PROBLEM AND SOLUTION DOCUMENTATION TEMPLATE FOR MACHINE LEARNING COMPETITIONS TO ENHANCE EXPLAINABILITY, REPRODUCIBILITY, AND COLLABORATION BETWEEN STAKEHOLDERS
Oluwaseun Hamzat
2021 Poster Presentation
in
Workshop: 2nd Workshop on Practical ML for Developing Countries: Learning Under Limited/low Resource Scenarios
in
Workshop: 2nd Workshop on Practical ML for Developing Countries: Learning Under Limited/low Resource Scenarios
Abstract
Democratizing access to Artificial Intelligence and truly utilizing it for the common
good requires multi-stakeholder AI competitions focused on real and prevalent
problems with the potential for large scale impact and that promotes and
ensures the explainability, reproducibility, contextualization and incremental enhancements of solutions. We propose a solution documentation and problem documentation template for AI/Machine Learning competitions that ensures the identification and systematic characterization of prevalent problems and the documentation of developed solutions in such a way that they can be easily utilized by anyone anywhere.
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