Toward a political economy of synthetic data: A data-intensive capitalism that is not a surveillance capitalism?

Review Computer Science, Theory & Methods

A Systematic Review on Data Scarcity Problem in Deep Learning: Solution and Applications

Aayushi Bansal et al.

Summary: Recent advancements in deep learning architecture have made it more useful in real-life applications. However, training deep learning models requires a large amount of data, which may not be readily available in many domains. Data augmentation techniques can be used to address this problem by expanding the available dataset, improving model accuracy and generalization.

ACM COMPUTING SURVEYS (2022)

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Article Mathematics, Interdisciplinary Applications

Synthetic Data

Trivellore E. Raghunathan

Summary: Synthetic data sets are an attractive framework to provide widespread access to data for analysis while mitigating privacy and confidentiality concerns. This article aims to review various methods for generating and analyzing synthetic data sets, inferential justification, limitations of the approaches, and future research directions.

ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, VOL 8, 2021 (2021)

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Article Social Issues

Humanly Extended Automation or the Future of Work Seen through Amazon Patents

Alessandro Delfanti et al.

Summary: Amazon's patents reveal a future where workers are not completely replaced by machines, but instead machines increase surveillance and work rhythms for workers and incorporate their activities to rationalize the labor process in a more pervasive digital form. This reinforces Amazon's power in the digital workplace, enabling workers to act and sense on behalf of machinery.

SCIENCE TECHNOLOGY & HUMAN VALUES (2021)

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Article Health Care Sciences & Services