The Future role of Big Data and machine learning in health and safety inspection efficiency

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<title>Future role of Big Data and machine learning in health and safety inspection efficiency</title>
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<namePart>Dahl, Øyvind</namePart>
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<namePart>Starren, Annick</namePart>
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<namePart>European Agency for Safety and Health at Work</namePart>
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<issuance>monographic</issuance>
<place>
<placeTerm type="text">Luxembourg</placeTerm>
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<publisher>Publications Office of the European Union</publisher>
<dateIssued>2019</dateIssued>
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<abstract displayLabel="Summary">Most labour inspectorates collect and store huge amounts of data related to their inspection objects and their inspection activities. Thus, inspectorates potentially possess large and rapidly growing volumes of data, nowadays referred to by the term big data'. Big data, combined with machine learning technology, is being used at an increasing rate for different predictive purposes, by learning from hidden trends in the data. For example, the predictive value of big data and machine learning techniques are being tested in areas as diverse as cancer prognosis and patient outcomes, bankruptcy prediction, oil price prediction, tax fraud detection, crime prediction and stock market forecasting. The fundamental question being addressed in this paper, however, is whether or not the use of big data and machine learning technology to target high-risk inspection objects is a promising avenue for labour inspectorates.</abstract>
<note type="statement of responsibility">Øyvind Dahl, Annick Starren</note>
<note>Resumen ejecutivo en español</note>
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<topic>Seguridad e higiene en el trabajo</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080627416">
<topic>Prevención de riesgos laborales</topic>
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<topic>Campañas de prevención</topic>
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<topic>Inspección de trabajo</topic>
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<topic>Big data</topic>
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<geographic>Europa</geographic>
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