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Table of Contents


Below is an overview of the current discussion topics within the Trusted AI Committee. Further updates will follow as the committee work develops. 

  • Focus of the committee is on policies, guidelines, tooling and use cases by industry

  • Survey and contact current open source Trusted AI related projects to join LF AI efforts 

  • Create a badging or certification process for open source projects that meet the Trusted AI policies/guidelines defined by LF AI

  • Create a document that describes the basic concepts and definitions in relation to Trusted AI and also aims to standardize the vocabulary/terminology

Mailing List

If you are interested in getting involved please email to be added to the mailing list. 

Current Participants

  • AT&T, Amdocs, Ericsson, IBM, Orange, TechM, Tencent


NameRegionOrganizationContact Info
Animesh Singh
North America
  • Souad Ouali : Europe (Orange)

  • Jeff Cao : Asia (Tencent)

    Working Group:



     Contact Info
    Ofer HermoniAmdocs 
     Mazin GilbertATT 
     Alka RoyATT 
    Mikael Anneroth 

    Jim Spohrer


    Maureen McElaney


    Susan Malaika

    Francois Jezequel 
    Nat SubramanianTech Mahindra

     Han Xiao Tencent

    Sub Categories

    - Fairness: Methods to detect and mitigate bias in datasets and models, including bias against known protected populations

    - Robustness: Methods to detect alterations/tampering with datasets and models, including alterations from known adversarial attacks

    - Explainability: Methods to enhance understandability/interpretability by persona/roles in process of AI model outcomes/decision recommendations, including ranking and debating results/decision options

    - Lineage: Methods to ensure provenance of datasets and AI models, including reproducibility of generated datasets and AI models


    If you are interested in getting involved please email for more information.