Traceability for trustworthy AI: a review of models and tools
Traceability is considered a key requirement for trustworthy artificial intelligence (AI), related
to the need to maintain a complete account of the provenance of data, processes, and …
to the need to maintain a complete account of the provenance of data, processes, and …
A meta-summary of challenges in building products with ml components–collecting experiences from 4758+ practitioners
Incorporating machine learning (ML) components into software products raises new
software-engineering challenges and exacerbates existing ones. Many researchers have …
software-engineering challenges and exacerbates existing ones. Many researchers have …
[HTML][HTML] Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods
Over the last decade, the importance of machine learning increased dramatically in
business and marketing. However, when machine learning is used for decision-making, bias …
business and marketing. However, when machine learning is used for decision-making, bias …
Collaboration challenges in building ml-enabled systems: Communication, documentation, engineering, and process
The introduction of machine learning (ML) components in software projects has created the
need for software engineers to collaborate with data scientists and other specialists. While …
need for software engineers to collaborate with data scientists and other specialists. While …
An artificial intelligence life cycle: From conception to production
This paper presents the" CDAC AI life cycle," a comprehensive life cycle for the design,
development, and deployment of artificial intelligence (AI) systems and solutions. It …
development, and deployment of artificial intelligence (AI) systems and solutions. It …
A mixed approach for urban flood prediction using Machine Learning and GIS
Extreme weather conditions, as one of many effects of climate change, is expected to
increase the magnitude and frequency of environmental disasters. In parallel, urban centres …
increase the magnitude and frequency of environmental disasters. In parallel, urban centres …
AI lifecycle models need to be revised: An exploratory study in Fintech
Tech-leading organizations are embracing the forthcoming artificial intelligence revolution.
Intelligent systems are replacing and cooperating with traditional software components …
Intelligent systems are replacing and cooperating with traditional software components …
[HTML][HTML] A model of trust in Fintech and trust in Insurtech: How Artificial Intelligence and the context influence it
Finance and insurance are being transformed by Artificial Intelligence (AI). Nevertheless, the
consumer is not passive in this process and there is some inhibition to trust. This research …
consumer is not passive in this process and there is some inhibition to trust. This research …
A five-level framework for research on process mining
Process Mining is a novel technology that helps enterprises to better understand their
business processes. Over the last 20 years, intensive research has been conducted into …
business processes. Over the last 20 years, intensive research has been conducted into …
Construction of a quality model for machine learning systems
Nowadays, systems containing components based on machine learning (ML) methods are
becoming more widespread. In order to ensure the intended behavior of a software system …
becoming more widespread. In order to ensure the intended behavior of a software system …