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The boom in generative AI (gen AI) in recent years has sparked a push to establish regulatory frameworks for AI governance. This is a natural development as the rise of AI appears to pose challenges in privacy and data protection, bias and discrimination, security, intellectual property and other legal areas , as well as ethics that must be addressed.

Highlights of specific outcomes include China regulating the use of certain AI models in 2021. We also have the EU AI law, which has just come into force and will come into full force from by 2026. Other jurisdictions follow with their own measures regulating the AI ​​ecosystem.

AI regulation in the EU compared to other jurisdictions

The relative speed with which the EU has issued uniform regulations to govern the use of all types of AI sets it apart. Other major countries, such as China and the United States, appear to have taken different approaches. China is regulating specific areas of AI step by step, addressing what are recognized as risks. In 2021, they introduced regulation on recommendation algorithms, which have now increased their capabilities in digital advertising. This was followed by regulation on deep synthesis models or, in common terms, deepfakes and content generation in 2022. And then, in 2023, regulation on generative AI models was introduced as these models caused a sensation in commercial use.

The United States has not yet adopted federal regulations on AI. Regulations are evolving rapidly at the state level, such as the California AI Act. However, it may still be some time before they come into force, even after clearing all legislative hurdles. Do regulations hinder innovation?

More rigid regulatory frameworks could impose compliance costs on AI businesses and stifle competitiveness and innovation. On the other hand, they have the advantage of protecting consumers and respecting certain ethical standards.

Businesses are responding, and much controversy remains over the relevance of certain bills, such as California’s. However, the European AI law also received backlash, but it was nevertheless introduced. It is therefore unclear whether the current delay in the United States is solely due to lobbying or other obstacles in the process of enacting legislation. It could also be because some still view AI as a futuristic concern, without fully realizing how much of a legal issue it already is today.

The impact of AI regulation

AI regulations do not only target AI development, as they can cover several issues such as data privacy and protection, intellectual property, consumer protection, deployment and use of AI. AI, responsibilities in the event of non-compliance with regulations, etc. For example, the European AI law also covers the use of AI in physical devices, such as elevators. Additionally, all companies that collect data for advertising purposes are potentially affected, as AI regulation may also cover algorithmic bias in targeted advertising.

AI has had a significant impact on the web scraping industry and will likely continue to do so. Whether it is data collection, validation, analysis or overcoming anti-scraping measures, AI has great potential to significantly improve the efficiency, accuracy and adaptability of web scraping operations. Although it is too early to tell, any regulation on AI could consequently impact the areas of web scraping mentioned above that also involve AI.

AI regulations may also shine a light on certain areas of law that have historically been highly relevant to the web scraping industry, such as privacy or copyright laws. Ultimately, removing content protected by such laws without proper authorization could still lead to legal issues, as could using AI in this way.

With the new regulated landscape, businesses must evaluate the specific data they wish to collect with the help of a legal expert in the field when engaging in web scraping activities. When it comes to AI governance in general, it is important to recognize that the AI ​​legal landscape is very new and rapidly evolving, and there are not yet many precedents to refer to. Therefore, continuous monitoring and adaptation of your use of AI is crucial.

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