Navigating AI Convergence in Human–Artificial Intelligence Teams @mpi-is
Navigating AI Convergence in Human–Artificial Intelligence Teams  @mpi-is
Uploaded February 2025 | Updated September 2026, 36 minutes ago
This study examines how the alignment of signals between AI and human teammates, along with the option to seek AI advice, impacts decision-making in human-AI teams in high-stakes contexts such as facial recognition or recruitment.

doi.org/10.1002/job.2856

The Wiley Journal for Organizational Behavior prepared a promotional video for this paper.

is.mpg.de/news
Navigating AI Convergence in Human–Artificial Intelligence TeamsMax Planck ETH Center for Learning Systems (CLS) - doctoral training at ETH ZurichMicrorobot collectives display versatile movement patternsKernel Methods Part II - Arthur Gretton - MLSS 2015 TübingenRobotic leg powered by HASELsRobot Learning - Stefan Schaal - MLSS 2017Acoustically driven microrobot outshines natural microswimmersDeep Reinforcement Learning Part 1 - Volodymyr Mnih - MLSS 2017Kernel Methods Part 3 - Bharath Sriperumbudur - MLSS 2017Optical Flow - Michael Black - MLSS 2013 TübingenProbabilistic Numerics I - Philipp Hennig - MLSS 2015 TübingenIMPRS-IS Application
Max Planck Institute for Intelligent Systems |

Navigating AI Convergence in Human–Artificial Intelligence Teams

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