PhilArchive
open access
Making Intelligence: Ethical Values in IQ and ML Benchmarks
The ML community recognizes the importance of anticipating and mitigating the potential negative impacts of benchmark research. In this position paper, we argue that more attention needs to be paid to areas of ethical risk that lie at the technical and scientific core of ML benchmarks. We identify overlooked structural similarities between human IQ and ML benchmarks. Human intelligence and ML benchmarks share similarities in setting standards for describing, evaluating and comparing performance on tasks relevant to intelligence. This enables us to unlock lessons from feminist philosophy of science scholarship that need to be considered by the ML benchmark community. Finally, we outline practical recommendations for benchmark research ethics and ethics review.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- ¿Cómo integrar la ética aplicada a la inteligencia artificial en el currículo? Análisis y recomendaciones desde el feminismo de la ciencia y de datos#697395
- Artificial Intelligence Tools for Scientific Work: Ethics, Responsibility, and Practical Applications#133015
- The human-authorship halo: attribution bias in literary style evaluation by humans and AI#972394
- The Role of Research Ethics Committees in Making Decisions About Risk#764149
- Falsifying Mary Wollstonecraft’s “Mind Has No Gender” Philosophy: A Scientific and Philosophical Rebuttal by Dr. Sinan Ibagüner#691800
Record · ID 108955
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive