“Never trust an AI platform whose loyalty you cannot trace. When the code serves the state or the shareholder before the citizen, your privacy becomes collateral.” – MJ Martin
There is significantly more risk when using Chinese-developed AI platforms compared to those built and operated in jurisdictions like the United States, Canada, or the European Union. The difference lies not only in technology design, but in governance models, surveillance laws, and state influence.
With the immense popularity of the Chinese AI platform, DeepSeek, I am constantly asked if it is safe to use.
My traditional response is that no AI platform can be truly safe and trustworthy for Canadians. You need to be judicious how you use – any AI platform – from any country. You need to ask yourself – if you, your company, your friends, or your family – will be at risk as a result of using any AI platform. They all have inherent vulnerabilities that can be exploited and be harmful.
In an effort to properly provide a well thought out answer to this common question, this paper aspires to offer a detailed, balanced analysis of the comparative risks.
Government Access and State Control
Chinese law explicitly requires companies to cooperate with state intelligence and security services. Article 7 of China’s National Intelligence Law (2017) mandates that “any organization or citizen shall support, assist, and cooperate with national intelligence work.” This means that data collected by Chinese AI companies can legally be shared with, or requisitioned by, the state without user consent or judicial oversight.
In contrast, the United States and Canada operate within constitutional and common-law systems that restrict government access to private data without a warrant or due process. Although the U.S. Patriot Act and related national-security powers have raised valid concerns, there is still a framework for appeal, transparency reports, and judicial review.
In practical terms, this means that user data submitted to a Chinese AI model may not remain private; even if the company claims to protect it. In an authoritarian system, corporate privacy policy cannot override state authority.
Data Localization and Cross-Border Flow
China enforces strict data-localization laws, requiring that most data generated within its borders be stored domestically and undergo government security reviews before being transferred abroad. That gives Beijing extensive leverage over both corporate data practices and international data exchange.
By contrast, U.S. and Canadian AI companies routinely host data on globally distributed cloud infrastructure, subject to regional privacy frameworks such as the General Data Protection Regulation (GDPR) in Europe or Canada’s Personal Information Protection and Electronic Documents Act (PIPEDA). These frameworks, while imperfect, provide recourse for users and enforce principles such as minimization, purpose limitation, and user consent.
The net effect is that Chinese AI ecosystems are far more closed and government-controlled, while North American systems are open but commercially driven, a crucial distinction in who ultimately wields power over your data.
Surveillance Integration and Social Scoring
Chinese AI development is deeply intertwined with state surveillance and population management, including facial-recognition systems, biometric tracking, and the Social Credit System. Leading AI firms such as SenseTime, Megvii, and iFlytek have all been implicated in government surveillance programs. When an AI company’s core business involves behavioural monitoring or predictive policing, privacy is secondary to compliance.
In the U.S. and Canada, surveillance partnerships exist, for example, between AI vendors and law enforcement, but they are far more regulated and subject to public scrutiny, court oversight, and investigative journalism. Civil-liberty groups can challenge misuse, and privacy commissioners can intervene. These accountability mechanisms, absent in China, make a profound difference.
Training Data and Censorship Bias
Another major risk concerns training-data bias and content censorship. Chinese AI systems operate under tight ideological restrictions. Generative models such as Baidu’s Ernie Bot or Alibaba’s Qwen are explicitly filtered to avoid politically sensitive topics (e.g., Tiananmen, Xinjiang, or Taiwan). This form of algorithmic censorship not only limits free expression but also distorts factual accuracy.
American AI systems, although influenced by corporate moderation policies, are not bound by state ideology. Their constraints are commercial and reputational rather than political. Users of Chinese AIs may therefore receive filtered, manipulated, or incomplete answers designed to align with government narratives. This represents a cognitive-integrity risk, not merely a privacy one.
Transparency and International Oversight
Western AI companies such as OpenAI, Anthropic, or Google DeepMind are subject to external academic scrutiny, media oversight, and independent audits. Stanford’s Center for Human-Centered AI (HAI) and the OECD AI Observatory regularly assess transparency practices. While far from perfect, this culture of accountability allows researchers to expose flaws and advocate for reform.
By contrast, Chinese AI research and corporate governance occur largely within state-approved boundaries. External auditing of data handling, bias mitigation, or privacy protections is rare or impossible. Without transparency, users cannot verify claims of safety or data protection.
Commercial versus Political Risk
In the U.S., privacy risks stem primarily from commercial exploitation; data being used to train models, target ads, or personalize content for profit. These are serious concerns but generally bounded by market and legal forces.
In China, the risk extends to political exploitation, data used for surveillance, censorship, or coercion. Once your data enters that system, it may serve political purposes beyond your awareness or consent. For foreign users, this could include profiling, blacklisting, or cross-border monitoring.
Can Chinese AI Be Used Safely?
There are legitimate, innovative Chinese AI systems in areas such as manufacturing, language translation, and education. For non-sensitive applications running locally (e.g., offline machine-vision or industrial robotics), the privacy risks are lower. However, any cloud-based AI service hosted or governed within China should be treated as non-private by design.
Users can mitigate risk through the following practices:
1. Avoid submitting personally identifiable or proprietary information to Chinese-based AI platforms.
2. Prefer Western or Canadian-hosted systems that disclose data-retention policies.
3. If collaboration with Chinese AI is necessary, use anonymised or synthetic datasets.
4. Monitor compliance with international privacy standards such as ISO/IEC 27701 or GDPR equivalence.
The Broader Question: Trust and Sovereignty
The deeper issue is not simply about China versus the United States or Canada. It is about data sovereignty, who owns, controls, and benefits from your information. Every jurisdiction encodes its values in its data laws. Authoritarian regimes prioritize control; liberal democracies prioritize consent (albeit inconsistently); and corporations prioritize profit.
For Canadians and other democratic citizens, the challenge is to assert national values in this global AI race. Canada’s privacy regime and forthcoming AI legislation should aim not only to protect individuals but to ensure that Canadian data serves Canadian interests. Trust in AI must be grounded in transparency, accountability, and respect for human rights.
Summary: The Greater Risk Lies in the Shadows
Yes, Chinese AI systems present a greater privacy and ethical risk than their U.S. or Canadian counterparts, not because the American and Canadian systems are benign, but because Chinese law institutionalizes surveillance as a feature rather than a flaw. When state power and data collection are indistinguishable, privacy cannot exist in any meaningful sense.
Yet users should not become complacent about Western AI either. The surveillance of profit can be as invasive as the surveillance of politics. The difference is that one sells your data; the other commands it. The path forward lies in demanding stronger international privacy standards, technological transparency, and digital self-sovereignty. Only then can humanity benefit from artificial intelligence without sacrificing the very privacy that defines what it means to be free.
About the Author:
Michael Martin is the Vice President of Technology with Metercor Inc., a Smart Meter, IoT, and Smart City systems integrator based in Canada. He has more than 40 years of experience in systems design for applications that use broadband networks, optical fibre, wireless, and digital communications technologies. He is a business and technology consultant. He was a senior executive consultant for 15 years with IBM, where he worked in the GBS Global Center of Competency for Energy and Utilities and the GTS Global Center of Excellence for Energy and Utilities. He is a founding partner and President of MICAN Communications and before that was President of Comlink Systems Limited and Ensat Broadcast Services, Inc., both divisions of Cygnal Technologies Corporation (CYN: TSX).
Martin served on the Board of Directors for TeraGo Inc (TGO: TSX) and on the Board of Directors for Avante Logixx Inc. (XX: TSX.V). He has served as a Member, SCC ISO-IEC JTC 1/SC-41 – Internet of Things and related technologies, ISO – International Organization for Standardization, and as a member of the NIST SP 500-325 Fog Computing Conceptual Model, National Institute of Standards and Technology. He served on the Board of Governors of the University of Ontario Institute of Technology (UOIT) [now Ontario Tech University] and on the Board of Advisers of five different Colleges in Ontario – Centennial College, Humber College, George Brown College, Durham College, Ryerson Polytechnic University [now Toronto Metropolitan University]. For 16 years he served on the Board of the Society of Motion Picture and Television Engineers (SMPTE), Toronto Section.
He holds three master’s degrees, in business (MBA), communication (MA), and education (MEd). As well, he has three undergraduate diplomas and seven certifications in business, computer programming, internetworking, project management, media, photography, and communication technology. He has completed over 60 next generation MOOC (Massive Open Online Courses) continuous education in a wide variety of topics, including: Economics, Python Programming, Internet of Things, Cloud, Artificial Intelligence and Cognitive systems, Blockchain, Agile, Big Data, Design Thinking, Security, Indigenous Canada awareness, and more.