Special Session on dAIEDGE: Trustworthy, Regulated, and Efficient AI on the Edge (TRUST-E)

Within the framework of the 22nd Conference on Distributed Computing and Artificial Intelligence (DCAI), which includes a range of interesting special sessions related to AI and emerging technologies, we are pleased to announce the Special Session on dAIEDGE: Trustworthy, Regulated, and Efficient AI on the Edge (TRUST-E).

This interdisciplinary session provides a unique platform to explore topics such as technical advancements in federated learning, cybersecurity, and efficient AI on the edge, as well as legal and ethical considerations like trustworthiness, explainability, and data protection. With a diverse program committee, this session guarantees a comprehensive discussion of the latest Edge AI developments.

• Scope

This Special Session focuses on advancing Artificial Intelligence at the edge by exploring theoretical, practical, and interdisciplinary perspectives. It will highlight recent progress, challenges, and innovations in Edge AI, including emerging software and hardware solutions, on-device learning, energy optimization, and communication strategies for resource-constrained devices.

Key topics include hybrid and distributed AI, energy-efficient architecture, and frameworks for Edge AI deployment. The session will also cover federated learning, privacy-preserving techniques, and the security of distributed edge  systems. This theme, along with other potentially related topics on the cybersecurity of edge AI, will be discussed.

Contributions discussing human rights, data protection, and other legal aspects of Artificial Intelligence at the edge, including interdisciplinary perspectives, are welcomed. Topics of interest include trustworthiness, non-discrimination and fairness, risk management, explainability, interpretability, human intervention, and more general data protection and security aspects.

• Topics

This Special Session provides a collaborative platform discussing Artificial Intelligence at the edge, encompassing diverse perspectives on this theme and other potentially related topics:

1. Edge AI scientific progress
2. Emerging SW/HW approaches for edge AI
3. Datasets and testbeds
4. On-device communication
5. Energy efficiency and optimization
6. Hybrid and distributed AI solutions
7. Edge AI on-demand framework
8. Distributed edge AI marketplace
9. Architectures for energy efficiency in distributed AI systems
10. Code generation, tuning, and deployment for Edge AI system
11. Generative edge AI
12. Trustworthy edge AI
13. Edge AI explainability and interpretability
14. Legal and ethical aspects of edge AI
15. Federated learning
16. Sustainable AI Systems for Economic and Social Impact
17. AI Innovations for Economic Growth and Resilience
18. Sustainable AI Solutions for Environmental Impact

Contributions containing both theoretical and practical results are welcomed.

We invite you to submit papers based on project results or other relevant research, and actively participate in order to maximize the visibility of dAIEDGE’s work and showcase the contributions of the Edge AI community. Publishing more about our progress is essential for advancing this field, as emphasized in our recent technical review.