A review of trustworthy and explainable artificial intelligence (xai)
The advancement of Artificial Intelligence (AI) technology has accelerated the development
of several systems that are elicited from it. This boom has made the systems vulnerable to …
of several systems that are elicited from it. This boom has made the systems vulnerable to …
Sense–Assess–eXplain (SAX): Building trust in autonomous vehicles in challenging real-world driving scenarios
M Gadd, D De Martini, L Marchegiani… - 2020 IEEE Intelligent …, 2020 - ieeexplore.ieee.org
This paper discusses ongoing work in demonstrating research in mobile autonomy in
challenging driving scenarios. In our approach, we address fundamental technical issues to …
challenging driving scenarios. In our approach, we address fundamental technical issues to …
Your way or my way: improving human-robot co-navigation through robot intent and pedestrian prediction visualisations
As mobile robots enter shared urban spaces, operating in close proximity to people, this
raises new challenges in terms of how these robots communicate with passers-by. Following …
raises new challenges in terms of how these robots communicate with passers-by. Following …
Recent advances in Trustworthy and Explainable Artificial Intelligence: status, challenges, and perspectives
The advancement of Artificial Intelligence (AI) technology has accelerated the development
of several systems that are elicited from it. This boom had made the systems vulnerable to …
of several systems that are elicited from it. This boom had made the systems vulnerable to …
Exploring Evaluation Methodologies for Explainable AI: Guidelines for Objective and Subjective Assessment
S Tekkesinoglu - Available at SSRN 4667052, 2023 - papers.ssrn.com
This article explores the landscape of evaluation methodologies for Explainable Artificial
Intelligence (XAI), focusing on both objective and subjective assessment paradigms …
Intelligence (XAI), focusing on both objective and subjective assessment paradigms …
Context-based explanations for machine learning predictions
S Anjomshoae - 2022 - diva-portal.org
In recent years, growing concern regarding trust in algorithmic decision-making has drawn
attention to more transparent and interpretable models. Laws and regulations are moving …
attention to more transparent and interpretable models. Laws and regulations are moving …