# Knowledge Graphs and Machine Learning in biased C4I applications

arXiv: https://arxiv.org/abs/2106.09258 · HTML: https://mlsanity.com/paper/2106.09258/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 30 references that are in the map.
- First posted on arXiv 17 Jun 2021.

## Builds on (most cited first, 4 of 4)

- [A Comprehensive Survey on Graph Neural Networks](https://mlsanity.com/paper/1901.00596/) (2019)
- [Gated Graph Sequence Neural Networks](https://mlsanity.com/paper/1511.05493/) (2015)
- [A Review of Relational Machine Learning for Knowledge Graphs](https://mlsanity.com/paper/1503.00759/) (2015)
- [Deep Learning on Knowledge Graph for Recommender System: A Survey](https://mlsanity.com/paper/2004.00387/) (2020)

## Abstract (arXiv)

This paper introduces our position on the critical issue of bias that recently appeared in AI applications. Specifically, we discuss the combination of current technologies used in AI applications i.e., Machine Learning and Knowledge Graphs, and point to their involvement in (de)biased applications of the C4I domain. Although this is a wider problem that currently emerges from different application domains, bias appears more critical in C4I than in others due to its security-related nature. While proposing certain actions to be taken towards debiasing C4I applications, we acknowledge the immature aspect of this topic within the Knowledge Graph and Semantic Web communities.