Negative Ontology of True Target for Machine Learning: Towards Evaluation and Learning under Democratic Supervision

• URL: http://arxiv.org/abs/2604.24824v1
• Date: Mon, 27 Apr 2026 15:01:26 GMT
• Title: Negative Ontology of True Target for Machine Learning: Towards Evaluation and Learning under Democratic Supervision
• Abstract summary: This article philosophically examines how shifts in assumptions regarding the existence and non-existence of the true target (TT) give rise to new perspectives and insights for machine learning (ML)-based predictive modeling.<n>We propose a knowledge system for evaluation and learning under Democratic Supervision.
• Score: 2.0885838435144963
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This article philosophically examines how shifts in assumptions regarding the existence and non-existence of the true target (TT) give rise to new perspectives and insights for machine learning (ML)-based predictive modeling and, correspondingly, proposes a knowledge system for evaluation and learning under Democratic Supervision. By systematically analysing the existence assumption of the TT in current mainstream ML paradigms, we explicitly adopt a negative ontology perspective, positing that the TT does not objectively exist in the real world, and, grounded in this non-existence assumption, define Democratic Supervision for ML. We further present Multiple Inaccurate True Targets (MIATTs) as an instance-level realization of Democratic Supervision. Building upon MIATTs, we derive principles, for the logic-driven generation and assessment of MIATTs, a logical assessment formulation for evaluation with MIATTs, and undefinable true target learning for learning with MIATTs. Based on these components, we establish the evaluation and learning with MIATTs (EL-MIATTs) framework for ML-based predictive modelling. A real-world application demonstrates the potential of the proposed EL-MIATTs framework in supporting education and professional development for individuals, aligning with prior discussions of Democratic Supervision in the fields of education and professional development.

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