Human Factors Guidance for the Integration of Artificial Intelligence and Machine Learning in FAA Systems

Smith, Philip J.; Roth, Emilie M.; Sarter, Nadine; Atkins, Ella; Evans, Mark; Bihari, Tom; Kim, Heejin

i

Human Factors Guidance for the Integration of Artificial Intelligence and Machine Learning in FAA Systems

2025-07-31
By Smith, Philip J. ; Roth, Emilie M. ; Sarter, Nadine ; ...

File Language:

English

Details

Creators:

Smith, Philip J. ; Roth, Emilie M. ; Sarter, Nadine ; Atkins, Ella ; Evans, Mark ; Bihari, Tom ; Kim, Heejin
Corporate Creators:

Ohio State University. Integrated Systems Engineering
Corporate Contributors:

United States. Federal Aviation Administration. NextGen Human Factors Division
Subject/TRT Terms:

Artificial Intelligence Automation Human-automation Interaction Human Factors Machine Learning
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

12/01/2022 – 9/01/2025
Corporate Publisher:

United States. Department of Transportation. Federal Aviation Administration
Abstract:

The goal of this project has been to develop a document providing guidance on the integration of artificial intelligence (AI)/machine learning (ML) technologies within information automation in FAA systems to support safety critical operations for air traffic control, traffic flow management and technical operations (maintenance). In this document such actions include the generation of alerts, support for fault diagnosis and recommendation of plans to resolve some conflict. The primary focus of this guidance document is on the design of decision support tools (DSTs). The intended audience includes human factors (HF) specialists, DST developers with expertise focused on AI/ML, as well as systems engineers and program managers who are participating in research, implementation and/or acquisition of FAA systems that incorporate AI/ML technologies within information automation.
Format:

PDF
Funding:

692M152340001
Collection(s):

Federal Aviation Administration
Main Document Checksum:

urn:sha-512:122ca12c113c0879349445c8b0c41260deff36790aafe40113b2410212456ba29adb6e2cbe245561300de7db1e421ab8eb4e22bae113aa3ae380a8651c75be3d
Download URL:

https://rosap.ntl.bts.gov/view/dot/86694/dot_86694_DS1.pdf
File Type:

[PDF - 2.59 MB ]

File Language:

English

ON THIS PAGE

Details

ROSA P serves as an archival repository of USDOT-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by USDOT or funded partners. As a repository, ROSA P retains documents in their original published format to ensure public access to scientific information.