[HTML][HTML] Explainable AI for earth observation: A review including societal and regulatory perspectives
CM Gevaert - International Journal of Applied Earth Observation and …, 2022 - Elsevier
Artificial intelligence and machine learning are ubiquitous in the domain of Earth
Observation (EO) and Remote Sensing. Congruent to their success in the domain of …
Observation (EO) and Remote Sensing. Congruent to their success in the domain of …
ISO/IEC quality standards for AI engineering
Artificial Intelligence (AI) plays a crucial role in the digital transformation of organizations,
with the influence of AI applications expanding daily. Given this context, the development of …
with the influence of AI applications expanding daily. Given this context, the development of …
[HTML][HTML] Quod erat demonstrandum?-Towards a typology of the concept of explanation for the design of explainable AI
In this paper, we present a fundamental framework for defining different types of
explanations of AI systems and the criteria for evaluating their quality. Starting from a …
explanations of AI systems and the criteria for evaluating their quality. Starting from a …
The black box problem revisited. Real and imaginary challenges for automated legal decision making
This paper addresses the black-box problem in artificial intelligence (AI), and the related
problem of explainability of AI in the legal context. We argue, first, that the black box problem …
problem of explainability of AI in the legal context. We argue, first, that the black box problem …
Artificial intelligence in government: Concepts, standards, and a unified framework
Recent advances in artificial intelligence (AI), especially in generative language modelling,
hold the promise of transforming government. Given the advanced capabilities of new AI …
hold the promise of transforming government. Given the advanced capabilities of new AI …
Co-design of human-centered, explainable AI for clinical decision support
eXplainable AI (XAI) involves two intertwined but separate challenges: the development of
techniques to extract explanations from black-box AI models and the way such explanations …
techniques to extract explanations from black-box AI models and the way such explanations …
Explanatory artificial intelligence (YAI): human-centered explanations of explainable AI and complex data
In this paper we introduce a new class of software tools engaged in delivering successful
explanations of complex processes on top of basic Explainable AI (XAI) software systems …
explanations of complex processes on top of basic Explainable AI (XAI) software systems …
Bridging the Transparency Gap: What Can Explainable AI Learn From the AI Act?
Abstract The European Union has proposed the Artificial Intelligence Act which introduces
detailed requirements of transparency for AI systems. Many of these requirements can be …
detailed requirements of transparency for AI systems. Many of these requirements can be …
Quality models for artificial intelligence systems: characteristic-based approach, development and application
The factors complicating the specification of requirements for artificial intelligence systems
(AIS) and their verification for the AIS creation and modernization are analyzed. The …
(AIS) and their verification for the AIS creation and modernization are analyzed. The …
Opening the Analogical Portal to Explainability: Can Analogies Help Laypeople in AI-assisted Decision Making?
Abstract Concepts are an important construct in semantics, based on which humans
understand the world with various levels of abstraction. With the recent advances in …
understand the world with various levels of abstraction. With the recent advances in …