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HAIKU

financed

Human AI teaming Knowledge and Understanding for aviation safety

The aim of the HAIKU Project is to deliver prototypes of AI Digital Assistants for different aviation segments and users: commercial aviation pilots, urban air mobility and sky taxis, remotely piloted drones, remote towers, and ai... see more

31/08/2025

DEEP BLUE

8M€

Project Budget: 8M€

Project leader

DEEP BLUE SRL No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

PARTICIPATION DEPralty Sin fecha límite de participación.

Financing granted El organismo HORIZON EUROPE notifico la concesión del proyecto The day 2022-09-01

HORIZON-CL5-2021-D6-01-01: More powerful and reliable on-board... ExpectedOutcome:Project results are expected to contribute to all of the following expected outcomes...

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Project duration: 35 months Date Start: 2022-09-01
End date: 2025-08-31

Project leader

DEEP BLUE SRL No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Project Budget 8M€

participation deadline Sin fecha límite de participación.

Project description The aim of the HAIKU Project is to deliver prototypes of AI Digital Assistants for different aviation segments and users: commercial aviation pilots, urban air mobility and sky taxis, remotely piloted drones, remote towers, and air traffic controllers. It is essential both for safe operations, and for society in general, that the people who currently keep aviation so safe can work with, train and supervise these AI systems, and that future autonomous AI systems make judgements and decisions that would be acceptable to humans. HAIKU will pave the way for human-centric-AI by developing guidance and assurance procedures, and by exploring Human-AI Teaming via several interactive prototypes.Three main research questions will be addressed:•What is the recommended human-AI relationship for each of the different AI applications in aviation? •What does it mean for AI to be explainable and hence trustworthy in each of these applications? •How do we best teach AIs, via human-in-the-loop AI learning for each of the potential aviation applications? The following main outputs are foreseen:1.New Human Factors design guidance and methods (‘HF4AI’ Capabilities) on how to develop safe, effective and trustworthy Digital Assistants for Aviation2.A set of aviation use cases – controlled experiments with high operational relevance – illustrating the tasks, roles, autonomy and team performance of the Digital Assistant in a range of normal and emergency scenarios3.New safety and validation assurance methods for Digital Assistants, to facilitate early integration into aviation systems by aviation stakeholders and regulatory authorities 4.Continuous engagement with relevant stakeholders - e.g. policy makers, professional associations, passengers associations and general public – to deliver Guidance on socially acceptable AI in safety critical operations, and for maintaining aviation’s strong safety culture record.

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