# Artificial Intelligence for Collective Intelligence: A National-Scale Research Strategy

arXiv: https://arxiv.org/abs/2411.06211 · HTML: https://mlsanity.com/paper/2411.06211/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 104 references that are in the map.
- First posted on arXiv 9 Nov 2024.

## Builds on (most cited first, 17 of 17)

- [Carbon Emissions and Large Neural Network Training](https://mlsanity.com/paper/2104.10350/) (2021)
- [Gender bias and stereotypes in Large Language Models](https://mlsanity.com/paper/2308.14921/) (2023)
- [chatClimate: Grounding Conversational AI in Climate Science](https://mlsanity.com/paper/2304.05510/) (2023)
- [Trust in AI and Its Role in the Acceptance of AI Technologies](https://mlsanity.com/paper/2203.12687/) (2022)
- [A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings](https://mlsanity.com/paper/2106.09012/) (2021)
- [Real Risks of Fake Data: Synthetic Data, Diversity-Washing and Consent Circumvention](https://mlsanity.com/paper/2405.01820/) (2024)
- [Multi-relational Graph Diffusion Neural Network with Parallel Retention for Stock Trends Classification](https://mlsanity.com/paper/2401.05430/) (2024)
- [Macro Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions](https://mlsanity.com/paper/2208.12616/) (2022)
- [Fostering new Vertical and Horizontal IoT Applications with Intelligence Everywhere](https://mlsanity.com/paper/2310.00346/) (2023)
- [Understanding the Vulnerability of CLIP to Image Compression](https://mlsanity.com/paper/2311.14029/) (2023)
- [A Survey on Social-Physical Sensing: An Emerging Sensing Paradigm that Explores the Collective Intelligence of Humans and Machine](https://mlsanity.com/paper/2104.01360/) (2021)
- [Agent Heterogeneity Mediates Extremism in an Adaptive Social Network Model](https://mlsanity.com/paper/2305.10230/) (2023)
- [COVID-19 what have we learned? The rise of social machines and connected devices in pandemic management following the concepts of predictive, preventive and personalised medicine](https://mlsanity.com/paper/2009.05791/) (2020)
- [Collective decision-making under changing social environments among agents adapted to sparse connectivity](https://mlsanity.com/paper/2110.13543/) (2021)
- [Agent-Based Modelling for Urban Analytics: State of the Art and Challenges](https://mlsanity.com/paper/2210.06955/) (2022)
- [Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient Matching](https://mlsanity.com/paper/2210.13231/) (2022)
- [Understanding (Ir)rational Herding Online](https://mlsanity.com/paper/2306.15684/) (2023)

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

- [BondBERT: What we learn when assigning sentiment in the bond market](https://mlsanity.com/paper/2511.01869/) (2025)
- [We Are All Creators: Generative AI, Collective Knowledge, and the Path Towards Human-AI Synergy](https://mlsanity.com/paper/2504.07936/) (2025)
- [Enhancing Regime Shift Detection Using Unstructured Data: A Study on the Treasury Market](https://mlsanity.com/paper/2605.30363/) (2026)
- [Wisdom Of The (AI) Crowd: Investigating Artificial Swarm Intelligence In Large Language Models](https://mlsanity.com/paper/2606.31404/) (2026)

## Abstract (arXiv)

Advances in artificial intelligence (AI) have great potential to help address societal challenges that are both collective in nature and present at national or trans-national scale. Pressing challenges in healthcare, finance, infrastructure and sustainability, for instance, might all be productively addressed by leveraging and amplifying AI for national-scale collective intelligence. The development and deployment of this kind of AI faces distinctive challenges, both technical and socio-technical. Here, a research strategy for mobilising inter-disciplinary research to address these challenges is detailed and some of the key issues that must be faced are outlined.