Call for Papers

We invite submissions on any aspect of trustworthy and socially responsible machine learning, which includes but not limited to:

• Novel methods for building more trustworthy machine learning models that prevent or alleviate negative societal impacts of existing machine learning methods
• New applications and settings where trustworthiness of machine learning plays an important role and how well existing techniques work under these settings
• New connections and mutual interactions between various aspects and properties of trustworthy and socially responsible ML: security, robustness, privacy, fairness, ethics, interpretability, transparency, etc.
• Futuristic concerns on trustworthiness and societal impact of existing machine learning systems
• Machine learning models with verifiable guarantees (such as robustness, fairness and privacy guarantees) to build trustworthiness
• Privacy-preserving machine learning approaches
• Theoretical understanding of trustworthy machine learning
• Explainable and interpretable AI
• Robust decision making under uncertainty
• Futuristic concerns about trustworthy machine learning
• Game-theoretic analysis for socially responsible machine learning systems
• Case studies and field research of the societal impacts of applying machine learning in mission-critical and human-centric tasks

Reviewing will be performed in double-blind, with criteria include:

• Quality of the methodology and experiments
• Novelty
• Relevance
• Societal impacts

Important Dates

Abstract and Full Paper Submission	October 3 October 5, 2022, 11:59 PM, Anywhere on Earth (AoE)     Extended!
Notification	October 20 October 23, 2022, AoE
Camera Ready and Video Submission	November 3November 10, 2022, AoE

Author Instructions

Papers should be submitted to OpenReview: https://openreview.net/group?id=NeurIPS.cc/2022/Workshop/TSRML

Submission Format

Submitted papers are recommended to have at most 6 pages with unlimited bibliography and appendix, using TSRML 2022 LaTex style files:

• tsrml_2022.tex - LaTeX template
• tsrml_2022.sty - style file for LaTeX 2e
• tsrml_2022.pdf - example PDF output generated by running "pdflatex"

The page limit is not hard, but keeping your paper reasonably short and concise can greatly improve readability. Submissions must be anonymous following NeurIPS double-blind reviewing guidelines and NeurIPS Code of Conduct. Accepted papers will be hosted on this workshop website but are considered non-archival and can be submitted to other workshops, conferences or journals if their submission policy allows.

Dual submission policy

We allow dual submission with other workshops or conferences. You can also submit papers that have some overlaps with your recently published papers. However, we disallow papers that are presented at the NeurIPS main conference as well as other machine learning conferences.