arXiv:2606. 12437v1 Announce Type: cross Abstract: The increasing encroachment of artificial intelligence (AI) on social life raises significant risks for society, particularly within the infospheres created and controlled by companies such as Google, Facebook, Apple, and Amazon.
By Oren Perez, Nurit Wimer
The paper examines how artificial intelligence impacts freedom of expression, focusing on two technologies: social media recommendation algorithms and conversational AI chatbots. It argues that recommendation algorithms shape speech visibility in the digital public sphere, making them relevant to free‑speech philosophy, while conversational AI raises questions about granting speech rights to agents and users’ right to information. The work also explores corporate speech rights for platforms and developers, aiming to highlight unresolved issues from AI’s rapid growth.
By Etienne Brown
arXiv:2606. 28331v1 Announce Type: cross Abstract: The widespread deployment of generative artificial intelligence (AI) models has raised serious concerns about the proliferation of AI-generated content.
By Andr\'es F\'abrega, Arkaprabha Bhattacharya, Miranda Christ, Sunoo Park
arXiv:2607. 12295v1 Announce Type: cross Abstract: The rapid integration of artificial intelligence (AI) and generative AI (GenAI) into education presents significant opportunities to enhance teaching and learning, while raising ethical concerns about the responsible use of these technologies in educational settings.
By Akriti Bagale, Nafisa Mehjabin, Ali \"Unl\"u, Aditya Johri
arXiv:2607. 24391v1 Announce Type: cross Abstract: AI systems already govern.
By Gilad Abiri
arXiv:2608. 16470v1 Announce Type: cross Abstract: We examine the worldwide trend of mandatory labeling of generative artificial intelligence(GenAI) as a reactive, symbolic form of legislation triggered by technological panic and institutional responses.
By Jingyi Chen, Chaofan Bu, Shibo Yan, Xuesong Li
arXiv:2608. 12346v1 Announce Type: new Abstract: This position paper argues that modern AI alignment methods - originally designed to prevent harmful output - are dual-use technologies that may easily be misused by malicious actors for censorship and manipulation.
By Sarah Ball, Phil Hackemann
arXiv:2609.23083v1 Announce Type: new
Abstract: The distinction between the spirit and letter of the law is a central issue across research and everyday life, and a growing concern for building safe,...
By Peng Qian, Andrew Li, Sam Chen, Sonia K. Murthy, Yonatan Belinkov, Tomer D. Ullman
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:2608. 04011v1 Announce Type: cross Abstract: This article examines the enduring epistemic and methodological crisis of traditional legal practice in light of the opportunities and constraints introduced by artificial intelligence.
By Ali Goksu, F. Gozde Kardes, Mustafa Yaylali
arXiv:2606. 00621v1 Announce Type: cross Abstract: Generative artificial intelligence has fundamentally changed how content is now produced.
By Shubhashis Sengupta, Benjamin McCarty, Milind Savagaonkar, Rhine Andotra
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