Subverting Betteridge’s law of headlines. Yes.

  • Well, the problem is you don’t know what you don’t know. One of the first example tasks in the paper was regarding implementing a symmetric cipher. Using a weak cipher was recommended by AI tools sometimes, these developers didn’t know that some ciphers were weak. Additionally, even when the AI tool recommended a strong cipher, such as AES, it generated code that screwed up an implementation detail (failing to return the authentication tag), making the result insecure. And the user didn’t know it was wrong because they didn’t know it was incomplete.

    There’s no substitution for domain specific knowledge. Users who were forced to use traditional tools got the answer correct significantly more often because they had to read, process, and understand the documentation for the libraries, which meant they understood why the symmetric cipher was the way it is, and what additional information needed to be reported and why.

    • Well, the problem is you don’t know what you don’t know.

      This is true, even recognized in the paper. People that spend more time on writing prompts (probably knowing that this is important) actually did manage to do reasonably well. Which is exactly what I in the previous reply was hinting at.

      Because, let’s be honest, this statement is true for everything where someone starts out new. In the past (and probably still) you had people blindly copying code blocks from stackoverflow not understanding what the code or realizing how outdated the answer might be.

      So the key is still education of people and making them aware of their limitations. You can try to block the usage of tools like this, some companies actively do so. But people will be people and as long as the tools are available they will try to use them. So the more realistic approach, in my opinion, is to educate them in the usage of these tools.