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Completed PROJECT GRANT Swedish Research Council

EUREKA ITEA4 EXPLAIN - Explanatory Artificial Intelligence for Industry

166.82M kr SEK

Funder Vinnova
Recipient Organization Abb Ab
Country Sweden
Start Date May 02, 2022
End Date May 30, 2025
Duration 1,124 days
Number of Grantees 1
Roles Principal Investigator
Data Source Swedish Research Council
Grant ID 2021-04336_Vinnova
Grant Description

Purpose and goal:

The EXPLAIN (Explanatory Artificial Intelligence for Industry) project envisions an explanatory end-to-end ML workflow that accommodates and leverages the expertise of key stakeholders in the industrial ecosystem. To to do so, innovation is required at the algorithmic as well as on the Human-Automation Interaction (HAI) and User eXperience (UX) front.

EXPLAIN brings together partners with expertise in ML, UX, and industrial processes, to develop an ML lifecycle with aspects that combine algorithms, interfaces, tools, processes, and guidelines. Expected results and effects:

The project will deliver demonstrators that integrate ML models, explanatory algorithms, and novel interface concepts that enable an effective dialog between ML algorithms and domain experts. Guidelines, and best practices for how to effectively engage with domain experts, and end users will be disseminated to the wider community. This has the potential to increase the uptake of ML and AI solutions in industrial domains.

The project will also deliver academic publications and documentations of how the results can be appropriated in other industrial contexts. Approach and implementation:

The project brings together partners from 3 countries - Sweden, Germany, and Netherlands. The partners represent every aspect of the market value chain. The multidisciplinary consortium will explore a variety of industrial use cases to ensure generalizability of the results.

The execution of the project is divided into 3 innovation cycles. Each cycle delivers software prototypes and mock- ups that will undergo evaluations with users to help identify areas for improvement. The cumulative result is an end-to-end ML lifecycle that integrates domain experts, and end users.

All Grantees

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