Myth: AI can accurately predict and optimize human behavior
With technological advances in the field of AI and a growing amount of behavioral data that employees produce in their day-to-day routine, so-called people analytics tools have become a topic of public debate. These tools capture and analyze the behavioral data of employees, combine it with business data and offer employees and their manager’s insights into work routines, performance and potential. Based on this, people analytics promises to objectify and optimize employee-related decisions. Managers, therefore, place high expectations on these tools, especially with a growing number of employees who work from home and move outside their spatial control.
AI can accurately predict and optimize human behavior.
AI can indeed predict probabilities of human actions based on historical data. However, the accuracy of these predictions depends heavily on the data quality and is by no means error-free. As the behavior of humans in the workplace is complex and cannot always be quantified and measured, the current generation of AI can support people management in a limited area only and will certainly not make human managers obsolete.
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|UNICORN IN THE FIELD|
About the authors
Researcher, University of Hamburg / Associated Doctoral Researcher, Humboldt Institute for Internet & Society
Sonja is an associated doctoral researcher in the group Innovation, Entrepreneurship & Society at HIIG and researcher at the University of Hamburg. At HIIG, she currently supports the research project Artificial Intelligence & Knowledge Work, funded by the German Federal Ministry for Labour and Social Affairs. Her research focuses, among other things, on the digitalization of processes in human resource management and its impact on employees. In particular, she is interested in so-called people analytics applications. Prior to her role as a researcher, Sonja spent five years working as an HR practitioner in the field of HR information systems.
Researcher in the project “Anonymous Predictive People Analytics (AnyPPA)” at FZI Forschungszentrum Informatik, Berlin
Miriam is a research associate at the FZI Forschungszentrum Informatik Berlin/ Karlsruhe. She is currently supervising the BMBF-funded project Anonymous Predictive People Analytics. She focuses on the topic of the future of work and considers the social and ethical implications of the increasing use of AI in the workplace, as well as the development of co-determination and equal opportunities in the workplace.
This post represents the view of the author and does not necessarily represent the view of the institute itself. For more information about the topics of these articles and associated research projects, please contact email@example.com.
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