TRR 318 - A dialog-based approach to explaining machine learning models (Subproject B01)

Overview

In Project B01, researchers are working on an artificial intelligence (AI) based system that can properly respond to questions at the level of language. In medicine, for example, the system should be able to explain a proposed treatment to a doctor and respond to patients’ questions and concerns regarding their treatment plan. The computer scientists and sociologists working on this project are including users’ perspectives in their research. For this, they are observing how, for instance, healthcare workers adopt this AI system and what requirements they have of the system. Based on these results, the researchers are developing a dialog system that can be used in a number of different areas of society.

Key Facts

Grant Number:
438445824
Project type:
Research
Project duration:
07/2021 - 06/2025
Funded by:
DFG
Website:
Homepage

More Information

Principal Investigators

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Prof. Dr. Axel-Cyrille Ngonga Ngomo

Data Science / Heinz Nixdorf Institute

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Philipp Cimiano

Universität Bielefeld

About the person (Orcid.org)
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Elena Esposito

Universität Bielefeld

Project Team

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M.Sc. Leonie Nora Sieger

Transregional Collaborative Research Centre 318

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Fabian Beer

Universität Bielefeld

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Dimitry Mindlin

Universität Bielefeld

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Cooperating Institutions

Universität Bielefeld

Cooperating Institution

Publications

Does Explainability Require Transparency?
E. Esposito, Sociologica 16 (2023) 17–27.
User Involvement in Training Smart Home Agents
L.N. Sieger, J. Hermann, A. Schomäcker, S. Heindorf, C. Meske, C.-C. Hey, A. Doğangün, in: International Conference on Human-Agent Interaction, ACM, 2022.
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