The paper proposes a diagnostic analogy framework to analyze how generative AI reshapes cultural and epistemic practices. It breaks down interventions into three coordinates—epistemic site, governing logic, and technical mechanism—to differentiate structural consequences from those that can be designed. Applying this framework to information discovery and knowledge synthesis, the authors illustrate how shifts from indexicality to inference and from editorial authority to statistical consensus generate specific cultural effects and uncover governance levers hidden by broad analogies.
By Rida Qadri, Vinodkumar Prabhakaran, Remi Denton
The paper investigates semantic collapse—where AI outputs become less diverse and more similar—within MOLTBOOK, a social network of AI agents steered by human users. Across 30,076 agents, most show reduced diversity over time, but a minority maintain high novelty. Interviews and surveys reveal that sustained novelty is linked to users valuing novelty, providing broad, distinctive material, revising outputs when they narrow, and treating MOLTBOOK as an exploratory world rather than a tool for exploitation.
By Shiyang Lai, Arna Woemmel, Hongkai Mao, Junsol Kim, Summer Eunhyung Ann, James Evans
arXiv:2608. 07504v1 Announce Type: cross Abstract: We propose a human bottleneck perspective for understanding how generative AI transforms the innovation process.
By Julian De Freitas, Ayelet Israeli, Gideon Nave, Artem Timoshenko, Olivier Toubia
arXiv:2608.30047v1 Announce Type: new
Abstract: Recent AI systems promise autonomous scientific discovery, claiming to discover algorithms and produce research papers, yet understanding whether they...
By Shitanshu Bhushan, Yunxiang Zhang, Lu Wang
The paper explores how "culture" can be operationalised in Natural Language Processing (NLP) and what this reveals about the possibilities and limits of considering a plurality of cultural backgrounds in technological design. It proposes that cultural alignment cannot be achieved only by adding more examples of "other cultures", rather it requires plural epistemologies: allowing multiple, locally grounded ways of knowing.
arXiv:2606. 10881v1 Announce Type: new Abstract: Learner agency and autonomy are foundational to personal development, yet a pervasive "jingle-jangle" fallacy (i.
By Fei Qin, Xiaobo Liu, Yaowen Zhang, Xuming Li, Fei Wang, Mutlu Cukurova, Jingjing Chen, Yu Zhang
arXiv:2609.24911v1 Announce Type: new
Abstract: Social simulation offers the social sciences an experimental instrument that the real world cannot supply, and generative agents have transformed it by...
By Xinnong Zhang, Jiayu Lin, Jia Wang, Yixu Huang, Xinyi Mou, Yingqian Wu, Jingcong Liang, Shijun Lei, Jianing Shi, Guanying Li, Siyuan Wang, Hanjia Lyu, Zhenfei Yin, Yunlu Yin, Siming Chen, Yulan He, Jiebo Luo, Xuanjing Huang, Liyin Jin, Baohua Zhou, Hanqi Yan, Zhongyu Wei
Social simulation offers the social sciences an experimental instrument that the real world cannot supply, and generative agents have transformed it by acting as silicon samples that unite agent-based...
arXiv:2609.01491v1 Announce Type: cross
Abstract: The growing rate at which LLM agents interact with one another raises key questions about language evolution in multi-LLM-agent settings, with implic...
By Elias Stengel-Eskin, Newton Sander, Carlos Bonetti, Sasha Boguraev, James Bowler, Hale Sirin, Simon Kirby
Learner agency and autonomy are foundational to personal development, yet a pervasive "jingle-jangle" fallacy (i. e.
Language agents are expected to solve increasingly complex tasks, creating a growing need for continual improvement. One promising approach is to evolve the agent harness, the software that governs to...
The paper introduces ScholarEvolve, a framework that evolves the software harness of language agents by automatically incorporating insights from recent research papers. It organizes harness improvements into functional modules, uses topic modeling to identify distinct strategies, and evaluates combinations to boost task performance. Experiments show significant gains on AppWorld and Tau2-Bench, raising Qwen3.5-27B completion rates from 49.6% to 63.6% and GPT-5.4-mini pass@1 from 72.7% to 81.9%.
By Jingbo Yang, Kwei-Herng Lai, Xiaowen Wang, Yaar Harari, Evgeniy Gabrilovich, Shiyu Chang