# A Collectivist, Economic Perspective on AI

arXiv: https://arxiv.org/abs/2507.06268 · HTML: https://mlsanity.com/paper/2507.06268/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 31 references that are in the map.
- First posted on arXiv 8 Jul 2025.

## Builds on (most cited first, 7 of 7)

- [A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification](https://mlsanity.com/paper/2107.07511/) (2021)
- [Performative Prediction](https://mlsanity.com/paper/2002.06673/) (2020)
- [Prediction-Powered Inference](https://mlsanity.com/paper/2301.09633/) (2023)
- [Hypothesis testing with e-values](https://mlsanity.com/paper/2410.23614/) (2024)
- [Large Language Models are overconfident and amplify human bias](https://mlsanity.com/paper/2505.02151/) (2025)
- [An Overview of Large Language Models for Statisticians](https://mlsanity.com/paper/2502.17814/) (2025)
- [A Survey On Secure Machine Learning](https://mlsanity.com/paper/2505.15124/) (2025)

## Built on by (most cited first, 4 of 4)

- [Decoding Alignment: A Critical Survey of LLM Development Initiatives through Value-setting and Data-centric Lens](https://mlsanity.com/paper/2508.16982/) (2025)
- [Crypto x AI, AI x Crypto: A Survey](https://mlsanity.com/paper/2606.13892/) (2026)
- [Generative Models Erode Human Temporal Learning Through Market Selection](https://mlsanity.com/paper/2606.06572/) (2026)
- [Multi-System Cognitive Steering for Generative Communication](https://mlsanity.com/paper/2610.19177/) (2026)

## Abstract (arXiv)

Information technology is in the midst of a revolution in which omnipresent data collection and machine learning are impacting the human world as never before. The word ``intelligence'' is being used as a North Star for the development of this technology, with human cognition viewed as a baseline. This view neglects the fact that humans are social animals and that much of our intelligence is social and cultural in origin. Moreover, failing to properly situate aspects of intelligence at the social level contributes to the treatment of the societal consequences of technology as an afterthought. The path forward is not merely more data and compute, and not merely more attention paid to cognitive or symbolic representations, but a thorough blending of economic and social concepts with computational and inferential concepts at the level of algorithm design.