The World Wide Web was built on an assumption held for three decades: the primary consumer of web content is a human being. This permeates every layer; its access model presumes human visitors, its economics rest on human attention, and its content targets human perception.
arXiv:2607. 22953v1 Announce Type: new Abstract: Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a model where third-parties collect and control massive amounts of user data.
By Sourena Khanzadeh, Daniel Platnick, Marjan Alirezaie, Hossein Rahnama
arXiv:2607. 08147v1 Announce Type: cross Abstract: Autonomous web agents promise to automate everyday browsing tasks, but inherit one of the web's oldest attack surfaces.
By Corban Villa, Alp Eren Ozdarendeli, Sijun Tan, Raluca Ada Popa
An LLM-based agent is a loop that reads itself. Agentic frameworks externalize identity, memory, and disposition into editable files.
arXiv:2606. 30801v1 Announce Type: cross Abstract: Personalization algorithms determine what content users encounter on online platforms.
By Alessandro Morosini, Sarah H. Cen, Andrew Ilyas, Hedi Driss, Aleksander M\k{a}dry, Chara Podimata
arXiv:2607. 13718v1 Announce Type: cross Abstract: As AI agents gain prevalance, users are increasingly exposed to the risks such systems entail.
By Alexandra E. Michael, Franziska Roesner
arXiv:2608. 03800v1 Announce Type: cross Abstract: An LLM-based agent is a loop that reads itself.
By Holly Lewis (Southern Illinois University Carbondale)
arXiv:2607. 05277v1 Announce Type: cross Abstract: Defenses that provide security guarantees against prompt injection attacks rely on strict isolation between trusted instructions and untrusted data.
By Kristina Nikoli\'c, Egor Zverev, Javier Rando, Matthew Jagielski, Edoardo Debenedetti, Florian Tram\`er
arXiv:2606. 14027v1 Announce Type: cross Abstract: Agentic browsers integrate autonomous AI agents into web browsers, enabling users to accomplish web tasks through natural-language instructions.
By Xilong Wang, Xiaoxing Chen, Patrick Li, Dawn Song, Neil Gong
arXiv:2607. 05363v1 Announce Type: new Abstract: Personal agents are becoming persistent user-owned intermediaries: they remember preferences, filter platform-mediated information, use tools, and negotiate with services.
By Dylan Zongmin Liu
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:2606. 25836v2 Announce Type: replace Abstract: To better assist users with completing challenging tasks, AI agents mediate communications, access data, and interact with different APIs.
By Hyejun Jeong, Dzung Pham, Amir Houmansadr, Eugene Bagdasarian