AI4SC @ AAAI 2027
Third AAAI Bridge on Artificial Intelligence for Scholarly Communication
co-located with the 41st Annual AAAI Conference on Artificial Intelligence
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The rapid developments in AI have a profound impact on many aspects of scholarly research. The Third Bridge on Artificial Intelligence for Scholarly Communication (AI4SC) aims to bridge the gap between AI approaches and practical solutions for scholarly research. The two-day bridge program aims to discuss the potential that AI has to offer scholarly researchers, including opportunities for AI research assistants, comprehensive literature analysis, and the automated extraction and organization of scholarly knowledge. In addition, we also acknowledge the challenges and difficulties associated with AI for scholarly research, including a lack of AI literacy, publication overload, diminishing peer review, and pressing issues regarding knowledge sharing.
In our previous two editions of this Bridge, also hosted at AAAI, we organized a highly interactive bridge program, with plenty of room for presentations, discussions, and audience participation. In this year's edition, we welcome the following submissions: research papers, short/vision papers, posters/demos, and non-archival submissions. We especially encourage submissions of interactive sessions and tutorials. As developments in AI continue to advance rapidly, our Bridge is more relevant than ever, as individual scientists are at a pivotal point in discovering how AI can be effectively, responsibly, and meaningfully integrated into scholarly research and communication.
Contact us: ai4sc2027@easychair.org
Join our LinkedIn group to stay in touch! https://www.linkedin.com/groups/14997014/
AI4SC 2027 community on Zenodo: [TBD]
KEYNOTE SPEAKER
[TBD]
Topics and Research Questions
Topics and Research Questions
Topics of special relevance for the bridge include, but are not limited to:
Machine Actionable Science
Scientific knowledge extraction from publications, datasets, software, and other scholarly outputs
Scholarly knowledge graphs, ontologies, taxonomies, and semantic representation
Linking, integrating, and aligning scholarly knowledge across disciplines and information sources
Neuro-symbolic AI for scientific knowledge representation, integration, and reasoning
AI-Driven and Automated Scientific Research
Automated and AI-assisted scientific discovery, experimentation, and knowledge generation
AI co-scientists, autonomous research agents, and agentic systems supporting scientific workflows
AI-assisted hypothesis generation, research planning, experimental design, and data analysis
Multi-agent systems for collaborative scientific investigation and problem-solving
AI-assisted literature reviews, systematic reviews, and scientific evidence synthesis
AI-assisted scientific writing, editing, translation, and presentation
AI-supported peer review and research evaluation
Applications of AI across scientific disciplines
Human-AI Collaboration and Research Infrastructure
Human-AI collaboration and interactive scientific workflows
Researcher up-skilling, AI literacy, and the changing roles of researchers
FAIR principles, open research infrastructures, and machine-readable scientific resources
Interoperability and integration of AI tools into existing research environments
Collaborative platforms connecting researchers, AI systems, scholarly resources and research institutions
Interdisciplinary Applications and Impact of AI in Science
Applications of AI in the natural sciences, life sciences, medicine, engineering, social sciences, and humanities
AI for addressing Sustainable Development Goals
Cross-disciplinary knowledge discovery and integration through AI
Case studies demonstrating the adoption, benefits, limitations, and challenges of AI in different research domains
Scientific Alignment and Research Integrity
AI alignment with scientific values, objectives, and research practices
Trustworthy, explainable, transparent, and accountable AI for scientific applications
Hallucination detection, factual verification, and evidence-grounded scientific reasoning
Bias, fairness, uncertainty, and reliability in AI-assisted research
Research integrity, originality, authorship, attribution, and responsible AI use
AI governance, ethical frameworks, policies, and guidelines for scientific research
Human oversight, risk assessment, and safeguards for autonomous scientific system
AI4SC-2027_main.pdfBRIDGE COMMITTEES
Program Committee
[TBD]
Organizing Committee
in alphabetical order
Contact the committee: ai4sc2027@easychair.org
Anna Jacyszyn
Anna Jacyszyn
BRIDGE CHAIR
anna.jacyszyn@fiz-karlsruhe.de
Postdoctoral researcher at FIZ Karlsruhe - Leibniz Institute for Information Infrastructure, Eggenstein-Leopoldshafen, Germany; coordinator of the Leibniz Science Campus Digital Transformation of Research (DiTraRe)
Azanzi Jiomekong
Azanzi Jiomekong
fidel.jiomekong@facsciences-uy1.cm
Assistant Professor in Computer Science at the University of Yaounde I, Cameroon and Guest Researcher at TIB - Leibniz Information Centre for Science and Technology and University Library, Hannover, Germany
Keith G. Mills
Keith G. Mills
Louisiana State University, Baton Rouge, Louisiana, USA
Allard Oelen
Allard Oelen
Team Lead Frontend / User Interfaces for the Open Research Knowledge Graph (ORKG). Postdoctoral researcher TIB - Leibniz Information Center for Science and Technology, Hannover, Germany.
Steering Committee
Sören Auer
Sören Auer
Professor of Data Science and Digital Libraries at Leibniz Universität Hannover, Director of the TIB - Leibniz Information Center for Science and Technology, Hannover, Germany
Harald Sack
Harald Sack
Professor of Information Service Engineering at FIZ Karlsruhe - Leibniz Institute for Information Infrastructure, Eggenstein-Leopoldshafen, Germany; spokespoerson of the Leibniz Science Campus Digital Transformation of Research (DiTraRe)
We look forward to welcoming you to this year’s Bridge
We look forward to welcoming you to this year’s Bridge
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