Author: Lawyer Zhao Xuan

Introduction: A Systemic Conflict Triggered by "Proxy Operations"

Recently, a low-key user experience has sparked heightened tension between the AI industry and internet platforms—some smartphones equipped with AI assistants, when attempting to automatically complete operations like sending WeChat red envelopes or placing e-commerce orders via voice commands, were identified by platform systems as "suspected of using cheats," triggering risk warnings and even account restrictions.

On the surface, this appears to be a technical compatibility issue; however, in a broader industrial context, it essentially unveils a structural conflict surrounding "who has the right to operate smartphones and who controls user access."

On one side are smartphone manufacturers and large model teams hoping to deeply embed AI into operating systems to achieve "seamless interaction." On the other side are internet platforms that have long relied on app entry points, user pathways, and data closed loops to build their commercial ecosystems.

When the "universal assistant" begins to "take action" on behalf of users, is it an efficiency tool or a rule breaker? This question is being pushed to the forefront of legal scrutiny by reality.

"Is the future here" or "risk warning"—a "code war" happening behind smartphone screens.

Recently, users who have obtained the latest AI smartphones may experience a dramatic scenario of "one second in the future, one second warning": just as they marvel at its convenience, they receive risk warnings from platforms like WeChat.

This all began with the deep collaboration between ByteDance's "Doubao" large model and several smartphone manufacturers. Today's voice assistants are no longer just for checking the weather; they are super butlers that can "see the screen and simulate operations."

Imagine a scenario where you simply say to your phone, "Send a red envelope in the Qingfei football team group" or "Help me buy the best deal on the new Adidas soccer shoes," and the phone automatically switches to the app, compares prices, and makes payments—all without you lifting a finger.

This technology, based on "simulated clicks" and "screen semantic understanding," has truly allowed AI to take over smartphones. However, this "smoothness" quickly collided with the "iron plate" of internet platforms.

Many users have found that using Doubao AI to operate WeChat triggers account restrictions and even warnings of "suspected use of cheats." E-commerce platforms like Taobao are also highly vigilant against such automated access. Some bloggers have likened it to AI being a butler running errands for you, but being stopped by mall security: "We do not serve robots."

• Users are confused: Why can't I use my own phone and my authorized AI to do the work for me?
• Platforms maintain: My ecosystem, my security, do not allow external "proxy operations."

This seemingly minor friction over technical compatibility is, in fact, another milestone game in the history of Chinese internet. It is no longer a simple battle for traffic but a direct collision between operating systems (OS) and super apps over "digital sovereignty."

The Dimensionality Reduction of Business Logic—When "Walled Gardens" Encounter "Wall Breakers"

Why are the reactions of major companies like Tencent and Alibaba so intense? This can be traced back to the core business model of the mobile internet—"walled gardens."

The commercial foundation of social, e-commerce, and content platforms lies in monopolizing entry points and user engagement. Every click and every browsing step is crucial for ad monetization and data accumulation. The emergence of "system-level AI assistants" like Doubao directly challenges this model.

This is a profound game about "entry" and "data." AI smartphones have touched the core commercial lifeline of internet giants, primarily for three reasons:

1. The "Click Icon Removal" Crisis:

When users only need to speak, and AI directly completes tasks, the app itself may be bypassed. Users no longer need to open apps to browse products or view ads, which means the advertising exposure and user attention economy that platforms rely on will be significantly weakened.

2. The "Parasitic" Acquisition of Data Assets:

AI operates and reads information by "seeing" the screen, without needing the platform to open interfaces. This effectively bypasses traditional cooperation rules, directly acquiring content, products, and data that platforms have invested heavily in building. From the platform's perspective, this is a "free-riding" behavior, and it may even use this data to train its own AI models.

3. The Change of "Gatekeeper" in Traffic Distribution:

In the past, the power of traffic distribution was held by super apps. Now, system-level AI is becoming the new "master switch." When users ask, "What do you recommend?" the AI's answer will directly determine where commercial traffic flows, enough to reshape the competitive landscape.

Therefore, the platforms' warnings and defenses are not merely technical exclusions but fundamental defenses of their commercial ecosystems. This reveals the deep-seated contradictions that have yet to be reconciled between technological innovation and platform rules.

Preparing for the Storm—A Deep Dive into the Four Legal Risks of AI Smartphones

As legal practitioners, when we look through the lens of the AI smartphone and major company disputes, we can see four unavoidable core legal risks:

1. Competitive Boundaries: Technological Neutrality Does Not Equal No Liability

The current focus of the dispute is whether AI operations constitute unfair competition. According to the "Anti-Unfair Competition Law," using technical means to hinder others' normal services of network products may constitute infringement.

"Cheat" Risks: In the "Tencent vs. 360 case" and several recent "automatic red envelope cheat cases," judicial practice has established a principle: unauthorized modification or interference with the operating logic of other software, or increasing server load through automation, may constitute unfair competition. If AI's "simulated clicks" skip ads or bypass interaction verification, affecting platform services or business logic, it may also face infringement determinations.

Traffic and Compatibility Issues: If AI guides users away from the original platform to use its recommended services, it may involve "traffic hijacking." Conversely, if the platform indiscriminately bans all AI operations, it may also need to justify whether its ban is a reasonable and necessary self-defense.

2. Data Security: Screen Information is Sensitive Personal Information

AI needs to "see" screen content to execute commands, which directly touches on the strict regulations of the "Personal Information Protection Law."

• Sensitive Information Handling: Screen content often contains sensitive personal information such as chat records, account information, and location tracking, which legally requires obtaining "separate consent" from users. The common "blanket authorization" seen in AI smartphones is questionable in its validity. If AI "sees" and processes private chat information while executing booking commands, it may violate the "minimum necessity" principle.
• Ambiguous Responsibility: Is data processing happening locally on the phone or in the cloud? Once leaked, how is responsibility divided between the smartphone manufacturer and the AI service provider? Current user agreements often do not clearly define this, creating compliance risks.

3. Antitrust Disputes: Do Platforms Have the Right to Refuse AI Access?

Future litigation may revolve around "essential facilities" and "refusal to deal."

AI smartphone parties may argue: WeChat and Taobao already possess attributes of public infrastructure, and refusing AI access without just cause may constitute an abuse of market dominance, hindering technological innovation.

Platform parties may counter: Data openness must be premised on security and property protection. Allowing AI to read data without authorization may breach technical protection measures, harming user and platform rights.

4. User Responsibility: When AI Makes Mistakes, Who Pays?

As AI transitions from a tool to an "agent," it brings a series of civil liability issues.

• Effectiveness of Agency Actions: If AI mistakenly buys the wrong product due to misunderstanding (e.g., executing "cheap phone" as a counterfeit), is it a significant misunderstanding or improper agency? Can users claim refunds based on "not acting personally"?
• Account Ban Losses: If a user's third-party account is banned due to using AI features, they may seek compensation from the smartphone manufacturer. The key lies in whether the risk was clearly indicated at the time of sale. If the warning was insufficient, the manufacturer may face collective rights protection.

This game is not only a technological dispute but also a redefinition of the legal boundaries of data ownership, platform responsibility, and user authorization in practice. Both AI manufacturers and platforms need to find a clear balance between innovation and compliance.

Conclusion: Boundaries of Rights and the Spirit of Contracts

The friction between Doubao and major companies appears to be a product conflict, but it actually reveals the fracture between the old and new orders: the past app-centric model is facing the impact of an AI-centric internet experience.

As legal practitioners, we clearly see that the existing legal system is struggling to cope with the intervention of general artificial intelligence. Simple "bans" or "bypasses" cannot serve as sustainable solutions. The future path may not lie in continuing to rely on technologies like "simulated clicks" to evade, but in promoting the establishment of a standardized AI interaction interface protocol.

In the absence of clear rules, we pay tribute to those who persist in exploring the frontiers of AI and uphold the principle of technology for good. At the same time, we must be soberly aware that respecting boundaries often leads to longer-lasting outcomes than disruption itself.

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