How can humans make sense of the rapid takeoff of artificial intelligence (AI)? We studied the sensemaking dynamics of AI through an open-ended, mixed-methods study with computational text analysis of...
arXiv:2608.24748v1 Announce Type: cross
Abstract: How can humans make sense of the rapid takeoff of artificial intelligence (AI)? We studied the sensemaking dynamics of AI through an open-ended, mixe...
By Jacy Reese Anthis, Erik Brynjolfsson, James Evans
arXiv:2606. 13658v1 Announce Type: new Abstract: This paper examines three recent frameworks for understanding the cognitive and epistemic consequences of artificial intelligence: Tri-System Theory, Thinkframes, and System 0.
By Marianna Bergamaschi Ganapini, Massimo Chiriatti, Enrico Panai, Giuseppe Riva
arXiv:2608. 08408v1 Announce Type: cross Abstract: Logics of abstraction in computational AI research often push important forms of knowledge and reflection aside: dominant standards of legitimacy separate from lived experience of harm; the goals of work misalign with the practices that operationalize them; and career demands crowd out critical reflection.
By Vyoma Raman, Isabel O. Gallegos, Neha Srivathsa
The paper reviews secondary studies and research agendas on generative AI (GenAI) in information systems, synthesizing evidence from 28 selected papers. It identifies GenAI’s transformative benefits—productivity, innovation, personalization, and democratized expertise—while highlighting challenges such as technical unreliability, ethical risks, and governance gaps. The authors propose a research agenda that shifts IS scholarship toward shaping the co‑evolution of AI capabilities with organizational routines, societal values, and regulatory institutions, emphasizing hybrid human‑AI ensembles, situated validation, design principles for probabilistic systems, and adaptive governance.
By Aleksander Jarz\k{e}bowicz, Adam Przyby{\l}ek, Jacinto Estima, Yen Ying Ng, Jakub Swacha, Beata Zielosko, Lech Madeyski, Noel Carroll, Kai-Kristian Kemell, Bartosz Marcinkowski, Alberto Rodrigues da Silva, Viktoria Stray, Netta Iivari, Anh Nguyen-Duc, Jorge Melegati, Boris Deliba\v{s}i\'c, Emilio Insfran
arXiv:2606. 09848v1 Announce Type: cross Abstract: As generative and agentic AI becomes embedded in everyday products, practitioners face a persistent challenge: how to design human-AI coordination -- the ongoing mutual adjustment between users and AI systems as mediate through interfaces-that supports usability, trust, and safety.
By James Pierce, Vaiva Kalnikait\.e, Siddharth Gupta, Brian Granger