Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Position: Build Agent Advocates, Not Platform Agents
Authors: Sayash Kapoor, Noam Kolt, Seth Lazar
ICML 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This position paper argues that we should promote agent advocates: user-controlled agents that safeguard individual autonomy and choice. Doing so demands three coordinated moves: broad public access to both compute and capable AI models that are not platform-owned, open interoperability and safety standards, and market regulation that prevents platforms from foreclosing competition. |
| Researcher Affiliation | Collaboration | Sayash Kapoor * 1 2 Noam Kolt * 3 Seth Lazar * 4 *Equal contribution 1Princeton University 2Mozilla 3Hebrew University 4Australian National University. Correspondence to: Sayash Kapoor <EMAIL>, Noam Kolt <EMAIL>, Seth Lazar <EMAIL>. |
| Pseudocode | No | The paper focuses on conceptual arguments, risks, and policy recommendations for AI agents and does not present any pseudocode or algorithm blocks. |
| Open Source Code | No | This paper is a position paper making conceptual arguments and proposing interventions; it does not describe a specific methodology for which source code would be released. |
| Open Datasets | No | This paper is a position paper and does not involve the use or analysis of specific datasets, thus it does not provide access information for open datasets. |
| Dataset Splits | No | This paper is a position paper and does not conduct experiments with datasets, therefore it does not provide information on dataset splits. |
| Hardware Specification | No | This paper does not describe experimental work that would require specific hardware, and therefore does not provide hardware specifications. |
| Software Dependencies | No | This paper is a position paper and does not implement a specific system or methodology, thus it does not list software dependencies with version numbers. |
| Experiment Setup | No | This paper is a position paper and does not present any experimental results, therefore it does not include details about an experimental setup. |