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Writer's pictureBart Schrooten

News from Arcada's Laboratory for Trustworthy AI

Arcada's Laboratory for Trustworthy AI presents the latest news within the research community.


The latest updates from Arcada's Laboratory for Trustworthy AI presented according to date.


22 May 2024: Lessons Learned in Performing a Trustworthy AI and Fundamental Rights Assessment 


The Trustworthy AI Laboratory at Arcada participated in the Pilot Project for “Responsible use of AI” in collaboration with the Province of Fryslân, Rijks ICT Gilde in the Netherlands and the Z-Inspection® Initiative, and a report has has now been released.  The pilot project took place from May 2022 to January 2023. During the pilot, the practical application of a deep learning algorithm from the Dutch province of Frŷslan was assessed. The AI maps heathland grassland by means of satellite images for monitoring nature reserves. “This report is made public. The results of this pilot are of great importance for the Dutch government, serving as a best practice with which public administrators can get started, and incorporate ethical and human rights values when considering the use of an AI system and/or algorithms. It also sends a strong message to encourage public administrators to make the results of AI assessments like this one, transparent and available to the public.” (quoting from the report). 

The report "Lessons Learned in Performing a Trustworthy AI and Fundamental Rights Assessment" can be read via this link External link.


8 February 2024: New projects to further strengthen Arcada's Laboratory for Trustworthy AI

The three new projects are presented below:


DeployAI – Development and Deployment of the European AI-on-demand Platform


Time frame: January 1, 2024 - December 31, 2027

Funding organisation: EU Digita

lArcada lead: Magnus Westerlund


The primary goal of DeployAI is to build, deploy, and launch a fully operational AI-On-Demand platform (AIoDP) promoting trustworthy, ethical, and transparent European AI solutions for use in the industry, mainly for SMEs, and in the public sector. The development of the AIoDP will be based on the requirements of the Pre-PAI and the ongoing AI4Europe projects. DeployAI will provide a comprehensive and Trustworthy AI (TAI) resource catalogue and marketplace, which offers responsible AI resources, and tools, ensuring easy access for end-users (SMEs, public sector) and asset developers, and meeting industrial standard requirements. AIoDP will allow the rapid prototyping of TAI applications and their deployment to a variety of cloud/edge/HPC infrastructures. To lower the entry barrier of using AI and to offer advanced AI capabilities, responsible European LLMs will be integrated in the AIoDP to enable services for downstream tasks, fine-tuning and other complex GPAI workflows. The AIoDP will be embedded in the European AI ecosystem, especially to EDIHs, TEFs, Dataspaces, SIMPL, and HPC/Cloud/Edge infrastructure. Interfaces to European initiatives and industrial AI-capable cloud platforms will be implemented, including an open API, to enable interoperability. A significant number of TAI resources will be made available on the AIoDP which will be qualified and labelled by an established process. Further, DeployAI will establish a viable AIoDP engagement strategy for AI resource providers and AI users and stimulate the European AI innovation landscape with its FSTP programme. Active stakeholder engagement will be ensured by providing matchmaking services and an interactive landscape tool. Finally, the project will provide a sustainable business model and a viable long-term strategy for the AIoDP. Governance structures responsible for the AIoDP ongoing operations will be put in place, while a permanent legal entity to own and operate the future AIoDP will be established.



MANOLO: Trustworthy Efficient AI for Cloud-Edge Computing


Time frame: January 1, 2024 - December 31, 2026

Funding organisation: EU Horizon

Arcada lead: Magnus Westerlund


MANOLO will deliver a complete stack of trustworthy algorithms and tools to help AI systems reach better efficiency and seamless optimization in their operations, resources and data required to train, deploy and run high-quality and lighter AI models in both centralised and cloud-edge distributed environments. It will push the state of the art in the development of a collection of complementary algorithms for training, understanding, compressing and optimising machine learning models by advancing research in the areas of: model compression, meta-learning (few-shot learning), domain adaptation, frugal neural network search and growth and neuromorphic models. Novel dynamic algorithms for data/energy efficient and policy-compliance allocation of AI tasks to assets and resources in the cloud-edge continuum will be designed, allowing for trustworthy widespread deployment. To support these activities a data management framework for distributed tracking of assets and their provenance (data, models, algorithms) and a benchmark system to monitor, evaluate and compare new AI algorithms and model deployments will be developed. Trustworthiness evaluation mechanisms will be embedded at its core for explainability, robustness and security of models while using the Z-Inspection methodology for TrustworthyAI assessment, helping AI systems conform to the new AI Act regulation. MANOLO will be deployed as a toolset and tested in lab environments via Use Cases with different distributed AI paradigms within cloud-edge continuum settings; it will be validated in verticals such as health, manufacturing, and telecommunications aligned with ADRA identified market opportunities, and with a granular set of embedded devices covering robotics, smartphones, IoT as well as using Neuromorphic chips. MANOLO will integrate with ongoing projects at EU level developing the next operating system for cloud-edge continuum, while promoting its sustainability via the AI-on-demand platform and EU portals.



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