Trustworthy artificial intelligence: a review
Artificial intelligence (AI) and algorithmic decision making are having a profound impact on
our daily lives. These systems are vastly used in different high-stakes applications like …
our daily lives. These systems are vastly used in different high-stakes applications like …
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if
harnessed appropriately, may deliver the best of expectations over many application sectors …
harnessed appropriately, may deliver the best of expectations over many application sectors …
The ethics of algorithms: key problems and solutions
Research on the ethics of algorithms has grown substantially over the past decade.
Alongside the exponential development and application of machine learning algorithms …
Alongside the exponential development and application of machine learning algorithms …
Machine learning testing: Survey, landscapes and horizons
This paper provides a comprehensive survey of techniques for testing machine learning
systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing …
systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing …
Towards fairness in visual recognition: Effective strategies for bias mitigation
Computer vision models learn to perform a task by capturing relevant statistics from training
data. It has been shown that models learn spurious age, gender, and race correlations when …
data. It has been shown that models learn spurious age, gender, and race correlations when …
[PDF][PDF] A framework for understanding unintended consequences of machine learning
As machine learning increasingly affects people and society, it is important that we strive for
a comprehensive and unified understanding of how and why unwanted consequences …
a comprehensive and unified understanding of how and why unwanted consequences …
[HTML][HTML] A survey on bias in deep NLP
I Garrido-Muñoz, A Montejo-Ráez… - Applied Sciences, 2021 - mdpi.com
Deep neural networks are hegemonic approaches to many machine learning areas,
including natural language processing (NLP). Thanks to the availability of large corpora …
including natural language processing (NLP). Thanks to the availability of large corpora …
Using satellite imagery to understand and promote sustainable development
BACKGROUND Accurate and comprehensive measurements of a range of sustainable
development outcomes are fundamental inputs into both research and policy. For instance …
development outcomes are fundamental inputs into both research and policy. For instance …
Fairness perceptions of algorithmic decision-making: A systematic review of the empirical literature
Algorithmic decision-making increasingly shapes people's daily lives. Given that such
autonomous systems can cause severe harm to individuals and social groups, fairness …
autonomous systems can cause severe harm to individuals and social groups, fairness …
Fairness in deep learning: A computational perspective
Fairness in deep learning has attracted tremendous attention recently, as deep learning is
increasingly being used in high-stake decision making applications that affect individual …
increasingly being used in high-stake decision making applications that affect individual …