foo.castr: visualising the future AI workforce

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Title: foo.castr: visualising the future AI workforce
Authors: Molina-Solana, M
Kennedy, M
Amador Diaz Lopez, J
Item Type: Journal Article
Abstract: Organization of companies and their HR departments are becoming hugely affected by recent advancements in computational power and Artificial Intelligence, with this trend likely to dramatically rise in the next few years. This work presents foo.castr, a tool we are developing to visualise, communicate and facilitate the understanding of the impact of these advancements in the future of workforce. It builds upon the idea that particular tasks within job descriptions will be progressively taken by computers, forcing the shaping of human jobs. In its current version, foo.castr presents three different scenarios to help HR departments planning potential changes and disruptions brought by the adoption of Artificial Intelligence.
Issue Date: 31-Dec-2018
Date of Acceptance: 19-Sep-2018
ISSN: 2058-6345
Publisher: Springer Nature
Journal / Book Title: Big Data Analytics
Volume: 3
Issue: 1
Copyright Statement: © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.
Sponsor/Funder: KPMG LLP
Reuters Ltd
European Commission
Funder's Grant Number: KPMG Centre
GA 743623
Publication Status: Published
Article Number: 9
Online Publication Date: 2018-11-01
Appears in Collections:Faculty of Engineering
Imperial College Business School

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