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CLAIMED, a visual and scalable component library for Trusted AI

Romeo Kienzler
IBM, Center for Open Source Data and AI Technologies (CODAIT)

Ivan Nesic
University Hospital of Basel

Abstract

CLAIMED is a component library for artificial intelligence, machine learning, \textquotedbl{}extract, transform, load\textquotedbl{} processes and data science. The goal is to enable low-code/no-code rapid prototyping by providing ready-made components for various business domains, supporting various computer languages, working on various data flow editors and running on diverse execution engines. To demonstrate its utility, we constructed a workflow composed exclusively of CLAIMED components. For this purpose, we made use of a publicly available Computed Tomography (CT) scans dataset covidata and created a deep learning model, which is supposed to classify exams as either COVID-19 positive or negative. The pipeline was built with Elyra's Pipeline Visual Editor, with support for local, Airflow and Kubeflow execution.

Keywords

Kubernetes, Kubeflow, JupyterLab, Elyra, KFServing, TrustedAI, AI Explainability, AI Fairness, AI Adversarial Robustness

DOI

10.25080/majora-1b6fd038-007

Bibtex entry

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