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Requirements engineering for artificial intelligence systems: A systematic map** study
Context: In traditional software systems, Requirements Engineering (RE) activities are well-
established and researched. However, building Artificial Intelligence (AI) based software …
established and researched. However, building Artificial Intelligence (AI) based software …
Fairness testing: A comprehensive survey and analysis of trends
Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and
concern among software engineers. To tackle this issue, extensive research has been …
concern among software engineers. To tackle this issue, extensive research has been …
Exploring explainability: a definition, a model, and a knowledge catalogue
The growing complexity of software systems and the influence of software-supported
decisions in our society awoke the need for software that is transparent, accountable, and …
decisions in our society awoke the need for software that is transparent, accountable, and …
Perceived diversity in software engineering: a systematic literature review
We define perceived diversity as the diversity factors that individuals are born with.
Perceived diversity in Software Engineering has been recognized as a high-value team …
Perceived diversity in Software Engineering has been recognized as a high-value team …
Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and …
The increasing use of data-driven decision support systems in industry and governments is
accompanied by the discovery of a plethora of bias and unfairness issues in the outputs of …
accompanied by the discovery of a plethora of bias and unfairness issues in the outputs of …
[HTML][HTML] Requirements practices and gaps when engineering human-centered Artificial Intelligence systems
Abstract Context: Engineering Artificial Intelligence (AI) software is a relatively new area with
many challenges, unknowns, and limited proven best practices. Big companies such as …
many challenges, unknowns, and limited proven best practices. Big companies such as …
From AI ethics principles to data science practice: a reflection and a gap analysis based on recent frameworks and practical experience
In the field of AI ethics, after the introduction of ethical frameworks and the evaluation
thereof, we seem to have arrived at a third wave in which the operationalisation of ethics is …
thereof, we seem to have arrived at a third wave in which the operationalisation of ethics is …
[HTML][HTML] Requirements engineering framework for human-centered artificial intelligence software systems
Context: Artificial intelligence (AI) components used in building software solutions have
substantially increased in recent years. However, many of these solutions focus on technical …
substantially increased in recent years. However, many of these solutions focus on technical …
What's up with requirements engineering for artificial intelligence systems?
In traditional approaches to building software systems (that do not include an Artificial
Intelligent (AI) or Machine Learning (ML) component), Requirements Engineering (RE) …
Intelligent (AI) or Machine Learning (ML) component), Requirements Engineering (RE) …
Explainable software systems: from requirements analysis to system evaluation
The growing complexity of software systems and the influence of software-supported
decisions in our society sparked the need for software that is transparent, accountable, and …
decisions in our society sparked the need for software that is transparent, accountable, and …