Explainable AI key to unlocking potential of automation for air traffic management

News Research and Innovation

innoveResearchers in the SESAR JU project, TAPAS, have completed a series of tests showing how applications built using explainable artificial intelligence can improve trust in humans operating automation-enhanced air traffic management systems. The algorithms will be now be adapted further to research AI-based automation support for in other ATM domains.

 

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