This paper sheds light on the role of digital platform labour in the development of today's
artificial intelligence, predicated on data-intensive machine learning algorithms. Focus is on …

This paper delves into the human factors in the “back-office” of artificial intelligence and of its
data-intensive algorithmic underpinnings. We show that the production of AI is a labor …

Artificial Intelligence-as-a-Service (AIaaS) empowers individuals and organisations to
access AI on-demand, in either tailored or 'off-the-shelf'forms. However, institutional …

Around the world, myriad workers perform micro-tasks on online platforms to train and
calibrate artificial intelligence solutions. Despite its apparent openness to anyone with basic …

This article extends the economic-sociological concept of embeddedness to encompass not
only social networks of, for example, friendship or kinship ties, but also economic networks …

In this work, we for the first time present a method for detecting labeling errors in image
datasets with semantic segmentation, ie, pixel-wise class labels. Annotation acquisition for …

While automated driving is often advertised with better-than-human driving performance, this
chapter reviews that it is nearly impossible to provide direct statistical evidence on the …

Active learning strategies for 3D object detection in autonomous driving datasets may help
to address challenges of data imbalance, redundancy, and high-dimensional data. We …

'Micro-work'consists of fragmented data tasks that myriad providers execute on online
platforms. While crucial to the development of data-based technologies, this poorly visible …

Today's artificial intelligence, largely based on data-intensive machine learning algorithms,
relies heavily on the digital labour of invisibilized and precarized humans-in-the-loop who …