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2,878 papers
A self-referential retrosynthesis framework for explainable AI provenance forensics under a fixed-generator setting that leverages a jointly optimized encoder-decoder pair to implement a self-embedding mechanism that enables round-trip consistency verification.
This paper introduces contrastive explanations for Quantitative Bipolar Argumentation Frameworks (QBAFs), one such formalism, and introduces a general form of contrastive attribution functions (CAFs) and establishes a set of general properties they should satisfy.
The results identify user evaluability as a planning-relevant dimension of AI assistance, complementary to generation quality and preference inference, complementary to generation quality and preference inference.
Abstract Here is a very popular view on what user rational trust in AI requires: the Explanation View of AI Trust, whereby user rational trust in AI requires an explanation of why the AI has reached the conclusion it has. The authors of this chapter think that the Explanation View of AI Trust is wrong. It is not true o...
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Abstract: Digital transformation has emerged as an important strategy for financial institutions to enhance operational efficiency and enhance customer experience in the digital business environment. This study aims to examine the relationships of Electronic Customer Relationship Management (E-CRM), Artificial Intellig...
Abstract. As enterprise AI moves from answering questions to taking actions, the question of human oversight sharpens. Regulation for higher-risk uses requires that systems be overseen by people who can understand, intervene in and if necessary halt them. In deployed practice this duty is often satisfied by assertion:...
This chapter develops a human-centered, leadership-driven framework explaining how education contributes to sustainability in AI-augmented societies. It addresses three research questions on leadership as a driver of sustainability, its mechanisms of influence, and its role in employability, inclusion, and resilience....
Generative Artificial Intelligence (GenAI) is becoming an integral part of travel planning. This fundamental transformation is changing the definition of travel decision delegation, calling for fresh research into responsible AI in tourism. Drawing on agency theory, trust theory and decision delegation framework, this...
Abstract Current research on explainable and white-box artificial intelligence faces prominent issues: conceptual disarray, divergent perspectives, and a disconnect between theory and practice. The foremost priority is therefore to return to the field’s purest objectives and explore its most fundamental questions. To t...
Artificial intelligence is increasingly performing administrative, analytical, coordinating, monitoring, communication, and decision-support functions historically associated with managers and business administration. This transformation does not imply the disappearance of organizations, management, managers, or busine...
An assurance-specific framework answering three questions: for which sustainability-assurance procedures AI creates analytical value, which risks arise when AI influences assurance work, and which decision rights and controls should govern that influence is developed.
Artificial intelligence changes what organizations can do; human leadership must decide what should be done, what remains accountable, and what must never be surrendered to machines. This working paper presents FILE: The Five Intelligences of Leadership Evolution as a human-centered management theory and diagnostic fra...
AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…
Data Mining & Modeling
A Blog post by Dharma-AI on Hugging Face
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
GPT-Lab
· gpt-lab.eu
Nov 3, 2026
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
The MIT professors collaborated to identify the first AI-discovered antibiotic, a scientific breakthrough that is widely recognized as a milestone in AI-driven drug discovery.
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