Explainable Artificial Intelligence for human-AI collaboration

J.S. van der Waa

doi:10.4233/uuid:855bd55f-d297-4fff-9248-9cde0ad2b976

Explainable Artificial Intelligence for human-AI collaboration

J.S. van der Waa

Interactive Intelligence

Research output: Thesis › Dissertation (TU Delft)

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Abstract

As a society, we have come to notice the influence and impact Artificially Intelligent (AI) agents have on the way we live our lives. For these AI agents to support us both effectively and responsibly, we require an understanding on how they make decisions and what the consequences are of these decisions. The research _field of Explainable Artificial Intelligence (XAI) aims to develop AI agents that can explain its own functioning to provide this understanding. In this thesis we defined, developed, and evaluated a core set of explanations an AI agent can provide to support their collaboration with humans.

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	Delft University of Technology
Supervisors/Advisors	Neerincx, M.A., Supervisor Jonker, C.M., Supervisor van Diggelen, J., Supervisor, External person
Thesis sponsors	TNO
Award date	19 Oct 2022
Print ISBNs	978-94-6458-619-0
DOIs	https://doi.org/10.4233/uuid:855bd55f-d297-4fff-9248-9cde0ad2b976
Publication status	Published - 2022

Keywords

Artificial Intelligence
Explainable AI
Machine Learning
Human-AI collaboration
Explainable Artificial Intelligence

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10.4233/uuid:855bd55f-d297-4fff-9248-9cde0ad2b976

van der Waa (2022) - Explainable Artificial Intelligence for human-AI collaboration (dissertation)Final published version, 13.9 MBLicence: Unspecified

Cite this

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abstract = "As a society, we have come to notice the influence and impact Artificially Intelligent (AI) agents have on the way we live our lives. For these AI agents to support us both effectively and responsibly, we require an understanding on how they make decisions and what the consequences are of these decisions. The research _field of Explainable Artificial Intelligence (XAI) aims to develop AI agents that can explain its own functioning to provide this understanding. In this thesis we defined, developed, and evaluated a core set of explanations an AI agent can provide to support their collaboration with humans. ",

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KW - Explainable AI

KW - Machine Learning

KW - Human-AI collaboration

KW - Explainable Artificial Intelligence

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M3 - Dissertation (TU Delft)

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Explainable Artificial Intelligence for human-AI collaboration

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Keywords

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