Code and Law: Who Owns the AI ​​Result

Ethical and legal issues: to whom owns the code generated AI

Author's blog ZeroBugzague

Introduction

AI programmers are no longer science fiction. They are already working - not in the form of androids with a keyboard, but in the form of the code, auto -complements, sentences and ready -made solutions. Github Copilot, Tabnine, Codeium and other tools based on language models allow the programmer not so much to write as oversee code. The car generates, a person edits.

And everything would be fine - until the question arises: And who owns the result? Who is the author of the line proposed by AI? Is it possible to use such a code in commercial projects? Who is responsible if he violates other people's rights?

Today, these issues are more relevant than ever. And the author's blog ZeroBugzague It offers to understand them: not only from the point of view of the law, but also from the perspective of ethics, responsibility and future digital creation.

The main part

When the code is not written by a person

AI tools create a code based on huge data arrays-billions of lines from open repositories, forums, documentation. The models trained on these data predict which code will be logical in the current context.

In practice, this means that the programmer can write a comment:
// Form a search function by a key word in an array of objects
And get the finished, working implementation.

But where did this implementation come from?
She could be:

• completely generated again, without direct copying;
• based on templates found in thousands of repositories;
• Partially coincide with the code under the license.

So, there is a conflict: Is this code created again or is it a processing of a stranger? And who is his author in this case?

Legal uncertainty

At the time of writing the article, most countries do not recognize AI as an author works. The right to a product of intellectual labor - whether it is code, text, music or image - receives an individual or legal entity that participated in the creation. There can be no artificial intelligence by a legal author.

But who then becomes the author of the code generated AI:

• The developer who wrote a request or comment?
• The company in which he works?
• Model creator?
• Has the platform?

This question remains today open , and much depends on the conditions of the use of a particular tool. GITHUB Copilot, for example, directly indicates that the user himself is responsible for the generated code and its verification for compliance with licenses.

So, while there is no clear legal protection, each team or developer must Evaluate risks yourself .

The danger of "licensed infection"

Particular attention should be paid to the risk of the so -called License Contamination -When the generated AI code accidentally or intentionally includes elements that are under limiting licenses (for example, GPL or AGPL).

If such a code is in a commercial product, this may entail:

• copyright violation;
• lawsuits;
• The requirement to open the source code of the entire product.

And although most modern models seek to avoid direct copying, cases of coincidences have already been recorded. One of the most famous is a lawsuit against Github Copilot, filed in 2022, which claimed that the model generated a code identical to the protected original.

Conclusion: Trust, but check . Any AI-generated code must go through an internal audit, especially if it is used in a product with a commercial license.

Ethical aspects: respect for the work of others

Regardless of the legal position, the issue of belonging to the AI ​​code is also Ethical question . If artificial intelligence generates a code that repeats someone else's solution, even in part, is appropriate to ask: is this correct?

Is it possible to consider the result of creativity trained in millions of lines of the Open-Source, truly “your own” if you just set the direction?

Some developers who publish code in open repositories express concern: they do not agree that their work is used in training commercial models, which are then sold. Others, on the contrary, consider this a natural continuation of the Open-Source of culture.

ZeroBugzague It adheres to ethics of respect: if you use the AI ​​code-check, adapt, clarify the origin. Awareness in digital creation is more important than speed.

What to do to developers and teams

While the world is moving to the development of global standards, it is important to use Practical strategies:

• Use AI as a draft, not the truth
  The generated code is not the final result. It requires verification, refinement and adaptation to the project.
• Integrate automatic license analysis tools
  Such tools can identify potential violations in the structure of the code.
• Separate risk zones
  Do not use AI helpers in critical security modules, finance, medicine without manual revision.
• Teach commands of digital ethics
  Each developer must understand the consequences of non-visual copying or blind use of AI result.
• Fix the origin
  It is important to document which code is generated by AI and for what request - this will help in the case of a legal proceedings.

Conclusion

AI changes programming. He accelerates, simplifies, inspires. But along with this, he puts us before questions that cannot be answered automatically. Who owns the line generated by request? Where is the line between inspiration and copying? Who is responsible for violation, if the author is an algorithm?

Blog ZeroBugzague I am convinced: right now we are forming a culture of responsible interaction with AI. Honesty, respect for someone else's work, legal awareness - this is the basis of confidence in the world, where the code is increasingly not writing a person, but a car.