Shortlisting: a Principled Approach

2026-01-29

AI Summary

This study addresses the lack of systematic and principled approaches to shortlisting—a critical yet underexplored stage in decision-making—where efficient and fair preliminary selection from large candidate sets remains challenging. It formally establishes shortlisting as a distinct problem with its own intrinsic value, differentiating it from ranking or voting tasks. By integrating insights from social choice theory and multi-agent systems, the work develops a conceptual framework and theoretical model that yield principled mechanisms for fair and efficient shortlisting. This foundational contribution provides rigorous guidance for algorithm design and advances the application of shortlisting in contexts such as participatory democracy and recommendation systems, ultimately reducing cognitive load and enhancing the fairness and public trustworthiness of collective decisions.

Technology Category

• Machine Learning: Learning Preferences or Rankings
• Game Theory and Economic Paradigms: Social Choice / Voting
• Multiagent Systems: Mechanism Design

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

Shortlisting is the process of selecting a subset of alternatives from a larger pool for further consideration or final decision-making. It is widely applied in social choice and multi-agent system scenarios. The growing demand for participatory decision-making and the continuously expanding space of candidates create an urgent need for efficient and fair shortlisting procedures. However, little principled study has been done on this problem. This blue-sky paper aims to highlight the overlooked significance of shortlisting, distinguish it from related problems, provide initial thoughts, and, more importantly, serve as a call to arms. We envision that principled shortlisting can reduce cognitive burden, enable fair collective decisions, encourage broader participation, and ultimately build trust in democratic systems.

Problem

• shortlisting
• social choice
• multi-agent systems
• fairness
• participatory decision-making

Innovation

• shortlisting
• principled approach
• fair decision-making
• multi-agent systems
• social choice