Charles Alcock is managing editor of the AIN Media Group, having rejoined the company in 2019. He has been an aviation journalist since 1986, and previously worked for AIN from 1990 to 2017, most recently as editor-in-chief. His main focus is on covering new aviation technology and business models, as well as international news.
Having been raised in the London area, Alcock studied at the University of Manchester in the UK and earned an honors degree in Politics and Modern History. He speaks English and French, and some German.

Managing Editor

SAE International, the global industry association focused on establishing engineering standards in the mobility sector, this week published new guidance on how artificial intelligence (AI) technology can be safely and successfully adopted for aviation applications. The new AIR6988 Artificial Intelligence Systems: Statement of Concerns document has been jointly prepared by SAE’s G-34 committee and the WG-114 committee of the U.S.-based organization’s European counterpart Eurocae.
The document considers the degree to which current standards for aerospace software, hardware, and system development are compatible with typical development approaches involving the use of AI and machine learning (ML). The committees are aiming to review all existing standards, identifying gaps that need filling to ensure AI and ML standards are sufficiently reliable.
“AIR6988 marks the first step on our journey to develop safe and reliable standards for artificial intelligence and machine learning in the aviation domain,” said Mark Roboff, a G-34 committee member who is also CEO of a specialist company called SkyThread.aero. “Through consensus amongst many experts and practitioners in industry and academia, this critical document enables us to define what is necessary to demonstrate compliance for the certification of AI or machine learning in safety-critical airborne and ground-based systems.”
The <a href="https://www.sae.org/standards/content/air6988/">document includes</a> the following elements: a survey of established AI techniques and their application to various problem domains and development workflow; an assessment of current aerospace industry standards and guidelines and their applicability to systems that incorporate ML technologies; a use case proposal for potential AI applications for aerospace domains for airborne and ground-based systems; and a staged plan proposal for developing a future standard for AI techniques, processes and technologies to be assessed in the context of aeronautical systems. 
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Charles Alcock

Daedalean is one of several specialist companies looking to apply artificial intelligence and machine learning technology to applications such as autonomous flight operations. (Image: Daedalean)

SAE and Eurocae Ask Whether Artificial Intelligence and Machine Learning Standards Are Fit For Aviation Purposes

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