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A policy primer and roadmap on AI worker surveillance and productivity scoring tools
Algorithmic worker surveillance and productivity scoring tools powered by artificial intelligence (AI) are becoming prevalent and ubiquitous technologies in the workplace. These tools are applied across white and blue-collar jobs, and gig economy roles. In the absence of legal protections, and stron...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10026198/ https://www.ncbi.nlm.nih.gov/pubmed/37360144 http://dx.doi.org/10.1007/s43681-023-00275-8 |
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author | Hickok, Merve Maslej, Nestor |
author_facet | Hickok, Merve Maslej, Nestor |
author_sort | Hickok, Merve |
collection | PubMed |
description | Algorithmic worker surveillance and productivity scoring tools powered by artificial intelligence (AI) are becoming prevalent and ubiquitous technologies in the workplace. These tools are applied across white and blue-collar jobs, and gig economy roles. In the absence of legal protections, and strong collective action capabilities, workers are in an imbalanced power position to challenge the practices of employers using these tools. Use of such tools undermines human dignity and human rights. These tools are also built on fundamentally erroneous assumptions. The primer section of this paper provides stakeholders (policymakers, advocates, workers, and unions) with insights into assumptions embedded in workplace surveillance and scoring technologies, how employers use these systems which impact human rights. The roadmap section lays out actionable recommendations for policy and regulatory changes which can be enacted by federal agencies and labor unions. The paper uses major policy frameworks developed or supported by the United States as the foundation for policy recommendations. These are Universal Declaration of Human Rights, the Organisation for Economic Co-operation and Development (OECD) Principles for the Responsible Stewardship of Trustworthy AI (OECD AI Principles), Fair Information Practices (FIPs) and the White House Blueprint for an AI Bill of Rights. |
format | Online Article Text |
id | pubmed-10026198 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-100261982023-03-21 A policy primer and roadmap on AI worker surveillance and productivity scoring tools Hickok, Merve Maslej, Nestor AI Ethics Opinion Paper Algorithmic worker surveillance and productivity scoring tools powered by artificial intelligence (AI) are becoming prevalent and ubiquitous technologies in the workplace. These tools are applied across white and blue-collar jobs, and gig economy roles. In the absence of legal protections, and strong collective action capabilities, workers are in an imbalanced power position to challenge the practices of employers using these tools. Use of such tools undermines human dignity and human rights. These tools are also built on fundamentally erroneous assumptions. The primer section of this paper provides stakeholders (policymakers, advocates, workers, and unions) with insights into assumptions embedded in workplace surveillance and scoring technologies, how employers use these systems which impact human rights. The roadmap section lays out actionable recommendations for policy and regulatory changes which can be enacted by federal agencies and labor unions. The paper uses major policy frameworks developed or supported by the United States as the foundation for policy recommendations. These are Universal Declaration of Human Rights, the Organisation for Economic Co-operation and Development (OECD) Principles for the Responsible Stewardship of Trustworthy AI (OECD AI Principles), Fair Information Practices (FIPs) and the White House Blueprint for an AI Bill of Rights. Springer International Publishing 2023-03-20 /pmc/articles/PMC10026198/ /pubmed/37360144 http://dx.doi.org/10.1007/s43681-023-00275-8 Text en © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Opinion Paper Hickok, Merve Maslej, Nestor A policy primer and roadmap on AI worker surveillance and productivity scoring tools |
title | A policy primer and roadmap on AI worker surveillance and productivity scoring tools |
title_full | A policy primer and roadmap on AI worker surveillance and productivity scoring tools |
title_fullStr | A policy primer and roadmap on AI worker surveillance and productivity scoring tools |
title_full_unstemmed | A policy primer and roadmap on AI worker surveillance and productivity scoring tools |
title_short | A policy primer and roadmap on AI worker surveillance and productivity scoring tools |
title_sort | policy primer and roadmap on ai worker surveillance and productivity scoring tools |
topic | Opinion Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10026198/ https://www.ncbi.nlm.nih.gov/pubmed/37360144 http://dx.doi.org/10.1007/s43681-023-00275-8 |
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