relevant evidence, how they come to know things, and even the standards by which they judge whether a system can be trusted. We argue that this reshaping is largely hidden from view, and we cal...

Alessandro Facchini · 0 citations
#explainable ai Oct 2026

DIGITAL INTELLIGENCE, ETHICAL AI GOVERNANCE, AND HUMAN INTELLIGENCE: A CONCEPTUAL FRAMEWORK FOR RESPONSIBLE DIGITAL TRANSFORMATION IN ASIAN COUNTRIES

Artificial intelligence (AI), big data analytics, and cloud computing are accelerating digital transformation by improving organizational efficiency, innovation, and data-driven decision-making across Asian economies. While these technologies create significant opportunities for economic and social development, they al...

Suman Kumar Dawn · 0 citations
#explainable ai Open access Oct 2026

RESEARCH ARCHITECTURE AND REPRODUCIBILITY GUIDE

Abstract This guide presents a practical framework for navigating, evaluating, and extending the Citizen Auditing — Open Methodology, Evidence & Digital Systems Research collection. The collection brings together methodological protocols, datasets, technical specifications, presentations, institutional communication re...

Erkan Yazargan · 0 citations
#explainable ai Oct 2026

The Ownership Cost of AI Goal-Setting: Empirical Evidence for a Quality-Motivation Dissociation and Differential Harm to Vulnerable Users (Extended Abstract)

AI systems are now deployed at scale to author personal goals on users' behalf in coaching platforms and productivity tools, a practice justified by the assumption that better-structured outputs produce better outcomes. We provide a preregistered experimental test of this assumption in personal goal-setting, a domain w...

Vivienne Bihe Chi, Roman Rietsche, Andreas Göldi et al. · 0 citations
#explainable ai Open access Oct 2026

THE BETTER FORGERY: Fidelity of Form, Responsive Verification, and When Skill Makes Deception More Harmful

Abstract Most people assume that skill and value travel together: a better copy is a better thing. For forgeries the relation runs the other way. A clumsy forger is caught within a season, and the loss is one picture. Van Meegeren’s forgeries were bought by museums, entered the catalogues and shaped the scholarship on...

José Caetano de Mattos · 0 citations
#explainable ai Open access Oct 2026

Enterprise AI Prompt Screening System

Abstract: Generative Artificial Intelligence (AI) tools are currently being widely used in business environments, but the prompts employed are unstructured text that can include personal data, financial information, credentials, or confidential information about an organization. There is also a risk involved in prompt...

Abhay Gaidhani, Prathmesh Ahire, Pooja Gamane et al. · 0 citations
#explainable ai Open access Oct 2026

Spec 027 — Movement, Culture, and Language in the Greater Indus World: Frozen Design and Pre-Analysis Plan (owner-adjudicated freeze, 2026-10-11)

Frozen study design, owner-adjudicated and frozen 2026-10-11 (repository: specs/027-movement-culture-language/, freeze commit 92711e9d; adjudication record adjudication.md in the same directory). An OSF Registration of this frozen design is filed from this component as its pre-analysis plan. Question: how do population...

Tristen Pierson · 0 citations
#explainable ai Oct 2026

Do We Need Computing Power Ethics? Participation Conditions in the AI Era

The ethics of computing power distribution is commonly treated as a question of price, infrastructure, environmental burden, security, or geopolitical inequality. The existing frameworks illuminate important aspects of computing power, with usually translating it into another object, such as a commodity, environmental...

Yunqi Jiang · 0 citations
#explainable ai Open access Oct 2026

Artificial Intelligence in the Social Media Strategies of UK Accounting Firms: An Evidence Synthesis and Protocol for a 21-Firm Mixed-Methods Study

Accounting firms in the United Kingdom are adopting artificial intelligence (AI) across audit, tax, reporting and advisory work, yet little is known about how they use AI in social media, particularly on LinkedIn, to generate content, analyse engagement, schedule posts, personalise messages and generate leads. This art...

Orjona Fjerza · 0 citations
#explainable ai Oct 2026

Impact of AI technology adoption on workload management: A pilot study with special references to private university lecturers in Colombo district

Artificial intelligence is becoming increasingly common in higher education, changing how academic staff handle teaching and administrative work. However, very few studies have examined its effect on instructors at private universities in the Colombo District, particularly the possibility that AI could add to their wor...

K.S. Nethmini, K.T.D. Jayathilake · 0 citations
#explainable ai Open access Oct 2026

Australian-Text-Analytics-Platform/ldaca-wordflow: Wordflow 0.7.12

Wordflow 0.7.12 makes Quotation Runs several times faster and shows quotations as they are found; makes AI annotation safer and cheaper, keeping labels if a run stops and sending each text only once; lets you name topics in Topic Modelling; adds Map values to the Data Editor; lets you move result table columns by dragg...

Alex Guo, Chao Sun · 0 citations

From tech blogs

See all →
MIT News · Artificial Intelligence Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

Microsoft Research Blog Oct 22, 2026

Flint-interactive: A language for creating interactive data visualizations

Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.