What is Impathy
Impathy is a research initiative exploring how algorithmic recommendation systems present different information to different individuals. By comparing parallel feeds across users, Impathy surfaces divergence, amplification, and informational asymmetry that is otherwise invisible to individual users.
Why this matters
Modern recommendation systems influence what people see, believe, and understand about the world. However, these systems are experienced individually and cannot be meaningfully observed from a single perspective. Impathy exists to make these differences observable.
Approach
Impathy captures and compares user-experienced exposure patterns across multiple perspectives on the same platforms over the same time period. The work focuses on comparative feed analysis, divergence patterns, and responsible presentation of findings.
Positioning
Impathy is not a social platform, ad product, or engagement tool. It is a research and transparency effort intended to support educators, researchers, journalists, and public interest organizations.
Current status
Research design and scope defined
Method instrumentation and research tooling development underway
Initial testing planned in controlled research contexts
Ethics and responsibility
Impathy is designed with privacy, consent, and non interference as core principles. No personal data is sold or shared. No user identities are published. Findings are presented in aggregate or anonymized form.