Github Copilot - Ethical Consideration

GitHub Copilot is trained on public repositories, including open-source projects, which may be governed by various licenses (like MIT, GPL, Apache, etc.). If Copilot generates code that is similar to or derived from open-source code with specific licensing terms, you might need to agree with those terms. For example, some licenses require attribution, which means you need to credit the original author in your project.

If you use the code generated by copilot in a commercial project without verifying its source, you could face legal issues if the original author claims ownership.

GitHub Copilot Legal Concerns

• Ownership: Since Copilot is trained on publicly available code, there is a possibility that the generated code could resemble existing work. This raises questions about who owns the generated code, especially if it is similar to copyrighted material.

• Copyright: Copilot may suggest code that is already used in existing projects, which could lead to copyright infringement if the original author's work is not properly attributed or licensed. Developers should be cautious when using Copilot to avoid legal issues related to intellectual property rights.

• Security: Copilot may suggest code that appears functional but contains hidden security vulnerabilities. Since the AI doesn't fully understand context, it's important for developers to review code for potential flaws, such as SQL injection risks, unencrypted data handling, or usage of outdated libraries.

There are several developers reported that copilot generated code that was similar to the code they written in past. This raises concerns about the originality of the code generated by copilot. As of now there is no any tool to verify authenticity of the code generated by copilot.

What is Github's Stance?

GitHub has stated that Copilot generates new code based on patterns it learned using text generation transformers, which means it does not directly copy code from any sources. However, there are cases where the generated code might look similar to existing code.

GitHub recommends developers to review and modify the code generated by Copilot to ensure it meets their project's requirements and follows best practices. They also advise developers to respect intellectual property rights, follow licensing terms, and conduct thorough code reviews to avoid legal issues.

How to Generate Safe Code from Copilot?

Here are some tips to generate safe code from Copilot:

• Review Code Suggestions: Always review the code Copilot suggests. Ensure it is following best practices and fits your projects requirements before integrating it.

• Modify Code: Make necessary modifications to the generated code to ensure it is secure, efficient, and accordance with your project's coding standards.

• Use Trusted Libraries: Where possible, prefer using well-established libraries instead of relying solely on AI-generated code. This can minimize risks of security vulnerabilities or bugs.

• Check for Security Flaws: Always review Copilot's code for potential security risks like SQL injections, XSS vulnerabilities, or weak encryption patterns. Conduct thorough testing and code reviews.

• Audit for Similarity to Existing Code: If the generated code appears too similar to existing projects or proprietary solutions, verify its origin to avoid copyright infringement.

• Enable Private Mode: When working on sensitive projects, You can disable Copilot or use it in private mode to avoid exposing confidential code.