MST Journal Special Issue

Peer Feedback Collection for Machine Learning Ethics

A clean, professional platform for Cambridge and Greater Boston researchers to share insights on the ethics, safety, and societal implications of machine learning systems

ABOUT THIS HUB

Designed for Local Scholars

This website serves as the primary peer review and feedback collection point for the MIT hosted Special Issue on Machine Learning Ethics. We are specifically inviting researchers, postdocs, postgraduates, nnd faculty from the Cambridge, Boston, and greater Boston area to share narrowed and constructive commentary on submitted papers.

LOCAL FOCUS
  • Mit Media Lab
  • Harvard CRCS | HIPS
  • MAT Computer Science
  • Boston University ALSIL
  • Complexity Research Group (CRG)
  • Brookings Institute
SUBMISSION PROCESS

Guidelines for Reviewers

Scope

Commentary should focus on ethical implications, baseline assumptions, bias, fairness, accountability, and societal impact of ML systems.

Format

Environ 2-3 paragraphs. Cite specific sections of the paper. Provide constructive, evidence-based feedback. Keep length under 600 words.

Confidentiality

Submissions are confidential to the special issue editorial team. Anonymous submissions are supported if you prefer.

Submit Your Feedback

Please fill out the form below. All fields marked * are required.

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