Copertina

Can AI Rely on the Systematicity of Truth? The Challenge of Modelling Normative Domains

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Queloz, Matthieu
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computers and Society
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Explainability Through Systematicity: The Hard Systematicity Challenge for Artificial Intelligence
di: Queloz, Matthieu
Pubblicazione: (2025)

Can Domain Experts Rely on AI Appropriately? A Case Study on AI-Assisted Prostate Cancer MRI Diagnosis
di: Chen, Chacha, et al.
Pubblicazione: (2025)

Pluralism in AI Governance: Toward Sociotechnical Alignment and Normative Coherence
di: Nkongolo, Mike Wa
Pubblicazione: (2026)

The Illusory Normativity of Rights-Based AI Regulation
di: Mei, Yiyang, et al.
Pubblicazione: (2025)

Artificial Intelligence Can Emulate Human Normative Judgments on Emotional Visual Scenes
di: Romeo, Zaira, et al.
Pubblicazione: (2025)

Relying on recent and temporally dispersed science predicts breakthrough inventions
di: Ke, Qing, et al.
Pubblicazione: (2021)

They Think AI Can Do More Than It Actually Can: Practices, Challenges, & Opportunities of AI-Supported Reporting In Local Journalism
di: Cifliku, Besjon, et al.
Pubblicazione: (2026)

Would You Rely on an Eerie Agent? A Systematic Review of the Impact of the Uncanny Valley Effect on Trust in Human-Agent Interaction
di: Alipour, Ahdiyeh, et al.
Pubblicazione: (2025)

Normative Moral Pluralism for AI: A Framework for Deliberation in Complex Moral Contexts
di: Yaacov, David-Doron
Pubblicazione: (2025)

ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness
di: Zhang, Yunfei, et al.
Pubblicazione: (2023)

Whose Truth? Pluralistic Geo-Alignment for (Agentic) AI
di: Janowicz, Krzysztof, et al.
Pubblicazione: (2025)

Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
di: Jain, Shomik, et al.
Pubblicazione: (2024)

Systematic Literature Review: Explainable AI Definitions and Challenges in Education
di: Altukhi, Zaid M., et al.
Pubblicazione: (2025)

Mechanistic Indicators of Understanding in Large Language Models
di: Beckmann, Pierre, et al.
Pubblicazione: (2025)

LEGOS-SLEEC: Tool for Formalizing and Analyzing Normative Requirements
di: Kolyakov, Kevin, et al.
Pubblicazione: (2025)

Normative Evaluation of Large Language Models with Everyday Moral Dilemmas
di: Sachdeva, Pratik S., et al.
Pubblicazione: (2025)

Normative active inference: A numerical proof of principle for a computational and economic legal analytic approach to AI governance
di: Constant, Axel, et al.
Pubblicazione: (2025)

From Trust to Truth: Actionable policies for the use of AI in fact-checking in Germany and Ukraine
di: Solopova, Veronika
Pubblicazione: (2025)

Modernizing Ground Truth: Four Shifts Toward Improving Reliability and Validity in AI in Education
di: Thomas, Danielle R., et al.
Pubblicazione: (2026)

Research Integrity and GenAI: A Systematic Analysis of Ethical Challenges Across Research Phases
di: Bjelobaba, Sonja, et al.
Pubblicazione: (2024)

Beyond Agreement: Rethinking Ground Truth in Educational AI Annotation
di: Thomas, Danielle R., et al.
Pubblicazione: (2025)

The ASIR Courage Model: A Phase-Dynamic Framework for Truth Transitions in Human and AI Systems
di: Kim, Hyo Jin
Pubblicazione: (2026)

Truth Knows No Language: Evaluating Truthfulness Beyond English
di: Figueras, Blanca Calvo, et al.
Pubblicazione: (2025)

Preserving Historical Truth: Detecting Historical Revisionism in Large Language Models
di: Ortu, Francesco, et al.
Pubblicazione: (2026)

Scaling Truth: The Confidence Paradox in AI Fact-Checking
di: Qazi, Ihsan A., et al.
Pubblicazione: (2025)

Can GenAI Move from Individual Use to Collaborative Work? Experiences, Challenges, and Opportunities of Coordinating GenAI into Collaborative Newswork
di: Xiao, Qing, et al.
Pubblicazione: (2025)

The Generative AI Paradox: GenAI and the Erosion of Trust, the Corrosion of Information Verification, and the Demise of Truth
di: Ferrara, Emilio
Pubblicazione: (2026)

DeliberationBench: A Normative Benchmark for the Influence of Large Language Models on Users' Views
di: Hewitt, Luke, et al.
Pubblicazione: (2026)

Epistemic Control and the Normativity of Machine Learning-Based Science
di: Ratti, Emanuele
Pubblicazione: (2026)

Dynamic Normativity: Necessary and Sufficient Conditions for Value Alignment
di: Corrêa, Nicholas Kluge
Pubblicazione: (2024)

Can AI be Consentful?
di: Pistilli, Giada, et al.
Pubblicazione: (2025)

Normativity and Productivism: Ableist Intelligence? A Degrowth Analysis of AI Sign Language Translation Tools for Deaf People
di: Seron-Abouelfadil, Nina, et al.
Pubblicazione: (2026)

Blocking Mechanism of Porn Website in India: Claim and Truth
di: Pandey, Saurabh, et al.
Pubblicazione: (2019)

Breaking Up with Normatively Monolithic Agency with GRACE: A Reason-Based Neuro-Symbolic Architecture for Safe and Ethical AI Alignment
di: Jahn, Felix, et al.
Pubblicazione: (2026)

AI Alignment vs. AI Ethical Treatment: 10 Challenges
di: Bradley, Adam, et al.
Pubblicazione: (2025)

Situated Ground Truths: Enhancing Bias-Aware AI by Situating Data Labels with SituAnnotate
di: Pandiani, Delfina Sol Martinez, et al.
Pubblicazione: (2024)

Aiming for AI Interoperability: Challenges and Opportunities
di: Faveri, Benjamin, et al.
Pubblicazione: (2026)

The Language of Trauma: Modeling Traumatic Event Descriptions Across Domains with Explainable AI
di: Schirmer, Miriam, et al.
Pubblicazione: (2024)

Can AI be Auditable?
di: Verma, Himanshu, et al.
Pubblicazione: (2025)

Truth Sleuth and Trend Bender: AI Agents to fact-check YouTube videos and influence opinions
di: Logé, Cécile, et al.
Pubblicazione: (2025)