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AIS'' 2026: International Conference on Artificial Intelligence in Society

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AIS''
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截稿日期:
2026-05-08 Extended
通知日期:
2026-06-05
会议日期:
2026-07-25
会议地点:
Valencia, Spain
届数:
1
浏览: 2714   关注: 2   参加: 0

会伴指数 (CP-I)

38.9 / 100
全站第 5,331 名 / 共 5,682 个会议 · 前 94%

人工智能与机器学习 第 687 / 739

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
19
社区关注 (10%)
24
资料公开度 (15%)
35

用到的输入: 有据可查的届次：1 · 在会伴关注它的研究者：2 人 · 过去 24 个月打开过本页的研究者：5 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-17

征稿

AIS'' 2026 (International Conference on Artificial Intelligence in Society) is an academic conference held in Valencia, Spain on 2026-07-25. The paper submission deadline is 2026-05-08 (extended). Acceptance notifications are sent on 2026-06-05.

Although the term Artificial Intelligence (AI) was coined in the 1950´s, more recently, it has been at the centre of unprecedented attention. Developments in AI technology have created much interest from all areas of society, such as Education, Business and Health. The benefits of deploying AI are being reported transversally in all sectors. Nonetheless, AI’s potential evolves hand in hand with unyielding concerns that cause restraint and limit its widespread use. The International Conference on Artificial Intelligence in Society (AIS) aims to reunite both researchers and practitioners in addressing AI most pressing questions. The conference´s main areas and topics are identified bellow in a non-exhaustive list. 1. Core AI Research and Methodologies • Machine learning and deep learning advances • Natural language processing and multimodal AI • Reinforcement learning and autonomous systems • Explainable and interpretable AI • Human-in-the-loop and hybrid intelligence systems • Edge and distributed AI architectures • AI and Security • Chatbots and virtual assistants 2. AI in Education • Adaptive learning platforms and personalized education • AI for assessment and feedback automation • Educational data mining and learning analytics • Virtual tutors and AI-assisted teaching • Ethical implications of AI in learning environments • AI-enhanced learning technology 3. AI in Healthcare • AI for diagnostics, imaging, and predictive healthcare • Genomic data analysis and bioinformatics • AI in mental health and well-being applications • Medical data privacy and security • Human-AI collaboration in clinical decision-making • Data analytics in healthcare • Personal health assistants 4. AI in Business, Industry, and Economics • Predictive analytics and forecasting • Generative AI for productivity and automation • AI in finance, risk assessment, and fraud detection • Intelligent supply chains and logistics • AI-driven entrepreneurship and innovation ecosystems • Customer support and engagement • Data-driven decision making • AI-powered business analytics 5. AI Ethics and Legislation/Regulation • Trustworthy and responsible AI • Ethical AI policies and practices • Algorithmic bias and discrimination • Transparency and explainable AI • Legal frameworks and regulatory compliance • Privacy and data protection • Global AI governance and international standards • AI safety and human-in-the-loop systems • Intellectual property in AI-generated works 6. AI for the Progress of Society • Democratisation of technological development • Disaster response and humanitarian aid • Inclusive and accessible technology • Social justice and human rights monitoring • Misinformation and fake news prevention • Smart cities and urban planning • Democratic and active citizenship • Sustainability and environmental protection
由 Natalia Teixeira 最后更新于

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