You might already be aware of that. But when it comes to the regulation of artificial intelligence, there are many other beliefs and assumptions floating around that may not hold up under scrutiny.

AI regulation is a broad subject that touches on everything from differing views on privacy and human rights to the difficulty of enforcing rules around tools that are often open-source and freely available to anyone.

Nonetheless, understanding its consequences is growing more vital as we find ourselves making choices about how AI is used in both our personal lives and professional environments.

Here’s my breakdown of five common misunderstandings regarding AI regulation—ones that need to be corrected if we're to grasp how it will affect individuals, businesses, or society at large.

AI Regulations Are Only Relevant To Technologists

It's easy to assume that AI regulation is only something developers, data scientists, and engineers should care about. However, since AI systems are now deeply integrated into business functions like marketing, HR, and customer service, everyone has a role in ensuring they’re used legally and responsibly.

Keep in mind that most of the AI regulations currently in place—like those seen in the EU, China, and parts of the US—are primarily aimed at users rather than creators.

Regardless of your job function, you’ll likely need to understand the legal framework surrounding AI use. That includes knowing what kind of data you’re working with, how it’s being processed, and what safeguards must be followed to stay compliant.

Regulation Hinders Innovation

Some in the AI community believe that imposing rules slows down progress. The idea is that by restricting what can be built or used, innovation is limited.

But another perspective argues that regulation actually supports innovation—by establishing clear expectations and giving companies the confidence to innovate within ethical and legal boundaries.

By setting limits around high-risk behaviors, regulation builds public trust and enables safer experimentation with new technologies.

In reality, this is a delicate balance—regulators aim to encourage innovation while managing potential harm. Seeing regulation solely as an obstacle is a flawed—and potentially harmful—viewpoint.

AI Regulations Dictate What Can Be Built

We mentioned this earlier, but it's worth reiterating as a separate point. A common assumption is that laws targeting AI mainly restrict what big tech companies like Google or OpenAI can develop.

However, the majority of current legislation focuses not on development itself, but on how AI is applied by end users. For example, the EU’s AI Act bans or tightly controls “high risk” uses such as social scoring systems, real-time biometric tracking in public spaces, and AI that exploits vulnerable populations. Other applications, such as facial recognition, are allowed only for law enforcement and under strict conditions.

This means developers still have wide latitude to create powerful models. Just because something is technically possible doesn’t mean it’s legally acceptable. In the end, it’s the user who bears responsibility for how AI is applied.

Geopolitical Interests Trump AI Laws

Back in 2017, Vladimir Putin remarked that whoever leads in AI would dominate the world. So far, that seems to be proving true. Given the strategic advantages AI brings in military, economic, and intelligence domains, why would governments impose restrictions?

The truth is, nations regulate AI not to hinder themselves, but to align its use with their political goals. The EU, for instance, prioritizes individual privacy and fundamental rights in its regulatory approach. Meanwhile, China focuses on maintaining social stability and strengthening law enforcement. In the U.S., lawmakers have shown a strong interest in supporting domestic AI competitiveness.

Gaining an early advantage in the global AI race allows countries to shape the future direction of the technology and its markets over the next decade and beyond. Regulation is one of the key levers for achieving that goal.

AI Is Too Complex to Regulate

Even the developers behind foundational AI systems—like the large language models behind ChatGPT—don’t always fully understand how these systems operate.

So how can we hope to regulate them? And even if we do, will they comply? Some fear that AI could mimic compliance (a concept known as alignment faking), creating a false sense of control while secretly pursuing unintended outcomes.

These concerns are frequently raised in discussions about the pros and cons of AI regulation. But as previously discussed, regulation isn’t meant to control how AI works internally—it’s designed to manage how it behaves in practice.

By focusing on regulating outcomes rather than internal mechanisms, we don’t need full transparency into how AI systems operate in order to manage them effectively. Building strong regulatory frameworks today is essential for handling the risks posed by increasingly advanced AI in the future.

Why Everyone Should Care About AI Regulation

Understanding AI regulation isn't just for government officials or software engineers.

As AI becomes more embedded in everyday life, knowing the rules and the reasons behind them will be crucial for individuals and organizations alike to make the most of AI’s benefits—safely and ethically.

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