Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities

Authors: Golnoosh Farnadi, Mohammad Havaei, Negar Rostamzadeh

ICML 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this position paper, we discuss that disparities towards marginalized communities performance, representation, privacy, robustness, interpretability and safety are not isolated concerns but rather interconnected elements of a cascading disparity phenomenon.
Researcher Affiliation Industry 1Google Research, Montreal, Canada. Correspondence to: Golnoosh Farnadi <gfarnadi@google.com>.
Pseudocode No The paper is a position paper and does not contain structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide concrete access to source code for any described methodology.
Open Datasets No The paper discusses concepts related to data but does not conduct experiments or provide concrete access information for a publicly available or open dataset used in its own research.
Dataset Splits No The paper does not conduct experiments and therefore does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce data partitioning.
Hardware Specification No The paper is a position paper and does not describe experiments, therefore no specific hardware details are provided.
Software Dependencies No The paper is a position paper and does not describe experiments, therefore no specific ancillary software details with version numbers are provided.
Experiment Setup No The paper is a position paper and does not describe experiments, therefore no specific experimental setup details (concrete hyperparameter values, training configurations, or system-level settings) are provided.