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ICAIL 2027: International Conference on Artificial Intelligence and Law

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ICAIL
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Día de Entrega:
2027-01-28 Faltan 121 días
Fecha de Notificación:
2027-04-19
Fecha de conferencia:
2027-07-05
Ubicación:
Vienna, Austria
Ediciones:
ICORE: C   Vistas: 1020   Seguidores: 0   Asistentes: 0

Índice Conference Partner (CP-I)

56,5 / 100
Puesto n.º 755 de 5.687 congresos · 14% superior

N.º 60 de 741 en Inteligencia artificial y aprendizaje automático

Reconocimiento académico (35%)
58
Selectividad en la revisión (20%) Sin datos: se puntúa con la línea base neutra de 50 —
Ediciones celebradas (20%)
84
Atención de la comunidad (10%)
10
Integridad del registro público (15%)
55

Datos utilizados: Categorías: ICORE C · Ediciones documentadas: 22 · Investigadores que abrieron esta página en los últimos 24 meses: 3

Falta en el registro público: Tasas de aceptación históricas (+4,5) · Premios al mejor artículo (+2,3)
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Solicitud de Artículos

ICAIL 2027 (International Conference on Artificial Intelligence and Law) is a ICORE C conference held in Vienna, Austria on 2027-07-05. The paper submission deadline is 2027-01-28. Acceptance notifications are sent on 2027-04-19.

Topics of interest include, but are not limited to, the following four groups. Foundations, knowledge representation and computational legal theory Logic and argumentation. Deontic and potestative logics, defeasible reasoning, argumentation frameworks, and models of normative conflict. Normative modelling. Formal or conceptual modelling of fundamental legal aspects, such as normative positions, causation, responsibility or legal qualification. Rule- and case-based reasoning. Formal and computational models of rule-based, case-based, evidential and value-based reasoning. Agent systems and norm emergence. Normative reasoning by autonomous agents, normative multi-agent systems, computational social science in law, and complex adaptive systems modelling of legal ecosystems. Neuro-symbolic integration. Approaches merging deep learning with symbolic legal knowledge representation and hybrid reasoning models, for example the autoformalisation of natural-language legal texts into computable logic or domain-specific languages. Ontologies and standards. Formal models of norms, legal ontologies, semantic web mark-up languages, open linked data, and legal data standards and interoperability schemas. Legal data science, information retrieval and generative AI Legal NLP. Precedent-aware named entity recognition, semantic role labelling, multilingual legal corpora, parsing of legal text, and information extraction from text. Information retrieval, search and network analysis. Legal information retrieval, semantic search, recommender systems, and structural network analysis of legal systems — statutory citation graphs, court precedent network topology, and topological data analysis of legal corpora. Argument mining. Argument mining on unstructured legal texts and automated information extraction from legal databases. Predictive analytics and other empirical methods. Predictive legal analytics, multi-modal legal data processing, and empirical machine learning methods applied to statutory and case law. Generative AI, evaluation and verification. LLM applications tailored for complex legal reasoning and synthesis, accompanied by rigorous evaluation pipelines, legal benchmarking, hallucination management and verification methods. Technical governance, legal risk analysis and normative alignment Regulatory compliance engineering. Formal and technical compliance-checking systems, logic-based verification, and runtime compliance for dynamic digital and AI regulatory environments, such as automated adherence to legal frameworks and end-to-end compliance architectures. Algorithmic fairness and bias. Bias assessment, fairness metrics, and non-discrimination design embedded in legal, judicial and administrative tools. Law-based AI safety, alignment and guardrails. Risk mitigation, model guardrails, norm-aware reinforcement learning, and law-following agent architectures designed to operate within legal constraints. Legal risk assessment and auditability. Automated legal risk assessment, exposure modelling, liability allocation, and explainable AI for judicial and administrative accountability and auditability. Accountability operationalisation. Operationalisation strategies for meaningful human control and other accountability frameworks, integrating normative systems, legal accountability and human oversight into high-stakes automated decisions. Legal technologies Hybrid intelligence workflows. Human-in-the-loop, human-on-the-loop and other legal workflow systems for judges, attorneys, legal practitioners and other relevant stakeholders. Access to justice and public interest technology. AI-driven access to justice tools, public interest legal technologies, and participatory data infrastructures. Rules as Code and e-government. Automation of the state, computational governance ("Rules as Code"), and e-justice and e-democracy platforms. Dispute resolution and negotiation. Computer-assisted and online dispute resolution, computational negotiation methods, and automated contract formation. Smart contracts and distributed ledgers. Formal, computational and jurisprudential challenges of smart contracts, DAOs and decentralised dispute resolution. Legal process, forensics and education. Legal process mining, digital forensics, evidence evaluation technology, and intelligent legal tutoring systems.
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