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What is Heteromation

Encyclopedia of Data Science and Machine Learning
Machines compensating for human effort.
Published in Chapter:
Data Science for Industry 4.0
Indraneel Dabhade (O Automation, India)
Copyright: © 2023 |Pages: 14
DOI: 10.4018/978-1-7998-9220-5.ch004
Abstract
Proliferation of smart devices coupled with advances in computing technologies has aided smart decision-making. Though the term data science is of recent origin, the field utilizes cornerstone computing and statistical concepts to solve data-specific challenges. The role of a data scientist is to extract maximum information from raw data. This role has spawned across disciplines but only acts as a supplemental measure to actual domain knowledge. The field of data science encompasses analytics, artificial intelligence, and statistical modeling. Information security has not always been integral to the data science ecosystem. An increasingly connected world with heightened reliance on data has encouraged data scientists to be well-versed with data security. This article takes an overview of the commercial application using data science, machine learning, and big data.
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Automation and Augmentation: Human Labor as Essential Complement to Machines
Created by cognitive scientist Bonnie Nardi. The term identifies human labor in automated work that is hidden and uncompensated.
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How and Why Is Work Meaningful (Beyond Survival Needs)?: Setting a Baseline
The importance of human labor in technological “automation” systems (Ekbia, Nardi, & Šabanovic, 2015, p. 1).
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