Export of artificial intelligence and big data technologies: Compliance challenges in an emerging fieldAbstract


This paper explores the main compliance challenges faced by the export of artificial intelligence and big data technologies, including export control regulations, data privacy protection, intellectual property protection, and geopolitical factors. The article analyzes the complexity of the current international regulatory framework and proposes strategic recommendations to address these challenges.

I. Introduction
With the rapid development of artificial intelligence (AI) and big data technologies, these emerging technologies have become an important part of the global digital economy. However, compliance issues in the process of technology export have become increasingly prominent and have become an important obstacle to the international expansion of enterprises. The dual-use nature of AI and big data technologies, the sensitivity of cross-border data flows, and the inconsistency of regulatory policies in various countries together constitute unique compliance challenges in this field.

II. Major compliance challenges in the export of artificial intelligence and big data technologies

  1. Complexity of export control regulations
    Dual-use goods control: Many AI technologies are classified as dual-use items and are subject to strict export controls

Differences in multilateral control systems: Coordination issues between multilateral mechanisms such as the Wassenaar Arrangement and the Australia Group and domestic laws of various countries

Uncertainty in technology classification: Compliance risks caused by the difficulty in classifying emerging technologies

  1. Data privacy and cross-border flow restrictions
    Data protection regulations such as GDPR: The strict requirements of the EU General Data Protection Regulation on data processing

Data localization policy: China, Russia and other countries require that specific data be stored domestically

Sensitive data identification problems: How to define “personal data” and “sensitive data”

  1. Dilemma of intellectual property protection
    Differences in the protectability of algorithm patents in different jurisdictions

Balance between the use of open source software and the protection of proprietary technology

Trade secret protection mechanism in technology exports

  1. Influence of geopolitical factors
    Technology blockade and sanctions in the context of Sino-US technological competition

Technology export restrictions in the field of critical infrastructure

Conflicts of AI ethical standards under different value systems

III. Status of international regulatory frameworks

  1. Comparison of regulatory policies of major economies
    Countries/regions Characteristics of export control Data supervision focus AI ethics framework
    US ITAR/EAR system, focusing on national security Industry self-discipline, state-level legislative differences Focus on innovation, limited supervision
    EU Strictly follow multilateral export control agreements GDPR comprehensive protection, strict cross-border restrictions Risk-based hierarchical supervision
    China Dynamic update of technology export catalog Data classification and classification management, cross-border security assessment Emphasis on controllable development, application scenario restrictions
  2. International coordination mechanism and conflict
    Limitations of technology trade rules under the WTO framework
    Digital trade clauses in bilateral and regional trade agreements
    International Standards Organization’s efforts in AI ethics and technical standards
    IV. Response strategy recommendations
  3. Enterprise-level compliance system construction
    Establish a technology export compliance risk assessment matrix
    Develop automated compliance screening tools
    Implement a full-process compliance monitoring mechanism
  4. Industry best practices
    Form a technology export compliance sharing database
    Establish an industry self-discipline and ethics review committee
    Develop verifiable compliance technology solutions
  5. Policy recommendations
    Promote the coordination of international AI technology export control standards

Establish a multilateral trust mechanism for cross-border data flows

Improve the talent training system for technology export compliance

V. Conclusion
The compliance challenges of AI and big data technology exports reflect the tension between technological innovation and the regulatory framework. In the face of this complex situation, enterprises, industry organizations and governments need to collaborate to build a new compliance system that takes into account both security and development. In the future, with the iteration of technology and changes in the international situation, compliance requirements will continue to evolve, and enterprises should establish dynamic and adaptive compliance capabilities.

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