Overview
Below is an overview of the current discussion topics within the LF AI Ethics 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
Current Participants
AT&T, Amdocs, Ericsson, IBM, Orange, TechM, Tencent
Chairs
@Animesh Singh - North America (IBM)
@OUALI Souad TGI/OLN - Europe (Orange)
@jeffcao(曹建峰) - Asia (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 reproducability of generated datasets and AI models
Working Group:
Name | Organization | |
---|---|---|
Jim Spohrer | IBM | |
Maureen McElaney | IBM | |
Susan Malaika | IBM | |
If you are interested in getting involved please email info@lfai.foundation for more information. Getting Involved