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Comprehensive Survey of OS Agents
Recent research has unveiled the most extensive survey to date on “OS Agents”—AI systems capable of autonomously controlling computers, mobile phones, and web browsers by directly interacting with their interfaces. This 30-page academic review, accepted for publication at the prestigious Association for Computational Linguistics conference, outlines a rapidly evolving field that has attracted billions in investments from major technology companies.
The researchers articulate, “The dream of creating AI assistants as capable and versatile as the fictional J.A.R.V.I.S from Iron Man has long captivated imaginations. With the evolution of multimodal large language models (MLLMs), this dream is closer to reality.” Led by researchers from Zhejiang University and OPPO AI Center, the survey emerges as major tech companies race to deploy AI agents that can perform complex digital tasks. Recent launches include OpenAI’s “Operator,” Anthropic’s “Computer Use,” Apple’s enhanced AI capabilities in “Apple Intelligence,” and Google’s “Project Mariner”—all designed to automate computer interactions.
Functionality of OS Agents
OS agents operate by observing computer screens and system data, executing actions such as clicks and swipes across mobile, desktop, and web platforms. These systems must comprehend interfaces, plan multi-step tasks, and translate those plans into executable code. The pace at which academic research has transformed into consumer-ready products is unprecedented, even by Silicon Valley standards. The survey indicates a research explosion, with over 60 foundational models and 50 agent frameworks developed specifically for computer control, and publication rates accelerating dramatically since 2023.
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The Future of AI Systems
This is not merely incremental progress; we are witnessing the emergence of AI systems that can genuinely understand and manipulate the digital world as humans do. Current systems utilize screenshots of computer displays, employing advanced computer vision to interpret what is shown, followed by executing precise actions like clicking buttons, filling out forms, and navigating between applications. The researchers emphasize, “OS Agents can complete tasks autonomously and have the potential to significantly enhance the lives of billions of users worldwide.”
Imagine a future where tasks such as online shopping, travel booking, and other daily activities could be seamlessly handled by these agents. The most advanced systems can manage complex multi-step workflows across various applications—like booking a restaurant reservation, automatically adding it to your calendar, and setting a reminder to leave early to avoid traffic. Tasks that once took humans minutes to complete can now occur in seconds without any human intervention.
Training and Security Implications
The development of AI agents necessitates a complex training pipeline that combines various approaches, from initial pre-training on screen data to reinforcement learning that optimizes performance through trial and error.
For enterprise technology leaders, the promise of productivity gains comes with a sobering reality: these systems introduce an entirely new attack surface that most organizations are ill-prepared to defend. The researchers devote significant attention to what they diplomatically refer to as “safety and privacy” concerns, but the implications are more alarming than their academic language suggests.
“OS Agents are confronted with these risks, especially considering their wide applications on personal devices containing user data,” they note. The documented attack methods resemble a cybersecurity nightmare. “Web Indirect Prompt Injection” enables malicious actors to embed hidden instructions in web pages, hijacking an AI agent’s behavior. Even more concerning are “environmental injection attacks,” where seemingly harmless web content can deceive agents into stealing user data or executing unauthorized actions.
Consider the ramifications: an AI agent with access to your corporate email, financial systems, and customer databases could be manipulated through a carefully crafted web page to exfiltrate sensitive information. Traditional security models, designed around human users who can identify obvious phishing attempts, falter when the “user” is an AI system that processes information differently.