Future of Workplace

 

Art & Education, Theories of Technology and the Production of Value from Everyday Life (Presenting lectures by Bernard Stiegler, David Harvey, Tiziana Terranova, Jonathan Beller and Christian Fuchs, Andrew McKinney’s contribution to Classroom concerns the relationship between technology, human labor, and everyday life in late capitalism)

AI Now Institute, Discriminating Systems: Gender, Race, and Power in AI, 2019

Barclays, Robots at the Gate, 2018

 

Bertrand, Marianne and Sendhil Mullainathan, "Are Emily And Greg More Employable Than Lakisha And Jamal? A Field Experiment On Labor Market Discrimination," American Economic Review, 2004, v94(4,Sep), 991-1013

B. Green, “Fair” risk assessments: A precarious approach for criminal justice reform, in: 5thWorkshop on Fairness, Accountability, and Transparency in Machine Learning, 2018

Brookings Institute, Automation and Artificial Intelligence: How machines are affecting people and places, 2019

Brynjolfsson, Erik and Tom Mitchell, "What Can Machine Learning Do? Workforce Implications." Science

Brynjolfsson, Erik, Daniel Rock and Chad Syverson, "Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics." NBER Working Paper No. 24001

Capgemini, Upskilling your people for the age of the machine

Capgemini, Why addressing ethical questions in AI will benefit organizations

Daron Acemoglu & Pascual Restrepo, 2018, "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, vol 108(6)

Data & Society Research Institute, Networked Employment Discrimination, 2014

Data & Society Research Institute, Understanding Fair Labor Practices in a Networked Age, 2014

Deloitte, Oracle, AI @ Work Report: Artificial Intelligence Is Winning More Hearts & Minds in the Workplace

Deloitte, AI-augmented Human Services, 2017

Economics of AI Conference 2017, Presentations and Working Papers

Ernst & Young, The new age: artificial intelligence for human resource opportunities and functions

Frank, Morgan, David Autor, James. E. Bessen, Erik Brynjolfsson, Manuel Cebrian, David J. Deming, Maryann Feldman et al, "Toward Understanding the Impact of Artificial Intelligence on Labor." Proceedings of the National Academy of Sciences

Frey, Carl Benedikt and Osborne, Michael A.: The Future of Employment: How Susceptible are Jobs to Computerisation?, 2013

Grace Lordan & David Neumark, "People Versus Machines: The Impact of Minimum Wages on Automatable Jobs," Labour Economics

 

Hannak, Aniko; Wagner, Claudia; Garcia, David; Mislove, Alan; Strohmaier, Markus; Wilson, Christo. Bias in Online Freelance Marketplaces: Evidence from Taskrabbit and Twitter. (CSCW’17)

HR Examiner, Navigating the Maze: The 2019 Index of Intelligent Technology in HR

IEC Market Strategy Board (MSB), Haier Group & German Research Centre for Artificial Intelligence (DFKI), Artificial Intelligence Across Industries, 2019
IEC, Factory of the Future

International Bar Association, Artificial Intelligence and Robotics and Their Impact on the Workplace, 2017

International Labor Organization, ASEAN in Transformation: The Future of Jobs at Risk of Automation, 2016

Jia Q., Guo Y., Li R., Li Y.R., & Chen Y.W. (2018), A conceptual artificial intelligence application framework in human resource management. In Proceedings of The 18th International Conference on Electronic Business

Joh, E. E. & White, W. B. (2018), How we can apply AI, and deep learning to our HR functional transformation and core talent processes? Cornell University, ILR School site

Kim, Pauline, Data-Driven Discrimination at Work (April 19, 2017). William & Mary Law Review, Vol. 48, pp. 857-936 (2017); Washington University in St. Louis Legal Studies Research Paper No. 16-12-01

KPMG, An Ethical Compass in the Automation Age, 2017

LinkedIn, AI Talent in the European Labour Market, 2019

Loi, Michele. "People Analytics must benefit the people. An ethical analysis of data-driven algorithmic systems in human resources management", (2020)

Manish Raghavan, Solon Barocas, Jon Kleinberg, Karen Levy,  Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices, 2019

McKinsey Company, A government blueprint to adapt the ecosystem to the future of work, 2020

McKinsey Company, The future of women at work: Transitions in the age of automation, 2019

McKinsey Company, A Future that Works: Automation, Employment and Productivity, 2017

McKinsey Company, Where machines could replace humans—and where they can’t (yet), 2016

Microsoft, Maximising the AI Opportunity, 2019

Microsoft, The Future Computed – AI and its role in society, 2018

MIT Technology Review, Every study we could find on what automation will do to jobs, in one chart (Erin Winick), 2018

OECD, The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis, 2016

Oracle, AI-augmented Human Services

PWC, 2018 AI Predictions 8 Insights to Shape Business Strategy

Upturn: Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias, 2018

​Webb, Michael, The Impact of Artificial Intelligence on the Labor Market, 2019

White House, Artificial Intelligence, Automation, and the Economy, 2016

World Economic Forum’s System Initiative on Shaping the Future of Education, Gender and Work, in collaboration with The Boston Consulting Group and using proprietary data provided exclusively for this report by Burning Glass Technologies, "Towards a Reskilling Revolution: A Future of Jobs for All"

World Economic Forum, Artificial intelligence will save jobs, not destroy them. Here's how

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