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Timo Speith
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What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research
M Langer, D Oster, T Speith, H Hermanns, L Kästner, E Schmidt, A Sesing, ...
Artificial Intelligence, 2021
5742021
A review of taxonomies of explainable artificial intelligence (XAI) methods
T Speith
Proceedings of the 2022 ACM conference on fairness, accountability, and …, 2022
3262022
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions
L Longo, M Brcic, F Cabitza, J Choi, R Confalonieri, J Del Ser, R Guidotti, ...
Information Fusion 106, 102301, 2024
2062024
Explainability as a non-functional requirement
MA Köhl, K Baum, M Langer, D Oster, T Speith, D Bohlender
2019 IEEE 27th international requirements engineering conference (RE), 363-368, 2019
1462019
Exploring explainability: a definition, a model, and a knowledge catalogue
L Chazette, W Brunotte, T Speith
2021 IEEE 29th international requirements engineering conference (RE), 197-208, 2021
1402021
From Responsibility to Reason-Giving Explainable Artificial Intelligence
K Baum, S Mantel, E Schmidt, T Speith
Philosophy and Technology 35 (1), 1-30, 2022
802022
On the relation of trust and explainability: Why to engineer for trustworthiness
L Kästner, M Langer, V Lazar, A Schomäcker, T Speith, S Sterz
2021 IEEE 29th international requirements engineering conference workshops …, 2021
802021
Spare me the details: How the type of information about automated interviews influences applicant reactions
M Langer, K Baum, CJ König, V Hähne, D Oster, T Speith
International Journal of Selection and Assessment 29 (2), 154-169, 2021
582021
Explainability auditing for intelligent systems: a rationale for multi-disciplinary perspectives
M Langer, K Baum, K Hartmann, S Hessel, T Speith, J Wahl
2021 IEEE 29th international requirements engineering conference workshops …, 2021
372021
Quo vadis, explainability?–A research roadmap for explainability engineering
W Brunotte, L Chazette, V Klös, T Speith
international working conference on requirements engineering: foundation for …, 2022
302022
Revisiting the performance-explainability trade-off in explainable artificial intelligence (XAI)
B Crook, M Schlüter, T Speith
2023 IEEE 31st International Requirements Engineering Conference Workshops …, 2023
272023
Explainable software systems: from requirements analysis to system evaluation
L Chazette, W Brunotte, T Speith
Requirements Engineering 27 (4), 457-487, 2022
272022
From Machine Ethics to Machine Explainability and Back
K Baum, H Hermanns, T Speith
ISAIM, 2018
222018
Towards a framework combining machine ethics and machine explainability
K Baum, H Hermanns, T Speith
arXiv preprint arXiv:1901.00590, 2019
182019
A new perspective on evaluation methods for explainable artificial intelligence (XAI)
T Speith, M Langer
2023 IEEE 31st International Requirements Engineering Conference Workshops …, 2023
162023
How to Evaluate Explainability?–A Case for Three Criteria
T Speith
2022 IEEE 30th International Requirements Engineering Conference Workshops …, 2022
132022
Sources of opacity in computer systems: Towards a comprehensive taxonomy
S Mann, B Crook, L Kästner, A Schomäcker, T Speith
2023 IEEE 31st International Requirements Engineering Conference Workshops …, 2023
102023
Welcome to the first international workshop on requirements engineering for explainable systems (RE4ES)
W Brunotte, L Chazette, V Klos, E Knauss, T Speith, A Vogelsang
2021 IEEE 29th International Requirements Engineering Conference Workshops …, 2021
72021
Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle
L Deck, A Schomäcker, T Speith, J Schöffer, L Kästner, N Kühl
European Workshop on Algorithmic Fairness 2024, 2024
6*2024
Explainability as a Requirement for Hardware: Introducing Explainable Hardware (XHW)
T Speith, J Speith, S Becker, Y Zou, A Biega, C Paar
2024 IEEE 32nd International Requirements Engineering Conference (RE), 354-362, 2024
5*2024
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