First DAI-DSS Research Collection – D3.2
Lucas Paletta, Herwig Zeiner, Michael Schneeberger, Julia Tschuden, Martin Pszeida, Andreas A. Mosbacher, Gustavo Vieira, Sylwia Olbrych, Alexander Nasuta, Johanna Werz, Noushin Gheibi, Stefan Böschen, Magdalena Dienstl, Marlene Mayer, Christian Muck
This report focuses on deliverable “First DAI-DSS Research Collection”, which is part of the Horizon Europe project FAIRWork. The deliverable aims to describe a first iteration on guidelines, methods and tools for democratising the production process in the light of their flexibilisation while using Artificial Intelligence, Optimisation, Human Factors Analytics, and Multi Agent Systems (MAS) as mediators in form of prototypes, physical experiments in laboratories, implemented questionnaires, modelling tools or semantic model of criteria catalogues. It presents a collection of concepts, methods, studies, and services of a research framework within the Democratised AI Decision Support System (DAI-DSS). The DAI-DSS research collection is based on the fundamental principles related to the research intended within the frame of this project that was described in Deliverable “D3.1 DAI-DSS Research Specification” and incorporates cross-connections with Deliverable “D4.1.1 DAI-DSS Architecture and initial Documentation and Test Report“ on the basis of functional components of the DAI-DSS system architecture.
The first part of the report provides an overview of the individual research tracks related to the various research strategies that incrementally shape and extend the research collection within the frame of this project and in the context of the scientific as well as industrial communities. It covers the most significant research domains such as democratisation of decision-making as well as digital shadows for resilience risk stratification or human experts. Additionally, it explores technical approaches like Artificial Intelligence (AI) and MAS crucial for improving Decision Support Systems (DSS). This section also presents the state-of-the-art in key aspects of today's technology, particularly reliability and trustworthiness in AI. The output of this research overview leads to the outline of research activities in multiple domains that will be addressed within the FAIRWork project.
The second part of the report focuses on the research collection in terms of the concrete research methods and services employed to investigate the technical aspects of decision-making processes, human aspects in the process, and digital Human Factors measurements. It presents research approaches for the successful implementation of AI and MAS-based technologies into DSS. Methods such as data-driven modelling, prototyping, and testing are proposed within the AI and MAS domains. Additionally, the report outlines the use of wearable sensors to capture critical information about the physiological, cognitive-emotional, and resilience state of humans, including implementation details of the Intelligent Sensor Box (ISB). Furthermore, the novel framework using Personas as Human Digital Twins for Decision Making in the context of Industry 5.0 is described in detail.
The third part covers initial observations on explainability and fairness in FAIRWork from an algorithmic point of view and summarises some reviews and surveys in the field.
The report also provides results of the strategy for scientific dissemination in the context of the research methodology of the FAIRWork project. The objective is to continuously disseminate project achievements, raise awareness about the project, and gather feedback to improve the created research artefacts.
The first part of the report provides an overview of the individual research tracks related to the various research strategies that incrementally shape and extend the research collection within the frame of this project and in the context of the scientific as well as industrial communities. It covers the most significant research domains such as democratisation of decision-making as well as digital shadows for resilience risk stratification or human experts. Additionally, it explores technical approaches like Artificial Intelligence (AI) and MAS crucial for improving Decision Support Systems (DSS). This section also presents the state-of-the-art in key aspects of today's technology, particularly reliability and trustworthiness in AI. The output of this research overview leads to the outline of research activities in multiple domains that will be addressed within the FAIRWork project.
The second part of the report focuses on the research collection in terms of the concrete research methods and services employed to investigate the technical aspects of decision-making processes, human aspects in the process, and digital Human Factors measurements. It presents research approaches for the successful implementation of AI and MAS-based technologies into DSS. Methods such as data-driven modelling, prototyping, and testing are proposed within the AI and MAS domains. Additionally, the report outlines the use of wearable sensors to capture critical information about the physiological, cognitive-emotional, and resilience state of humans, including implementation details of the Intelligent Sensor Box (ISB). Furthermore, the novel framework using Personas as Human Digital Twins for Decision Making in the context of Industry 5.0 is described in detail.
The third part covers initial observations on explainability and fairness in FAIRWork from an algorithmic point of view and summarises some reviews and surveys in the field.
The report also provides results of the strategy for scientific dissemination in the context of the research methodology of the FAIRWork project. The objective is to continuously disseminate project achievements, raise awareness about the project, and gather feedback to improve the created research artefacts.
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@techreport{fairwork_d3.2,
title = {First DAI-DSS Research Collection - D3.2},
author = {Lucas Paletta, Herwig Zeiner, Michael Schneeberger, Julia Tschuden, Martin Pszeida, Andreas A. Mosbacher, Gustavo Vieira, Sylwia Olbrych, Alexander Nasuta, Johanna Werz, Noushin Gheibi, Stefan Böschen, Magdalena Dienstl, Marlene Mayer, Christian Muck},
editor = {Lucas Paletta},
url = {https://fairwork-project.eu/deliverables/D3.2_First-DAI-DSS-ResearchCollection_V1.0_preliminary.pdf},
year = {2024},
date = {2024-04-30},
urldate = {2024-04-30},
abstract = {This report focuses on deliverable “First DAI-DSS Research Collection”, which is part of the Horizon Europe project FAIRWork. The deliverable aims to describe a first iteration on guidelines, methods and tools for democratising the production process in the light of their flexibilisation while using Artificial Intelligence, Optimisation, Human Factors Analytics, and Multi Agent Systems (MAS) as mediators in form of prototypes, physical experiments in laboratories, implemented questionnaires, modelling tools or semantic model of criteria catalogues. It presents a collection of concepts, methods, studies, and services of a research framework within the Democratised AI Decision Support System (DAI-DSS). The DAI-DSS research collection is based on the fundamental principles related to the research intended within the frame of this project that was described in Deliverable “D3.1 DAI-DSS Research Specification” and incorporates cross-connections with Deliverable “D4.1.1 DAI-DSS Architecture and initial Documentation and Test Report“ on the basis of functional components of the DAI-DSS system architecture.
The first part of the report provides an overview of the individual research tracks related to the various research strategies that incrementally shape and extend the research collection within the frame of this project and in the context of the scientific as well as industrial communities. It covers the most significant research domains such as democratisation of decision-making as well as digital shadows for resilience risk stratification or human experts. Additionally, it explores technical approaches like Artificial Intelligence (AI) and MAS crucial for improving Decision Support Systems (DSS). This section also presents the state-of-the-art in key aspects of today's technology, particularly reliability and trustworthiness in AI. The output of this research overview leads to the outline of research activities in multiple domains that will be addressed within the FAIRWork project.
The second part of the report focuses on the research collection in terms of the concrete research methods and services employed to investigate the technical aspects of decision-making processes, human aspects in the process, and digital Human Factors measurements. It presents research approaches for the successful implementation of AI and MAS-based technologies into DSS. Methods such as data-driven modelling, prototyping, and testing are proposed within the AI and MAS domains. Additionally, the report outlines the use of wearable sensors to capture critical information about the physiological, cognitive-emotional, and resilience state of humans, including implementation details of the Intelligent Sensor Box (ISB). Furthermore, the novel framework using Personas as Human Digital Twins for Decision Making in the context of Industry 5.0 is described in detail.
The third part covers initial observations on explainability and fairness in FAIRWork from an algorithmic point of view and summarises some reviews and surveys in the field.
The report also provides results of the strategy for scientific dissemination in the context of the research methodology of the FAIRWork project. The objective is to continuously disseminate project achievements, raise awareness about the project, and gather feedback to improve the created research artefacts.
},
howpublished = {https://fairwork-project.eu/deliverables/D3.2_First-DAI-DSS-ResearchCollection_V1.0_preliminary.pdf},
keywords = {deliverable},
pubstate = {published},
tppubtype = {techreport}
}